text:
892-5626,
	USA. cheatham@helix.nih.gov},
  keywords = {Computer Simulation; DNA; Mathematical Computing; Nucleic Acid Conformation;
	Poly A; Poly C; Poly G; Poly T; Solutions; Solvents},
  owner = {emilio},
  pmid = {9833666},
  timestamp = {2010.04.21}
}

@ARTICLE{Chekmarev:Ishida:Levy:2004,
  author = {Chekmarev, D. and Ishida, T. and Levy, {R. M.} },
  title = {Long time conformational transitions of alanine dipeptide in aqueous
	solution: continuous and discrete state kinetic models},
  journal = {J. Phys. Chem. B},
  year = {2004},
  volume = {108},
  pages = {19487--19495},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Chen2010,
  author = {I-Jen Chen and Nicolas Foloppe},
  title = {Drug-like bioactive structures and conformational coverage with the
	LigPrep/ConfGen suite: comparison to programs MOE and catalyst.},
  journal = {J Chem Inf Model},
  year = {2010},
  volume = {50},
  pages = {822--839},
  number = {5},
  month = {May},
  abstract = {Computational conformational sampling underpins many aspects of small
	molecule modeling and design in pharmaceutical work. This work examined
	in detail the widely distributed LigPrep/ConfGen software suite and
	the conformational models it produces for drug-like compounds. We
	also compare LigPrep/ConfGen to MOE and Catalyst. Tests of the conformational
	sampling protocols included the reproduction of known bioactive structures
	of ligands, characterization of the size, coverage and diversity
	of the output conformational models, and relative computation times.
	The present tests will help the user to make informed choices among
	the predefined ConfGen protocols (Very fast, Fast, Intermediate,
	and Comprehensive), and the adjustable input parameters. The parameters
	governing the initial compound preparation (LigPrep) and the subsequent
	conformational sampling were explored. This analysis has led to a
	new protocol called "ConfGen Optimized", which improves upon the
	predefined protocols. ConfGen Optimized is computationally tractable
	and reproduced 80\% of the bioactive structures within 1 A, versus
	66\% for the default ConfGen Fast protocol. We also addressed the
	issue of the reproduction of compact/folded bioactive structures
	by ConfGen. It involved the compilation of a new set of 50 folded
	diverse drug-like bioactive structures. This indicates that heuristics
	penalizing folded conformers hinder reproduction of some binding
	modes. Overall, ConfGen offers great flexibility of use and provides
	a valuable addition to the molecular modeling toolbox.},
  comment = {Ligand reorganization},
  doi = {10.1021/ci100026x},
  institution = {D) Ltd., Granta Park, Abington, Cambridge CB21 6GB, United Kingdom.
	i.chen@vernalis.com},
  keywords = {Drug Design; Ligands; Models, Molecular; Molecular Conformation; Protein
	Binding; Proteins; Small Molecule Libraries; Software},
  owner = {emilio},
  pmid = {20423098},
  timestamp = {2010.09.08},
  url = {http://dx.doi.org/10.1021/ci100026x}
}

@ARTICLE{Chen2009,
  author = {Jianhan Chen},
  title = {Intrinsically disordered p53 extreme C-terminus binds to S100B(betabeta)
	through "fly-casting".},
  journal = {J Am Chem Soc},
  year = {2009},
  volume = {131},
  pages = {2088--2089},
  number = {6},
  month = {Feb},
  abstract = {Intrinsically disordered proteins (IDPs) are functional proteins where
	a lack of stable tertiary structures is required for function. Many
	of the IDPs involved in cellular regulation and signaling have substantial
	residual structures in the unbound state and fold into stable structures
	upon binding to their biological partners. Specific roles of these
	residual structures in and the underlying mechanisms of coupled binding
	and folding are poorly understood. Here we use physics-based atomistic
	simulations to compute the multidimensional free energy surfaces
	of coupled folding and binding of the intrinsically disordered p53
	extreme C-terminus to protein S100B(betabeta). The results show that,
	even though the unbound p53 peptide appears to sample several alternative
	folded states previously observed when in complex with various targets,
	it binds to S100B(betabeta) through formation of nonspecific complexes,
	i.e., a "fly-casting"-like process. The current work, together with
	previous NMR and coarse-grained modeling studies of another prototypical
	system, suggests that the main role of the residual structures in
	the unbound states of regulatory IDPs might be to provide thermodynamic
	control of binding through modulating the entropic cost of folding
	and not to enhance the binding rate by acting as initial contact
	sites.},
  institution = {Department of Biochemistry, Kansas State University, Manhattan, Kansas
	66506, USA.},
  keywords = {Computer Simulation; Kinetics; Models, Molecular; Nerve Growth Factors,
	chemistry; Nuclear Magnetic Resonance, Biomolecular; Protein Binding;
	Protein Conformation; S100 Proteins, chemistry; Surface Properties;
	Thermodynamics; Tumor Suppressor Protein p53, chemistry},
  language = {eng},
  medline-pst = {ppublish},
  owner = {emilio},
  pmid = {19216110},
  timestamp = {2011.07.15}
}

@ARTICLE{Chen:Brooks:2008,
  author = {Chen, J. and Brooks, {C. L. III}},
  title = {Implicit modeling of nonpolar solvation for simulating protein folding
	and conformational transitions},
  journal = {Phys. Chem. Chem. Phys.},
  year = {2008},
  volume = {10},
  pages = {471--481},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Chen:Brooks:JACS:2007,
  author = {Chen, J. and Brooks, {C. L. III}},
  title = {Critical importance of length scale dependence in implicit modeling
	of hydrophobic interactions},
  journal = {J. Am. Chem. Soc.},
  year = {2007},
  volume = {129},
  pages = {2444--2445},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Chen:Brooks:Khandogin:2008,
  author = {Chen, J. and Brooks, {C. L. III} and Khandogin, J.},
  title = {Recent advances in implicit solvent based methods for biomolecular
	simulations},
  journal = {Curr. Opin. Struct. Biol.},
  year = {2008},
  volume = {18},
  pages = {140--148},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Chen:Im:Brooks:2006,
  author = {Chen, J. and Im, W. and Brooks, {C. L. III}},
  title = {Balancing solvation and intramolecular interactions: Toward a consistent
	generalized Born force field},
  journal = {J. Am. Chem. Soc.},
  year = {2006},
  volume = {128},
  pages = {3728--3736},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Chen:Tropsha:2006,
  author = {Chen, X. and Tropsha, A.},
  title = {Calculation of the Relative Binding Affinity of Enzyme Inhibitors
	Using the Generalized Linear Response Method},
  journal = {J. Chem. Theory Comput.},
  year = {2006},
  volume = {2},
  pages = {1435--1443},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Chen2009a,
  author = {Yu Chen and Brian K Shoichet},
  title = {Molecular docking and ligand specificity in fragment-based inhibitor
	discovery.},
  journal = {Nat Chem Biol},
  year = {2009},
  volume = {5},
  pages = {358--364},
  number = {5},
  month = {May},
  abstract = {Fragment screens have successfully identified new scaffolds in drug
	discovery, often with relatively high hit rates (5\%) using small
	screening libraries (1,000-10,000 compounds). This raises two questions:
	would other noteworthy chemotypes be found were one to screen all
	commercially available fragments (>300,000), and does the success
	rate imply low specificity of fragments? We used molecular docking
	to screen large libraries of fragments against CTX-M beta-lactamase.
	We identified ten millimolar-range inhibitors from the 69 compounds
	tested. The docking poses corresponded closely to the crystallographic
	structures subsequently determined. Notably, these initial low-affinity
	hits showed little specificity between CTX-M and an unrelated beta-lactamase,
	AmpC, which is unusual among beta-lactamase inhibitors. This is consistent
	with the idea that the high hit rates among fragments correlate to
	a low initial specificity. As the inhibitors were progressed, both
	specificity and affinity rose together, yielding to our knowledge
	the first micromolar-range noncovalent inhibitors against a class
	A beta-lactamase.},
  doi = {10.1038/nchembio.155},
  institution = {Department of Pharmaceutical Chemistry, University of California,
	San Francisco, California, USA.},
  keywords = {Binding Sites; Crystallography, X-Ray; Drug Discovery; Enzyme Inhibitors;
	Ligands; Models, Molecular; Molecular Structure; beta-Lactamases},
  owner = {emilio},
  pii = {nchembio.155},
  pmid = {19305397},
  timestamp = {2010.10.26},
  url = {http://dx.doi.org/10.1038/nchembio.155}
}

@ARTICLE{Cheng2008,
  author = {Lily S Cheng and Rommie E Amaro and Dong Xu and Wilfred W Li and
	Peter W Arzberger and J. Andrew McCammon},
  title = {Ensemble-based virtual screening reveals potential novel antiviral
	compounds for avian influenza neuraminidase.},
  journal = {J Med Chem},
  year = {2008},
  volume = {51},
  pages = {3878--3894},
  number = {13},
  month = {Jul},
  abstract = {Avian influenza virus subtype H5N1 is a potential pandemic threat
	with human-adapted strains resistant to antiviral drugs. Although
	virtual screening (VS) against a crystal or relaxed receptor structure
	is an established method to identify potential inhibitors, the more
	dynamic changes within binding sites are neglected. To accommodate
	full receptor flexibility, we use AutoDock4 to screen the NCI diversity
	set against representative receptor ensembles extracted from explicitly
	solvated molecular dynamics simulations of the neuraminidase system.
	The top hits are redocked to the entire nonredundant receptor ensemble
	and rescored using the relaxed complex scheme (RCS). Of the 27 top
	hits reported, half ranked very poorly if only crystal structures
	are used. These compounds target the catalytic cavity as well as
	the newly identified 150- and 430-cavities, which exhibit dynamic
	properties in electrostatic surface and geometric shape. This ensemble-based
	VS and RCS approach may offer improvement over existing strategies
	for structure-based drug discovery.},
  comment = {Receptor reorganization},
  doi = {10.1021/jm8001197},
  institution = {National Biomedical Computation Resource, University of California,
	San Diego, La Jolla, California 92093, USA.},
  keywords = {Antiviral Agents; Binding Sites; Computer Simulation; Crystallography,
	X-Ray; Drug Evaluation, Preclinical; Enzyme Inhibitors; Influenza
	A Virus, H5N1 Subtype; Ligands; Models, Molecular; Molecular Structure;
	Neuraminidase; Solvents; Static Electricity; Structure-Activity Relationship;
	Surface Properties},
  owner = {emilio},
  pmid = {18558668},
  timestamp = {2010.09.09},
  url = {http://dx.doi.org/10.1021/jm8001197}
}

@ARTICLE{Cheng2007,
  author = {Li-Tien Cheng and Joachim Dzubiella and J. Andrew McCammon and Bo
	Li},
  title = {Application of the level-set method to the implicit solvation of
	nonpolar molecules.},
  journal = {J Chem Phys},
  year = {2007},
  volume = {127},
  pages = {084503},
  number = {8},
  month = {Aug},
  abstract = {A level-set method is developed for numerically capturing the equilibrium
	solute-solvent interface that is defined by the recently proposed
	variational implicit solvent model [Dzubiella, Swanson, and McCammon,
	Phys. Rev. Lett. 104, 527 (2006); J. Chem. Phys. 124, 084905 (2006)].
	In the level-set method, a possible solute-solvent interface is represented
	by the zero level set (i.e., the zero level surface) of a level-set
	function and is eventually evolved into the equilibrium solute-solvent
	interface. The evolution law is determined by minimization of a solvation
	free energy functional that couples both the interfacial energy and
	the van der Waals type solute-solvent interaction energy. The surface
	evolution is thus an energy minimizing process, and the equilibrium
	solute-solvent interface is an output of this process. The method
	is implemented and applied to the solvation of nonpolar molecules
	such as two xenon atoms, two parallel paraffin plates, helical alkane
	chains, and a single fullerence C(60). The level-set solutions show
	good agreement for the solvation energies when compared to available
	molecular dynamics simulations. In particular, the method captures
	solvent dewetting (nanobubble formation) and quantitatively describes
	the interaction in the strongly hydrophobic plate system.},
  doi = {10.1063/1.2757169},
  institution = {Department of Mathematics, University of California, San Diego, La
	Jolla, California 92093-0112, USA. lcheng@math.ucsd.edu},
  keywords = {Computer Simulation; Models, Chemical; Polymers, chemistry; Software;
	Solvents, chemistry; Thermodynamics},
  language = {eng},
  medline-pst = {ppublish},
  owner = {emilio},
  pmid = {17764265},
  timestamp = {2011.02.03},
  url = {http://dx.doi.org/10.1063/1.2757169}
}

@ARTICLE{Cheng2009,
  author = {Li-Tien Cheng and Yang Xie and Joachim Dzubiella and J. Andrew McCammon
	and Jianwei Che and Bo Li},
  title = {Coupling the Level-Set Method with Molecular Mechanics for Variational
	Implicit Solvation of Nonpolar Molecules.},
  journal = {J Chem Theory Comput},
  year = {2009},
  volume = {5},
  pages = {257--266},
  number = {2},
  month = {Feb},
  abstract = {We construct a variational explicit-solute implicit-solvent model
	for the solvation of molecules. Central in this model is an effective
	solvation free-energy functional that depends solely on the position
	of solute-solvent interface and solute atoms. The total free energy
	couples altogether the volume and interface energies of solutes,
	the solute-solvent van der Waals interactions, and the solute-solute
	mechanical interactions. A curvature dependent surface tension is
	incorporated through the so-called Tolman length which serves as
	the only fitting parameter in the model. Our approach extends the
	original variational implicit-solvent model of Dzubiella, Swanson,
	and McCammon [Phys. Rev. Lett. 2006, 96, 087802 and J. Chem. Phys.
	2006, 124, 084905] to include the solute molecular mechanics. We
	also develop a novel computational method that combines the level-set
	technique with optimization algorithms to determine numerically the
	equilibrium conformation of nonpolar molecules. Numerical results
	demonstrate that our new model and methods can capture essential
	properties of nonpolar molecules and their interactions with the
	solvent. In particular, with a suitable choice of the Tolman length
	for the curvature correction to the surface tension, we obtain the
	solvation free energy for a benzene molecule in a good agreement
	with experimental results.},
  doi = {10.1021/ct800297d},
  institution = {Department of Mathematics, University of California, San Diego, La
	Jolla, California 92093-0112, USA.},
  language = {eng},
  medline-pst = {ppublish},
  owner = {emilio},
  pmid = {20150952},
  timestamp = {2011.02.03},
  url = {http://dx.doi.org/10.1021/ct800297d}
}

@ARTICLE{Cheng:Prusoff:1973,
  author = {Cheng, Y.-C. and Prusoff, {W. H.}},
  title = {Relationship between the inhibition constant ($K_I$) and the concentration
	of inhibitor which causes 50 per cent inhibition ({IC}$_{50}$) of
	an enzymatic reaction},
  journal = {Biochemical Pharmacology},
  year = {1973},
  volume = {22},
  pages = {3099--3108},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@BOOK{ChernickBook2008,
  title = {Bootstrap Methods: A Guide for Practitioners and Researchers, 2nd
	ed.},
  publisher = {John Wiley \& Sons, Hoboken, NJ},
  year = {2008},
  author = {Michael R. Chernick},
  owner = {emilio},
  timestamp = {2011.11.23}
}

@ARTICLE{Chialvo:90,
  author = {Chialvo, A. A.},
  title = {Determination of Excess Gibbs Free Energy from Computer Simulation
	by the Single Charging-Integral Approach. I. Theory},
  journal = {J. Chem. Phys.},
  year = {1990},
  volume = {92},
  pages = {673},
  number = {1},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@BOOK{Chipot:Pohorille:book:2007,
  title = {Free Energy Calculations. Theory and Applications in Chemistry and
	Biology},
  publisher = {Springer, Berlin Heidelberg},
  year = {2007},
  author = {Christophe Chipot and {Andrew Pohorille (Eds.)}},
  series = {Springer Series in Chemical Physics},
  address = {Berlin Heidelberg},
  owner = {emilio},
  timestamp = {2010.05.20}
}

@ARTICLE{Chipot:Millot:Maigret:Kollman:94,
  author = {Chipot, C. and Millot, C. and Maigret, B. and Kollman, P. A.},
  journal = {J. Phys. Chem.},
  year = {1994},
  volume = {98},
  pages = {11362},
  number = {44},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Chocholousova:Feig:2006,
  author = {Chocholousova, J. and Feig, M.},
  title = {Balancing an Accurate Representation of the Molecular Surface in
	Generalized Born Formalisms with Integrator Stability in Molecular
	Dynamics Simulations},
  journal = {J. Comp. Chem.},
  year = {2006},
  volume = {27},
  pages = {719-729},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Chodera:Mobley:cosb2011,
  author = {John D. Chodera and David L. Mobley and Michael R. Shirts and Richard
	W. Dixon and Kim Branson and Vijay S. Pande},
  title = {Alchemical free energy methods for drug discovery: Progress and challenges.},
  journal = {Curr. Opin. Struct. Biol.},
  year = {2011},
  volume = {21},
  pages = {150--160},
  owner = {emilio},
  timestamp = {2011.02.04}
}

@ARTICLE{Chodera:Singhal:Pande:Dill:Swope:2007,
  author = {Chodera, {J. D.} and Singhal, N. and Pande, {V. S.} and Dill, {K.
	A.} and Swope, {W. C.}},
  title = {Automatic discovery of metastable states for the construction of
	Markov models of macromolecular conformational dynamics},
  journal = {J. Chem. Phys.},
  year = {2007},
  volume = {126},
  pages = {155101},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Chong2009,
  author = {Lillian T Chong and Jed W Pitera and William C Swope and Vijay S
	Pande},
  title = {Comparison of computational approaches for predicting the effects
	of missense mutations on p53 function.},
  journal = {J. Mol. Graph. Model.},
  year = {2009},
  volume = {27},
  pages = {978--982},
  number = {8},
  abstract = {We applied our recently developed kinetic computational mutagenesis
	(KCM) approach [L.T. Chong, W.C. Swope, J.W. Pitera, V.S. Pande,
	Kinetic computational alanine scanning: application to p53 oligomerization,
	J. Mol. Biol. 357 (3) (2006) 1039-1049] along with the MM-GBSA approach
	[J. Srinivasan, T.E. Cheatham 3rd, P. Cieplak, P.A. Kollman, D.A.
	Case, Continuum solvent studies of the stability of DNA, RNA, and
	phosphoramidate-DNA helices, J. Am. Chem. Soc. 120 (37) (1998) 9401-9409;
	P.A. Kollman, I. Massova, C.M. Reyes, B. Kuhn, S. Huo, L.T. Chong,
	M. Lee, T. Lee, Y. Duan, W. Wang, O. Donini, P. Cieplak, J. Srinivasan,
	D.A. Case, T.E. Cheatham 3rd., Calculating structures and free energies
	of complex molecules: combining molecular mechanics and continuum
	models, Acc. Chem. Res. 33 (12) (2000) 889-897] to evaluate the effects
	of all possible missense mutations on dimerization of the oligomerization
	domain (residues 326-355) of tumor suppressor p53. The true positive
	and true negative rates for KCM are comparable (within 5\%) to those
	of MM-GBSA, although MM-GBSA is much less computationally intensive
	when it is applied to a single energy-minimized configuration per
	mutant dimer. The potential advantage of KCM is that it can be used
	to directly examine the kinetic effects of mutations.},
  doi = {10.1016/j.jmgm.2008.12.006},
  institution = {Department of Chemistry, University of Pittsburgh, Pittsburgh, PA
	15260, USA. ltchong@pitt.edu},
  keywords = {Computational Biology; Computer Simulation; Humans; Mutagenesis; Mutation,
	Missense; Protein Folding; Tumor Suppressor Protein p53},
  owner = {emilio},
  pii = {S1093-3263(08)00179-4},
  pmid = {19168381},
  timestamp = {2010.04.21},
  url = {http://dx.doi.org/10.1016/j.jmgm.2008.12.006}
}

@ARTICLE{Chothia:74,
  author = {C. Chothia},
  journal = {Nature},
  year = {1974},
  volume = {248},
  pages = {338},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Christ2008,
  author = {Clara D Christ and Wilfred F van Gunsteren},
  title = {Multiple free energies from a single simulation: extending enveloping
	distribution sampling to nonoverlapping phase-space distributions.},
  journal = {J Chem Phys},
  year = {2008},
  volume = {128},
  pages = {174112},
  number = {17},
  month = {May},
  abstract = {A recently proposed method to obtain free energy differences for multiple
	end states from a single simulation of a reference state which was
	called enveloping distribution sampling (EDS) [J. Chem. Phys. 126,
	184110 (2007)] is expanded to situations where the end state configuration
	space densities do not show overlap. It uses a reference state Hamiltonian
	suggested by Han in 1992 [Phys. Lett. A 165, 28 (1992)] in a molecular
	dynamics implementation. The method allows us to calculate multiple
	free energy differences "on the fly" from a single molecular dynamics
	simulation. The influence of the parameters on the accuracy and precision
	of the obtained free energy differences is investigated. A connection
	is established between the presented method and the Bennett acceptance
	ratio method. The method is applied to four two-state test systems
	(dipole inversion, van der Waals perturbation, charge inversion,
	and water to methanol conversion) and two multiple-state test systems
	[dipole inversion with five charging states and five (dis-)appearing
	water molecules]. Accurate results could be obtained for all test
	applications if the parameters of the reference state Hamiltonian
	were optimized according to a given algorithm. The deviations from
	the exact result or from an independent calculation were at most
	0.6 kJ/mol. An accurate estimation of the free energy difference
	is always possible, independent of how different the end states are.
	However, the convergence times of the free energy differences are
	longer in cases where the end state configuration space densities
	do not show overlap [charge inversion, water to methanol conversion,
	(dis-)appearing water molecules] than in cases where the configuration
	space densities do show some overlap [(multiple) dipole inversion
	and van der Waals perturbation].},
  doi = {10.1063/1.2913050},
  institution = {Laboratory of Physical Chemistry, Swiss Federal Institute of Technology,
	ETH 8093 Zürich, Switzerland.},
  owner = {emilio},
  pmid = {18465915},
  timestamp = {2010.09.23},
  url = {http://dx.doi.org/10.1063/1.2913050}
}

@ARTICLE{Christ2007,
  author = {Clara D Christ and Wilfred F van Gunsteren},
  title = {Enveloping distribution sampling: a method to calculate free energy
	differences from a single simulation.},
  journal = {J Chem Phys},
  year = {2007},
  volume = {126},
  pages = {184110},
  number = {18},
  month = {May},
  abstract = {The authors present a method to calculate free energy differences
	between two states A and B "on the fly" from a single molecular dynamics
	simulation of a reference state R. No computer time has to be spent
	on the simulation of intermediate states. Only one state is sampled,
	i.e., the reference state R which is designed such that the subset
	of phase space important to it is the union of the parts of phase
	space important to A and B. Therefore, an accurate estimate of the
	relative free energy can be obtained by construction. The authors
	applied the method to four test systems (dipole inversion, van der
	Waals interaction perturbation, charge inversion, and water to methanol
	conversion) and compared the results to thermodynamic integration
	estimates. In two cases, the enveloping distribution sampling calculation
	was straightforward. However, in the charge inversion and the water
	to methanol conversion, Hamiltonian replica-exchange molecular dynamics
	of the reference state was necessary to observe transitions in the
	reference state simulation between the parts of phase space important
	to A and B, respectively. This can be explained by the total absence
	of phase space overlap of A and B in these two cases.},
  doi = {10.1063/1.2730508},
  institution = {Laboratory of Physical Chemistry, ETH Zürich, 8093 Zürich, Switzerland.},
  owner = {emilio},
  pmid = {17508795},
  timestamp = {2010.09.23},
  url = {http://dx.doi.org/10.1063/1.2730508}
}

@ARTICLE{Christ2009,
  author = {Clara D Christ and Wilfred F Van Gunsteren},
  title = {Comparison of three enveloping distribution sampling Hamiltonians
	for the estimation of multiple free energy differences from a single
	simulation.},
  journal = {J Comput Chem},
  year = {2009},
  volume = {30},
  pages = {1664--1679},
  number = {11},
  month = {Aug},
  abstract = {We test the performance of three different reference state Hamiltonians
	for enveloping distribution sampling (EDS). EDS is an implementation
	of umbrella sampling which allows estimation of various free energy
	differences "on the fly" from a single simulation. This is achieved
	by construction of a reference state, which envelopes the regions
	of configuration space important to the various end states of interest.
	The proposed Hamiltonians differ in the way energy barriers separating
	these regions of configuration space are reduced. The test system
	consisted of 17 disubstituted benzenes in water and in complex with
	alpha-cyclodextrin. The calculated free energy differences correlate
	with thermodynamic integration results (R(2) > 0.99 for the ligands
	in water and R(2) > 0.98 for the ligands in complex with alpha-cyclodextrin).
	One of the reference state Hamiltonians outperformed the others in
	sampling the configuration space important to the various end states.
	In this reference state not all barriers between all pairs of states
	are reduced. Instead a minimum spanning tree of states is calculated,
	which connects states that are "closest" in configuration space.},
  doi = {10.1002/jcc.21325},
  institution = {Laboratory of Physical Chemistry, Swiss Federal Institute of Technology,
	ETH, 8093 Zürich, Switzerland.},
  keywords = {Algorithms; Benzene; Binding Sites; Computer Simulation; Ligands;
	Models, Chemical; Models, Molecular; Thermodynamics; Water; alpha-Cyclodextrins},
  owner = {emilio},
  pmid = {19504591},
  timestamp = {2010.09.23},
  url = {http://dx.doi.org/10.1002/jcc.21325}
}

@ARTICLE{Christ2010,
  author = {Clara D Christ and Alan E Mark and Wilfred F van Gunsteren},
  title = {Basic ingredients of free energy calculations: a review.},
  journal = {J Comput Chem},
  year = {2010},
  volume = {31},
  pages = {1569--1582},
  number = {8},
  month = {Jun},
  abstract = {Methods to compute free energy differences between different states
	of a molecular system are reviewed with the aim of identifying their
	basic ingredients and their utility when applied in practice to biomolecular
	systems. A free energy calculation is comprised of three basic components:
	(i) a suitable model or Hamiltonian, (ii) a sampling protocol with
	which one can generate a representative ensemble of molecular configurations,
	and (iii) an estimator of the free energy difference itself. Alternative
	sampling protocols can be distinguished according to whether one
	or more states are to be sampled. In cases where only a single state
	is considered, six alternative techniques could be distinguished:
	(i) changing the dynamics, (ii) deforming the energy surface, (iii)
	extending the dimensionality, (iv) perturbing the forces, (v) reducing
	the number of degrees of freedom, and (vi) multi-copy approaches.
	In cases where multiple states are to be sampled, the three primary
	techniques are staging, importance sampling, and adiabatic decoupling.
	Estimators of the free energy can be classified as global methods
	that either count the number of times a given state is sampled or
	use energy differences. Or, they can be classified as local methods
	that either make use of the force or are based on transition probabilities.
	Finally, this overview of the available techniques and how they can
	be best used in a practical context is aimed at helping the reader
	choose the most appropriate combination of approaches for the biomolecular
	system, Hamiltonian and free energy difference of interest.},
  doi = {10.1002/jcc.21450},
  institution = {Laboratory of Physical Chemistry, Swiss Federal Institute of Technology,
	ETH, Zürich 8093, Switzerland.},
  keywords = {Models, Molecular; Molecular Dynamics Simulation; Monte Carlo Method;
	Thermodynamics},
  owner = {emilio},
  pmid = {20033914},
  timestamp = {2010.09.23},
  url = {http://dx.doi.org/10.1002/jcc.21450}
}

@ARTICLE{Christen2007,
  author = {Markus Christen and Clara D Christ and Wilfred F van Gunsteren},
  title = {Free energy calculations using flexible-constrained, hard-constrained
	and non-constrained molecular dynamics simulations.},
  journal = {Chemphyschem},
  year = {2007},
  volume = {8},
  pages = {1557--1564},
  number = {10},
  month = {Jul},
  abstract = {A comparison of different treatments of bond-stretching interactions
	in molecular dynamics simulation is presented. Relative free energies
	from simulations using rigid bonds maintained with the SHAKE algorithm,
	using partially rigid bonds maintained with a recently introduced
	flexible constraints algorithm, and using fully flexible bonds are
	compared in a multi-configurational thermodynamic integration calculation
	of changing liquid water into liquid methanol. The formula for the
	free energy change due to a changing flexible constraint in a flexible
	constraint simulation is derived. To allow for a more direct comparison
	between these three methods, three different pairs of models for
	water and methanol were used: a flexible model (simulated without
	constraints and with flexible constraints), a rigid model (simulated
	with standard hard constraints), and an alternative flexible model
	(simulated with flexible constraints and standard hard constraints)
	in which the ideal or constrained bond lengths correspond to the
	average bond lengths obtained from a short simulation of the unconstrained
	flexible model. The particular treatment of the bonds induces differences
	of up to 2 \% in the liquid densities, whereas (excess) free energy
	differences of up to 5.7 (4.3) kJ mol(-1) are observed. These values
	are smaller than the differences observed between the three different
	pairs of methanol/water models: up to 5 \% in density and up to 8.5
	kJ mol(-1) in (excess) free energy.},
  doi = {10.1002/cphc.200700176},
  institution = {Laboratory of Physical Chemistry, Swiss Federal Institute of Technology,
	ETH, 8093 Zürich, Switzerland.},
  keywords = {Algorithms; Chemistry, Physical; Methanol; Models, Chemical; Models,
	Statistical; Physicochemical Phenomena; Thermodynamics; Water},
  owner = {emilio},
  pmid = {17577902},
  timestamp = {2010.09.23},
  url = {http://dx.doi.org/10.1002/cphc.200700176}
}

@ARTICLE{Christen2008,
  author = {Markus Christen and Wilfred F van Gunsteren},
  title = {On searching in, sampling of, and dynamically moving through conformational
	space of biomolecular systems: A review.},
  journal = {J Comput Chem},
  year = {2008},
  volume = {29},
  pages = {157--166},
  number = {2},
  month = {Jan},
  abstract = {Methods to search for low-energy conformations, to generate a Boltzmann-weighted
	ensemble of configurations, or to generate classical-dynamical trajectories
	for molecular systems in the condensed liquid phase are briefly reviewed
	with an eye to application to biomolecular systems. After having
	chosen the degrees of freedom and method to generate molecular configurations,
	the efficiency of the search or sampling can be enhanced in various
	ways: (i) efficient calculation of the energy function and forces,
	(ii) application of a plethora of search enhancement techniques,
	(iii) use of a biasing potential energy term, and (iv) guiding the
	sampling using a reaction or transition pathway. The overview of
	the available methods should help the reader to choose the combination
	that is most suitable for the biomolecular system, degrees of freedom,
	interaction function, and molecular or thermodynamic properties of
	interest.},
  doi = {10.1002/jcc.20725},
  institution = {Laboratory of Physical Chemistry, Swiss Federal Institute of Technology
	Zürich, ETH, CH-8093 Zürich, Switzerland.},
  keywords = {Algorithms; Biotechnology, methods; Computer Simulation; Energy Transfer;
	Molecular Conformation; Thermodynamics},
  language = {eng},
  medline-pst = {ppublish},
  owner = {emilio},
  pmid = {17570138},
  timestamp = {2011.07.15},
  url = {http://dx.doi.org/10.1002/jcc.20725}
}

@ARTICLE{Christenson:Claesson:88,
  author = {Christenson, H. K. and Claesson, P. M.},
  title = {Cavitation and the Interaction Between Macroscopic Hydrophobic Surfaces},
  journal = {Science},
  year = {1988},
  volume = {239},
  pages = {390},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Cichocki:89,
  author = {Cichocki, B. and Felderhof, B. and Hinsen, K.},
  journal = {Phys. Rev. A},
  year = {1989},
  volume = {39},
  pages = {5350-5356},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Clark2006,
  author = {Matthew Clark and Frank Guarnieri and Igor Shkurko and Jeff Wiseman},
  title = {Grand canonical Monte Carlo simulation of ligand-protein binding.},
  journal = {J Chem Inf Model},
  year = {2006},
  volume = {46},
  pages = {231--242},
  number = {1},
  abstract = {A new application of the grand canonical thermodynamics ensemble to
	compute ligand-protein binding is described. The described method
	is sufficiently rapid that it is practical to compute ligand-protein
	binding free energies for a large number of poses over the entire
	protein surface, thus identifying multiple putative ligand binding
	sites. In addition, the method computes binding free energies for
	a large number of poses. The method is demonstrated by the simulation
	of two protein-ligand systems, thermolysin and T4 lysozyme, for which
	there is extensive thermodynamic and crystallographic data for the
	binding of small, rigid ligands. These low-molecular-weight ligands
	correspond to the molecular fragments used in computational fragment-based
	drug design. The simulations correctly identified the experimental
	binding poses and rank ordered the affinities of ligands in each
	of these systems.},
  doi = {10.1021/ci050268f},
  institution = {Locus Pharmaceuticals Four Valley Square, Blue Bell, Pennsylvania
	19422, USA. mclark@locuspharma.com},
  keywords = {Binding Sites; Computer Simulation; Ligands; Models, Molecular; Monte
	Carlo Method; Muramidase; Protein Binding; Protein Conformation;
	Thermolysin},
  owner = {emilio},
  pmid = {16426059},
  timestamp = {2010.10.26},
  url = {http://dx.doi.org/10.1021/ci050268f}
}

@ARTICLE{Clark2009,
  author = {Matthew Clark and Siavash Meshkat and George T Talbot and Paolo Carnevali
	and Jeffrey S Wiseman},
  title = {Fragment-based computation of binding free energies by systematic
	sampling.},
  journal = {J Chem Inf Model},
  year = {2009},
  volume = {49},
  pages = {1901--1913},
  number = {8},
  month = {Aug},
  abstract = {A fragment-based method for computing protein-ligand binding free
	energies by systematic sampling has been developed. Systematic sampling
	of fragment-protein interactions in translational and rotational
	space is followed by de novo assembly of fragments into molecules
	and computation of binding free energies for the molecules with statistical
	mechanics. The rigorous sampling provides independence from the choice
	of initial binding pose and assembling fragments enables evaluation
	of binding of a large number of molecule poses with relatively little
	computation. The method allows a full sampling of possible conformations
	and avoids the "conformational focusing" problem associated with
	free energy methods that sample only limited conformational and orientation
	changes from a starting pose. The direct computation of the entropy
	loss upon assembling fragments into molecules is an innovation for
	fragment-based methods. The computed binding free energies are compared
	to calorimetric data for a series of ligands for the T4 lysozyme
	L99A mutant and binding constants for a series of p38 MAP kinase
	ligands. In both cases, the standard error of prediction is close
	to 1 kcal/mol.},
  doi = {10.1021/ci900132r},
  institution = {Locus Pharmaceuticals, Blue Bell, PA 19422, USA.},
  keywords = {Bacteriophage T4; Computer Simulation; Humans; Ligands; Models, Molecular;
	Muramidase; Protein Binding; Protein Conformation; Proteins; Thermodynamics;
	p38 Mitogen-Activated Protein Kinases},
  owner = {emilio},
  pmid = {19610599},
  timestamp = {2010.10.26},
  url = {http://dx.doi.org/10.1021/ci900132r}
}

@ARTICLE{Clark2009a,
  author = {Matthew Clark and Sia Meshkat and Jeffrey S Wiseman},
  title = {Grand canonical free-energy calculations of protein-ligand binding.},
  journal = {J Chem Inf Model},
  year = {2009},
  volume = {49},
  pages = {934--943},
  number = {4},
  month = {Apr},
  abstract = {The principles behind the computation of protein-ligand binding free
	energies by Monte Carlo simulation in the Grand Canonical Ensemble
	are described in detail, and two variations of the calculation are
	presented. The computation can be performed by bathing a protein
	binding site either with ligand images that interact with each other
	or with ligand images that pass through each other. The second method
	is theoretically more rigorous, but we show that both methods lead
	to the same result, and there are distinct numeric advantages to
	using ligand images that interact with each other. The Grand Canonical
	simulation provides gas-phase binding free energies that can be converted
	to aqueous energies by generalized Born-surface area (GB/SA) solvation
	calculations to provide values that agree with experiment within
	+/-1.5 kcal/mol. However, the accuracy of these simple solvation
	calculations is a major limiting factor in the accuracy of the overall
	binding free-energy computation. The Grand Canonical simulation has
	several characteristics beneficial to free-energy calculations. One
	is that the number of parameters that must be set for the simulation
	is small and can be determined objectively, making the outcome more
	deterministic, with respect to choice of input conditions, as compared
	to perturbation methods. Second, the simulation is free from assumptions
	about the starting pose or nature of the binding site. A final benefit
	is that binding free energies are a direct outcome of the simulation,
	and little processing is required to determine them.},
  doi = {10.1021/ci8004397},
  institution = {Locus Pharmaceuticals, Four Valley Square, 512 Township Line Road,
	Blue Bell, Pennsylvania 19422, USA. mclark@drmatthewclark.com},
  keywords = {Algorithms; Bacteriophage T4; Binding Sites; Computational Biology;
	Computer Simulation; Energy Transfer; Ligands; Models, Statistical;
	Monte Carlo Method; Muramidase; Mutation; Protein Binding; Proteins},
  owner = {emilio},
  pmid = {19309088},
  timestamp = {2010.10.26},
  url = {http://dx.doi.org/10.1021/ci8004397}
}

@BOOK{Coffin:Hughes:Varmus:1997,
  title = {Retroviruses at the National Center for Biotechnology Information},
  publisher = {Cold Spring Harbor: Cold Spring Harbor Laboratory},
  year = {1997},
  author = {Coffin, {J. M.} and Hughes, {S. H.} and Varmus, {H. E.}},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Cojocaru2007,
  author = {Vlad Cojocaru and Peter J Winn and Rebecca C Wade},
  title = {The ins and outs of cytochrome {P}450s.},
  journal = {Biochim Biophys Acta},
  year = {2007},
  volume = {1770},
  pages = {390--401},
  number = {3},
  month = {Mar},
  abstract = {The active site of cytochromes P450 is situated deep inside the protein
	next to the heme cofactor. Consequently, enzyme specificity and kinetics
	can be influenced by how substrates pass through the protein to access
	the active site and how products egress from the active site. We
	previously analysed the channels between the active site and the
	protein surface in P450 crystal structures available in October 2003
	[R.C. Wade, P.J. Winn, I. Schlichting, Sudarko, A survey of active
	site access channels in cytochromes P450, J. Inorg. Biochem. 98 (2004)
	1175-1182]. Since then, 52 new P450 structures have been made available,
	including entries for ten isozymes for which structures were not
	previously available. We present an updated survey covering all P450
	crystal structures available in March 2006. This survey shows channels
	not observed earlier in crystal structures, some of which were identified
	in previous molecular dynamics simulations. The crystal structures
	demonstrate how some of the channels can merge when the protein structure
	opens up resulting in a wide cleft to the active site, caused largely
	by movements of the F-G helix-loop-helix and the B-C loop. Significant
	differences were observed between the channels in the crystal structures
	of the mammalian and bacterial enzymes. The multiplicity of channels
	suggests possibilities for substrate channelling to and from the
	P450s.},
  doi = {10.1016/j.bbagen.2006.07.005},
  institution = {Molecular and Cellular Modeling Group, EML Research, Schloss-Wolfsbrunnenweg
	33, 69118 Heidelberg, Germany.},
  keywords = {Binding Sites; Cytochrome P-450 Enzyme System; Models, Molecular;
	Protein Conformation; Protein Folding},
  owner = {emilio},
  pii = {S0304-4165(06)00205-4},
  pmid = {16920266},
  timestamp = {2010.09.07},
  url = {http://dx.doi.org/10.1016/j.bbagen.2006.07.005}
}

@ARTICLE{Colizzi2010,
  author = {Colizzi, F. and Perozzo, R. and Scapozza, L. and Recanatini, M. and
	Cavalli, A.},
  title = {Single-molecule pulling simulations can discern active from inactive
	enzyme inhibitors},
  journal = {J. Am. Chem. Soc.},
  year = {2010},
  volume = {132},
  pages = {7361-71},
  number = {21},
  abstract = {Understanding ligand-protein recognition and interaction processes
	is of primary importance for structure-based drug design. Traditionally,
	several approaches combining docking and molecular dynamics (MD)
	simulations have been exploited to investigate the physicochemical
	properties of complexes of pharmaceutical interest. Even if the geometric
	properties of a modeled protein-ligand complex can be well predicted
	by computational methods, it is challenging to rank a series of analogues
	in a consistent fashion with biological data. In the unique beta-hydroxyacyl-ACP
	dehydratase of Plasmodium falciparum (PfFabZ), the application of
	standard molecular docking and MD simulations was partially sufficient
	to shed light on the activity of previously discovered inhibitors.
	Complementing docking results with atomistic simulations in the steered
	molecular dynamics (SMD) framework, we devised an in silico approach
	to study molecular interactions and to compare the binding characteristics
	of ligand analogues. We hypothesized an interaction model that both
	explained the biological activity of known ligands, and provided
	insight into designing novel enzyme inhibitors. Mimicking single-molecule
	pulling experiments, we used SMD-derived force profiles to discern
	active from inactive compounds for the first time. A new compound
	was designed and its biological activity toward the PfFabZ enzyme
	predicted. Finally, the computational predictions were experimentally
	confirmed, highlighting the robustness of the drug design approach
	presented herein.},
  address = {Department of Pharmaceutical Sciences, University of Bologna, Via
	Belmeloro 6, I-40126 Bologna, Italy. francesco.colizzi@unibo.it},
  comment = {Jun 2

	Single-molecule pulling simulations can discern active from inactive
	enzyme inhibitors

	20462212

	Colizzi, Francesco Perozzo, Remo Scapozza, Leonardo Recanatini, Maurizio
	Cavalli, Andrea Research Support, Non-U.S. Gov't United States Journal
	of the American Chemical Society J Am Chem Soc. 2010 Jun 2;132(21):7361-71.

	eng},
  issn = {1520-5126 (Electronic) 0002-7863 (Linking)},
  keywords = {Antimalarials/*chemistry/pharmacology *Drug Design Enzyme Inhibitors/*chemistry/pharmacology
	Flavonoids/*chemistry/pharmacology Hydro-Lyases/antagonists & inhibitors/*chemistry
	Luteolin/chemistry/pharmacology *Molecular Dynamics Simulation Plasmodium
	falciparum/drug effects/*enzymology Protein Conformation Structure-Activity
	Relationship},
  owner = {mauro},
  refid = {42},
  timestamp = {2011.07.22},
  url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=20462212}
}

@ARTICLE{Congreve2008,
  author = {Miles Congreve and Gianni Chessari and Dominic Tisi and Andrew J
	Woodhead},
  title = {Recent developments in fragment-based drug discovery.},
  journal = {J. Med. Chem.},
  year = {2008},
  volume = {51},
  pages = {3661--3680},
  number = {13},
  month = {Jul},
  doi = {10.1021/jm8000373},
  institution = {Astex Therapeutics Ltd., 436 Cambridge Science Park, Milton Road,
	Cambridge CB4 0QA, UK. m.congreve@astex-therapeutics.com},
  keywords = {Databases, Factual; Drug Design; Drug Evaluation, Preclinical; Humans;
	Ligands; Protein Binding; Proteins},
  owner = {emilio},
  pmid = {18457385},
  timestamp = {2010.10.26},
  url = {http://dx.doi.org/10.1021/jm8000373}
}

@ARTICLE{Connelly:94,
  author = {Connelly, P. R. and Aldape, R. A. and Bruzzese, F. J. and Chambers,
	S. P. and Fitzgibbon, M. J. and Fleming, M. A. and Itoh, S. and Livingston,
	D. J. and Navia, M. A. and Thomson, J. A. and Wilson, K. P.},
  title = {Enthalpy of Hydrogen Bond Formation in a Protein-Ligand Binding Reaction},
  journal = {Proc. Natl. Acad. Sci. USA},
  year = {1994},
  volume = {91},
  pages = {1964-1968},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Connolly:85,
  author = {Connolly, M. L.},
  title = {Computation of Molecular Volume},
  journal = {J. Am. Chem. Soc.},
  year = {1985},
  volume = {107},
  pages = {1118-24},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Connolly:83,
  author = {Connolly, M. L.},
  title = {Analytical Molecular Surface Calculation},
  journal = {J. of Applied Crystallography},
  year = {1983},
  volume = {16},
  pages = {548-558},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Cornell1995,
  author = {Cornell, Wendy D. and Cieplak, Piotr and Bayly, Christopher I. and
	Gould, Ian R. and Merz, Kenneth M. and Ferguson, David M. and Spellmeyer,
	David C. and Fox, Thomas and Caldwell, James W. and Kollman, Peter
	A.},
  title = {A Second Generation Force Field for the Simulation of Proteins, Nucleic
	Acids, and Organic Molecules},
  journal = {Journal of the American Chemical Society},
  year = {1995},
  volume = {117},
  pages = {5179--5197},
  number = {19},
  month = may,
  abstract = {null},
  comment = {doi: 10.1021/ja00124a002},
  issn = {0002-7863},
  owner = {emilio},
  publisher = {American Chemical Society},
  timestamp = {2011.02.07},
  url = {http://dx.doi.org/10.1021/ja00124a002}
}

@ARTICLE{Cortis:Friesner:97,
  author = {Cortis, C. M. and Friesner, R. A.},
  journal = {J. Comp. Chem.},
  year = {1997},
  volume = {18},
  pages = {1591-1608},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Cossins2008,
  author = {Benjamin P Cossins and Sebastien Foucher and Colin M Edge and Jonathan
	W Essex},
  title = {Protein-ligand binding affinity by nonequilibrium free energy methods.},
  journal = {J Phys Chem B},
  year = {2008},
  volume = {112},
  pages = {14985--14992},
  number = {47},
  month = {Nov},
  abstract = {Nonequilibrium (NE) free energy methods are embarrassingly parallel
	and may be very conveniently run on desktop computers using distributed
	computing software. In recent years there has been a proliferation
	of NE methods, but these approaches have barely, if at all, been
	used in the context of calculating protein-ligand binding free energies.
	In a recent study by these authors, different combinations of NE
	methods with various test systems were compared and protocols identified
	which yielded results as accurate as replica exchange thermodynamic
	integration (RETI). The NE approaches, however, lend themselves to
	extensive parallelization through the use of distributed computing.
	Here the best performing of those NE protocols, a replica exchange
	method using Bennett's acceptance ratio as the free energy estimator
	(RENE), is applied to two sets of congeneric inhibitors bound to
	neuraminidase and cyclooxygenase-2. These protein-ligand systems
	were originally studied with RETI, giving results to which NE and
	RENE simulations are compared. These NE calculations were carried
	out on a large, highly distributed group of low-performance desktop
	computers which are part of a Condor pool. RENE was found to produce
	results of a predictive quality at least as good as RETI in less
	than half the wall clock time. However, non-RE NE results were found
	to be far less predictive. In addition, the RENE method successfully
	identified a localized region of rapidly changing free energy gradients
	without the need for prior investigation. These results suggest that
	the RENE protocol is appropriate for use in the context of predicting
	protein-ligand binding free energies and that it can offer advantages
	over conventional, equilibrium approaches.},
  doi = {10.1021/jp803533w},
  institution = {School of Chemistry, University of Southampton, Highfield, Southampton,
	UK.},
  keywords = {Ligands; Neuraminidase; Proteins; Thermodynamics},
  owner = {emilio},
  pmid = {18973369},
  timestamp = {2010.09.17},
  url = {http://dx.doi.org/10.1021/jp803533w}
}

@ARTICLE{Cramer:Truhlar:99,
  author = {Cramer, C. J. and Truhlar, D.},
  title = {Implicit Solvent Models: Equilibria, Structure, Spectra, and Dynamics},
  journal = {Chem. Rev.},
  year = {1999},
  volume = {99},
  pages = {2161-2200},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Cross:86,
  author = {Cross, A. J.},
  journal = {J. Chem. Phys. Lett.},
  year = {1986},
  volume = {128},
  pages = {198},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Csermely2010,
  author = {Peter Csermely and Robin Palotai and Ruth Nussinov},
  title = {Induced fit, conformational selection and independent dynamic segments:
	an extended view of binding events.},
  journal = {Trends Biochem. Sci.},
  year = {2010},
  volume = {35},
  pages = {539--546},
  month = {Jun},
  abstract = {Single molecule and NMR measurements of protein dynamics increasingly
	uncover the complexity of binding scenarios. Here, we describe an
	extended conformational selection model that embraces a repertoire
	of selection and adjustment processes. Induced fit can be viewed
	as a subset of this repertoire, whose contribution is affected by
	the bond types stabilizing the interaction and the differences between
	the interacting partners. We argue that protein segments whose dynamics
	are distinct from the rest of the protein ('discrete breathers')
	can govern conformational transitions and allosteric propagation
	that accompany binding processes and, as such, might be more sensitive
	to mutational events. Additionally, we highlight the dynamic complexity
	of binding scenarios as they relate to events such as aggregation
	and signalling, and the crowded cellular environment.},
  doi = {10.1016/j.tibs.2010.04.009},
  institution = {Department of Medical Chemistry, Semmelweis University, PO Box 260.,
	H-1444 Budapest 8, Hungary.},
  owner = {emilio},
  pii = {S0968-0004(10)00088-5},
  pmid = {20541943},
  timestamp = {2010.09.30},
  url = {http://dx.doi.org/10.1016/j.tibs.2010.04.009}
}

@ARTICLE{Cui2008a,
  author = {Qiang Cui and Martin Karplus},
  title = {Allostery and cooperativity revisited.},
  journal = {Protein Sci},
  year = {2008},
  volume = {17},
  pages = {1295--1307},
  number = {8},
  month = {Aug},
  abstract = {Although phenomenlogical models that account for cooperativity in
	allosteric systems date back to the early and mid-60's (e.g., the
	KNF and MWC models), there is resurgent interest in the topic due
	to the recent experimental and computational studies that attempted
	to reveal, at an atomistic level, how allostery actually works. In
	this review, using systems for which atomistic simulations have been
	carried out in our groups as examples, we describe the current understanding
	of allostery, how the mechanisms go beyond the classical MWC/Pauling-KNF
	descriptions, and point out that the "new view" of allostery, emphasizing
	"population shifts," is, in fact, an "old view." The presentation
	offers not only an up-to-date description of allostery from a theoretical/computational
	perspective, but also helps to resolve several outstanding issues
	concerning allostery.},
  doi = {10.1110/ps.03259908},
  institution = {Department of Chemistry and Theoretical Chemistry Institute, University
	of Wisconsin, Madison, Wisconsin 53706, USA.},
  keywords = {Allosteric Regulation; Allosteric Site; Animals; Dimerization; Hemoglobins;
	Humans; Models, Molecular; Protein Structure, Quaternary; Protein
	Structure, Tertiary; Proteins},
  owner = {emilio},
  pii = {ps.03259908},
  pmid = {18560010},
  timestamp = {2011.01.18},
  url = {http://dx.doi.org/10.1110/ps.03259908}
}

@ARTICLE{Cui2009,
  author = {Qinghua Cui and Enrico O Purisima and Edwin Wang},
  title = {Protein evolution on a human signaling network.},
  journal = {BMC Syst Biol},
  year = {2009},
  volume = {3},
  pages = {21},
  abstract = {BACKGROUND: The architectural structure of cellular networks provides
	a framework for innovations as well as constraints for protein evolution.
	This issue has previously been studied extensively by analyzing protein
	interaction networks. However, it is unclear how signaling networks
	influence and constrain protein evolution and conversely, how protein
	evolution modifies and shapes the functional consequences of signaling
	networks. In this study, we constructed a human signaling network
	containing more than 1,600 nodes and 5,000 links through manual curation
	of signaling pathways, and analyzed the dN/dS values of human-mouse
	orthologues on the network. RESULTS: We revealed that the protein
	dN/dS value decreases along the signal information flow from the
	extracellular space to nucleus. In the network, neighbor proteins
	tend to have similar dN/dS ratios, indicating neighbor proteins have
	similar evolutionary rates: co-fast or co-slow. However, different
	types of relationships (activating, inhibitory and neutral) between
	proteins have different effects on protein evolutionary rates, i.e.,
	physically interacting protein pairs have the closest evolutionary
	rates. Furthermore, for directed shortest paths, the more distant
	two proteins are, the less chance they share similar evolutionary
	rates. However, such behavior was not observed for neutral shortest
	paths. Fast evolving signaling proteins have two modes of evolution:
	immunological proteins evolve more independently, while apoptotic
	proteins tend to form network components with other signaling proteins
	and share more similar evolutionary rates, possibly enhancing rapid
	information exchange between apoptotic and other signaling pathways.
	CONCLUSION: Major network constraints on protein evolution in protein
	interaction networks previously described have been found for signaling
	networks. We further uncovered how network characteristics affect
	the evolutionary and co-evolutionary behavior of proteins and how
	protein evolution can modify the existing functionalities of signaling
	networks. These new insights provide some general principles for
	understanding protein evolution in the context of signaling networks.},
  doi = {10.1186/1752-0509-3-21},
  institution = {Biotechnology Research Institute, National Research Council Canada,
	Montreal, Quebec, Canada. cuiqinghua@bjmu.edu.cn},
  keywords = {Animals; Evolution, Molecular; Humans; Metabolic Networks and Pathways;
	Mice; Models, Biological; Models, Genetic; Proteins; Signal Transduction;
	Systems Biology},
  owner = {emilio},
  pii = {1752-0509-3-21},
  pmid = {19226461},
  timestamp = {2010.05.20},
  url = {http://dx.doi.org/10.1186/1752-0509-3-21}
}

@ARTICLE{Cui2008,
  author = {Qizhi Cui and Traian Sulea and Joseph D Schrag and Christine Munger
	and Ming-Ni Hung and Marwen Naïm and Miroslaw Cygler and Enrico O
	Purisima},
  title = {Molecular dynamics-solvated interaction energy studies of protein-protein
	interactions: the MP1-p14 scaffolding complex.},
  journal = {J Mol Biol},
  year = {2008},
  volume = {379},
  pages = {787--802},
  number = {4},
  month = {Jun},
  abstract = {Using the MP1-p14 scaffolding complex from the mitogen-activated protein
	kinase signaling pathway as model system, we explored a structure-based
	computational protocol to probe and characterize binding affinity
	hot spots at protein-protein interfaces. Hot spots are located by
	virtual alanine-scanning consensus predictions over three different
	energy functions and two different single-structure representations
	of the complex. Refined binding affinity predictions for select hot-spot
	mutations are carried out by applying first-principle methods such
	as the molecular mechanics generalized Born surface area (MM-GBSA)
	and solvated interaction energy (SIE) to the molecular dynamics (MD)
	trajectories for mutated and wild-type complexes. Here, predicted
	hot-spot residues were actually mutated to alanine, and crystal structures
	of the mutated complexes were determined. Two mutated MP1-p14 complexes
	were investigated, the p14(Y56A)-mutated complex and the MP1(L63A,L65A)-mutated
	complex. Alternative ways to generate MD ensembles for mutant complexes,
	not relying on crystal structures for mutated complexes, were also
	investigated. The SIE function, fitted on protein-ligand binding
	affinities, gave absolute binding affinity predictions in excellent
	agreement with experiment and outperformed standard MM-GBSA predictions
	when tested on the MD ensembles of Ras-Raf and Ras-RalGDS protein-protein
	complexes. For wild-type and mutant MP1-p14 complexes, SIE predictions
	of relative binding affinities were supported by a yeast two-hybrid
	assay that provided semiquantitative relative interaction strengths.
	Results on the MP1-mutated complex suggested that SIE predictions
	deteriorate if mutant MD ensembles are approximated by just mutating
	the wild-type MD trajectory. The SIE data on the p14-mutated complex
	indicated feasibility for generating mutant MD ensembles from mutated
	wild-type crystal structure, despite local structural differences
	observed upon mutation. For energetic considerations, this would
	circumvent costly needs to produce and crystallize mutated complexes.
	The sensitized protein-protein interface afforded by the p14(Y56A)
	mutation identified here has practical applications in screening-based
	discovery of first-generation small-molecule hits for further development
	into specific modulators of the mitogen-activated protein kinase
	signaling pathway.},
  doi = {10.1016/j.jmb.2008.04.035},
  institution = {Biotechnology Research Institute, National Research Council Canada,
	6100 Royalmount Avenue, Montreal, Quebec, Canada.},
  keywords = {Adaptor Proteins, Signal Transducing; Amino Acid Substitution; Binding
	Sites; Crystallography, X-Ray; MAP Kinase Signaling System; Models,
	Molecular; Multiprotein Complexes; Mutagenesis, Site-Directed; Protein
	Interaction Domains and Motifs; Proteins; Recombinant Proteins; Thermodynamics;
	Two-Hybrid System Techniques},
  owner = {emilio},
  pii = {S0022-2836(08)00467-1},
  pmid = {18479705},
  timestamp = {2010.05.20},
  url = {http://dx.doi.org/10.1016/j.jmb.2008.04.035}
}

@ARTICLE{Curutchet:Cramer:Truhlar:2003,
  author = {Curutchet, C. and Cramer, C. J. and Truhlar, D. G. and Ruiz-L\`{o}pez,
	M. F. and Rinaldi, D. and Orozco, M. and Luque, F. J.},
  title = {Electrostatic Component of Solvation: Comparison of SCRF Continuum
	Models},
  journal = {J. Comp. Chem.},
  year = {2003},
  volume = {24},
  pages = {284-297},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Dahiyat:Mayo:1997,
  author = {Dahiyat, {B. I.} and Mayo, {S. L.}},
  title = {De novo protein design: fully automated sequence selection},
  journal = {Science},
  year = {1997},
  volume = {278},
  pages = {82-87},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Dahiyat:Sarisky:Mayo:1997,
  author = {Dahiyat, {B. I.} and Sarisky, {C. A.} and Mayo, {S. L.}},
  title = {De novo protein design: towards fully automated sequence selection},
  journal = {J. Mol. Biol.},
  year = {1997},
  volume = {273},
  pages = {789-796},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Dang:94,
  author = {Dang, L. X.},
  title = {Potential of Mean Force for the Methane-Methane Pair in Water},
  journal = {J. Chem. Phys.},
  year = {1994},
  volume = {100},
  pages = {9032},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Dang:Petitt:90,
  author = {Dang, L. X. and Petitt, B. M.},
  journal = {J. Phys. Chem.},
  year = {1990},
  volume = {94},
  pages = {4303-4311},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Namor:91,
  author = {Danil de Namor, A. F. and Ritt, M.-C. and Schwing-Weill, M.-J. and
	Arn{\'{a}}ud-Neu, F. and Lewis, D. V. F.},
  title = {Solution thermodynamics of amino acid-18-crown-6 and amino-acid-cryptand
	222 complexes in methanol and ethanol. Linear enthalpy-entropy compensation
	effect},
  journal = {J. Chem. Soc. Faraday trans.},
  year = {1991},
  volume = {87},
  pages = {3231-3239},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Darden:93,
  author = {Darden, T. A. and York, D. M. and Pedersen, L. G.},
  journal = {J. Chem. Phys.},
  year = {1993},
  volume = {98},
  pages = {10089-10092},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Darve2008,
  author = {Eric Darve and David Rodríguez-Gómez and Andrew Pohorille},
  title = {Adaptive biasing force method for scalar and vector free energy calculations.},
  journal = {J Chem Phys},
  year = {2008},
  volume = {128},
  pages = {144120},
  number = {14},
  month = {Apr},
  abstract = {In free energy calculations based on thermodynamic integration, it
	is necessary to compute the derivatives of the free energy as a function
	of one (scalar case) or several (vector case) order parameters. We
	derive in a compact way a general formulation for evaluating these
	derivatives as the average of a mean force acting on the order parameters,
	which involves first derivatives with respect to both Cartesian coordinates
	and time. This is in contrast with the previously derived formulas,
	which require first and second derivatives of the order parameter
	with respect to Cartesian coordinates. As illustrated in a concrete
	example, the main advantage of this new formulation is the simplicity
	of its use, especially for complicated order parameters. It is also
	straightforward to implement in a molecular dynamics code, as can
	be seen from the pseudocode given at the end. We further discuss
	how the approach based on time derivatives can be combined with the
	adaptive biasing force method, an enhanced sampling technique that
	rapidly yields uniform sampling of the order parameters, and by doing
	so greatly improves the efficiency of free energy calculations. Using
	the backbone dihedral angles Phi and Psi in N-acetylalanyl-N'-methylamide
	as a numerical example, we present a technique to reconstruct the
	free energy from its derivatives, a calculation that presents some
	difficulties in the vector case because of the statistical errors
	affecting the derivatives.},
  doi = {10.1063/1.2829861},
  institution = {Mechanical Engineering Department, Stanford University, Stanford,
	California 94305-4040, USA. darve@stanford.edu},
  keywords = {Algorithms; Computer Simulation; Energy Transfer; Models, Chemical;
	Models, Molecular; Stress, Mechanical; Thermodynamics},
  language = {eng},
  medline-pst = {ppublish},
  owner = {emilio},
  pmid = {18412436},
  timestamp = {2011.07.15},
  url = {http://dx.doi.org/10.1063/1.2829861}
}

@ARTICLE{Das2008,
  author = {Kalyan Das and Joseph D Bauman and Arthur D Clark and Yulia V Frenkel
	and Paul J Lewi and Aaron J Shatkin and Stephen H Hughes and Eddy
	Arnold},
  title = {High-resolution structures of HIV-1 reverse transcriptase/TMC278
	complexes: strategic flexibility explains potency against resistance
	mutations.},
  journal = {Proc Natl Acad Sci U S A},
  year = {2008},
  volume = {105},
  pages = {1466--1471},
  number = {5},
  month = {Feb},
  abstract = {TMC278 is a diarylpyrimidine (DAPY) nonnucleoside reverse transcriptase
	inhibitor (NNRTI) that is highly effective in treating wild-type
	and drug-resistant HIV-1 infections in clinical trials at relatively
	low doses ( approximately 25-75 mg/day). We have determined the structure
	of wild-type HIV-1 RT complexed with TMC278 at 1.8 A resolution,
	using an RT crystal form engineered by systematic RT mutagenesis.
	This high-resolution structure reveals that the cyanovinyl group
	of TMC278 is positioned in a hydrophobic tunnel connecting the NNRTI-binding
	pocket to the nucleic acid-binding cleft. The crystal structures
	of TMC278 in complexes with the double mutant K103N/Y181C (2.1 A)
	and L100I/K103N HIV-1 RTs (2.9 A) demonstrated that TMC278 adapts
	to bind mutant RTs. In the K103N/Y181C RT/TMC278 structure, loss
	of the aromatic ring interaction caused by the Y181C mutation is
	counterbalanced by interactions between the cyanovinyl group of TMC278
	and the aromatic side chain of Y183, which is facilitated by an approximately
	1.5 A shift of the conserved Y(183)MDD motif. In the L100I/K103N
	RT/TMC278 structure, the binding mode of TMC278 is significantly
	altered so that the drug conforms to changes in the binding pocket
	primarily caused by the L100I mutation. The flexible binding pocket
	acts as a molecular "shrink wrap" that makes a shape complementary
	to the optimized TMC278 in wild-type and drug-resistant forms of
	HIV-1 RT. The crystal structures provide a better understanding of
	how the flexibility of an inhibitor can compensate for drug-resistance
	mutations.},
  doi = {10.1073/pnas.0711209105},
  institution = {Center for Advanced Biotechnology and Medicine and Department of
	Chemistry and Chemical Biology, Rutgers, The State University of
	New Jersey, Piscataway, NJ 08854, USA.},
  keywords = {Amino Acid Motifs; Amino Acid Sequence; Anti-HIV Agents; Crystallography,
	X-Ray; Drug Design; Drug Resistance, Viral; Enzyme Inhibitors; HIV
	Reverse Transcriptase; Humans; Molecular Sequence Data; Mutation;
	Nitriles; Protein Conformation; Protein Engineering; Pyrimidines;
	Reverse Transcriptase Inhibitors},
  owner = {emilio},
  pii = {0711209105},
  pmid = {18230722},
  timestamp = {2010.10.27},
  url = {http://dx.doi.org/10.1073/pnas.0711209105}
}

@ARTICLE{Das2004,
  author = {Kalyan Das and Arthur D Clark and Paul J Lewi and Jan Heeres and
	Marc R De Jonge and Lucien M H Koymans and H. Maarten Vinkers and
	Frederik Daeyaert and Donald W Ludovici and Michael J Kukla and Bart
	De Corte and Robert W Kavash and Chih Y Ho and Hong Ye and Mark A
	Lichtenstein and Koen Andries and Rudi Pauwels and Marie-Pierre De
	Béthune and Paul L Boyer and Patrick Clark and Stephen H Hughes and
	Paul A J Janssen and Eddy Arnold},
  title = {Roles of conformational and positional adaptability in structure-based
	design of TMC125-R165335 (etravirine) and related non-nucleoside
	reverse transcriptase inhibitors that are highly potent and effective
	against wild-type and drug-resistant HIV-1 variants.},
  journal = {J Med Chem},
  year = {2004},
  volume = {47},
  pages = {2550--2560},
  number = {10},
  month = {May},
  abstract = {Anti-AIDS drug candidate and non-nucleoside reverse transcriptase
	inhibitor (NNRTI) TMC125-R165335 (etravirine) caused an initial drop
	in viral load similar to that observed with a five-drug combination
	in naïve patients and retains potency in patients infected with NNRTI-resistant
	HIV-1 variants. TMC125-R165335 and related anti-AIDS drug candidates
	can bind the enzyme RT in multiple conformations and thereby escape
	the effects of drug-resistance mutations. Structural studies showed
	that this inhibitor and other diarylpyrimidine (DAPY) analogues can
	adapt to changes in the NNRTI-binding pocket in several ways: (1).
	DAPY analogues can bind in at least two conformationally distinct
	modes; (2). within a given binding mode, torsional flexibility ("wiggling")
	of DAPY analogues permits access to numerous conformational variants;
	and (3). the compact design of the DAPY analogues permits significant
	repositioning and reorientation (translation and rotation) within
	the pocket ("jiggling"). Such adaptations appear to be critical for
	potency against wild-type and a wide range of drug-resistant mutant
	HIV-1 RTs. Exploitation of favorable components of inhibitor conformational
	flexibility (such as torsional flexibility about strategically located
	chemical bonds) can be a powerful drug design concept, especially
	for designing drugs that will be effective against rapidly mutating
	targets.},
  doi = {10.1021/jm030558s},
  institution = {Center for Advanced Biotechnology and Medicine and Department of
	Chemistry and Chemical Biology, Rutgers University, Piscataway, New
	Jersey 08854, USA.},
  keywords = {Anti-HIV Agents, chemistry; Crystallography, X-Ray; Drug Resistance,
	Viral; HIV Reverse Transcriptase, chemistry/genetics; Models, Molecular;
	Mutation; Protein Conformation; Pyridazines, chemistry; Pyrimidines,
	chemistry; Reverse Transcriptase Inhibitors, chemistry},
  language = {eng},
  medline-pst = {ppublish},
  owner = {emilio},
  pmid = {15115397},
  timestamp = {2012.02.22},
  url = {http://dx.doi.org/10.1021/jm030558s}
}

@ARTICLE{Das:Arnold:1996,
  author = {Das, K. and Ding, J. and Hsiou, Y. and Clark Jr., {A. D.} and Moereels,
	H. and Koymans, L. and Andries, K. and Pauwels, R. and Janssen, {P.
	A.} and Boyer, {P. L.} and Clark, P. and Smith Jr., {R. H.} and Kroeger
	Smith, {M. B.} and Michejda, {C. J.} and Hughes, {S. H.} and Arnold,
	E.},
  title = {Crystal structures of 8-Cl and 9-Cl TIBO complexed with wild-type
	HIV-1 RT and 8-Cl TIBO complexed with the Tyr181Cys HIV-1 RT drug-resistant
	mutant},
  journal = {J. Mol. Biol.},
  year = {1996},
  volume = {264},
  pages = {1085--1100},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Das2005,
  author = {Kalyan Das and Paul J Lewi and Stephen H Hughes and Eddy Arnold},
  title = {Crystallography and the design of anti-AIDS drugs: conformational
	flexibility and positional adaptability are important in the design
	of non-nucleoside HIV-1 reverse transcriptase inhibitors.},
  journal = {Prog Biophys Mol Biol},
  year = {2005},
  volume = {88},
  pages = {209--231},
  number = {2},
  month = {Jun},
  abstract = {Drug resistance is a key cause of failure for treatment of HIV infection.
	The efficacy of non-nucleoside reverse transcriptase inhibiting (NNRTI)
	drugs is impaired by rapid emergence of drug-resistance mutations.
	A multidisciplinary effort led to the discovery of the potent NNRTIs
	dapivirine and etravirine, both of which are diarylpyrimidine (DAPY)
	derivatives. Systematic structural and molecular modeling studies
	of HIV-1 reverse transcriptase (RT)/NNRTI complexes revealed different
	modes of inhibitor binding, and some of the DAPY inhibitors can bind
	to RT in different conformations. The torsional flexibility ("wiggling")
	of the inhibitors can generate numerous conformational variants and
	the compactness of the inhibitors permits significant repositioning
	and reorientation (translation and rotation) within the pocket ("jiggling").
	Such adaptations appear to be critical for the ability of the diarylpyrimidine
	NNRTIs to retain their potency against a wide range of drug-resistant
	HIV-1 RTs. Exploitation of inhibitor conformational flexibility (such
	as torsional flexibility about strategically located chemical bonds)
	can be a powerful element of drug design, especially for the design
	of drugs that will be effective against rapidly mutating targets
	(which is a collection of related targets).},
  doi = {10.1016/j.pbiomolbio.2004.07.001},
  institution = {Department of Chemistry and Chemical Biology, Center for Advanced
	Biotechnology and Medicine, Rutgers University, 679 Hoes Lane West,
	Piscataway, NJ 08854, USA.},
  keywords = {Acquired Immunodeficiency Syndrome, drug therapy/virology; Adaptation,
	Physiological; Animals; Anti-HIV Agents, administration /&/ dosage/chemistry;
	Crystallography, methods; Drug Delivery Systems, methods; Drug Design;
	Drug Resistance, Multiple, Viral, genetics; Gene Expression Regulation,
	Viral, physiology; Genetic Variation; HIV Reverse Transcriptase,
	chemistry/genetics/metabolism; HIV-1, drug effects/enzymology/genetics;
	Humans; Protein Conformation; Reverse Transcriptase Inhibitors, administration
	/&/ dosage/chemistry; Structure-Activity Relationship},
  language = {eng},
  medline-pst = {ppublish},
  owner = {emilio},
  pii = {S0079-6107(04)00074-4},
  pmid = {15572156},
  timestamp = {2012.02.22},
  url = {http://dx.doi.org/10.1016/j.pbiomolbio.2004.07.001}
}

@ARTICLE{Das:Lewi:Hughes:Arnold:2004,
  author = {Das, K. and Lewi, {P. J.} and Hughes,{S. H.} and Arnold, E.},
  title = { Crystallography and the design of anti-{AIDS} drugs: conformational
	flexibility and positional adaptability are important in the design
	of non-nucleoside {HIV-1} reverse transcriptase inhibitors},
  journal = {Progress in Biophysics and Molecular Biology},
  year = {2005},
  volume = {88},
  pages = {209--231},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Day2010,
  author = {Ryan Day and Dietmar Paschek and Angel E Garcia},
  title = {Microsecond simulations of the folding/unfolding thermodynamics of
	the Trp-cage miniprotein.},
  journal = {Proteins},
  year = {2010},
  volume = {78},
  pages = {1889--1899},
  number = {8},
  month = {Jun},
  abstract = {We study the unbiased folding/unfolding thermodynamics of the Trp-cage
	miniprotein using detailed molecular dynamics simulations of an all-atom
	model of the protein in explicit solvent using the Amberff99SB force
	field. Replica-exchange molecular dynamics simulations are used to
	sample the protein ensembles over a broad range of temperatures covering
	the folded and unfolded states at two densities. The obtained ensembles
	are shown to reach equilibrium in the 1 mus/replica timescale. The
	total simulation time used in the calculations exceeds 100 mus. Ensemble
	averages of the fraction folded, pressure, and energy differences
	between the folded and unfolded states as a function of temperature
	are used to model the free energy of the folding transition, DeltaG(P,
	T), over the whole region of temperatures and pressures sampled in
	the simulations. The DeltaG(P, T) diagram describes an ellipse over
	the range of temperatures and pressures sampled, predicting that
	the system can undergo pressure-induced unfolding and cold denaturation
	at low temperatures and high pressures, and unfolding at low pressures
	and high temperatures. The calculated free energy function exhibits
	remarkably good agreement with the experimental folding transition
	temperature (T(f) = 321 K), free energy, and specific heat changes.
	However, changes in enthalpy and entropy are significantly different
	than the experimental values. We speculate that these differences
	may be due to the simplicity of the semiempirical force field used
	in the simulations and that more elaborate force fields may be required
	to describe appropriately the thermodynamics of proteins.},
  doi = {10.1002/prot.22702},
  institution = {Department of Physics, Applied Physics and Astronomy and Center for
	Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic
	Institute, Troy, New York 12180, USA.},
  keywords = {Amino Acid Sequence; Computer Simulation; Kinetics; Models, Molecular;
	Molecular Sequence Data; Peptides; Protein Folding; Protein Stability;
	Thermodynamics; Time Factors},
  owner = {emilio},
  pmid = {20408169},
  timestamp = {2010.10.27},
  url = {http://dx.doi.org/10.1002/prot.22702}
}

@ARTICLE{DeClercq:1998,
  author = {De Clercq, E.},
  title = {The role of non-nucleoside reverse transcriptase inhibitors ({NNRTI's}
	in the therapy of {HIV-1} infection},
  journal = {Antiviral Research},
  year = {1998},
  volume = {38},
  pages = {153--179},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{DelBuono:96,
  author = {Del Buono, G. and Figueirido, F. and Levy, R. M.},
  journal = {Chem. Phys. Lett.},
  year = {1996},
  volume = {263},
  pages = {521-529},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{DelBuono:94,
  author = {Del Buono, G. and Figueirido, F. and Levy, R. M.},
  journal = {Proteins: Structure, Function and Genetics},
  year = {1994},
  volume = {20},
  pages = {85-97},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{DeLorbe2009,
  author = {John E DeLorbe and John H Clements and Martin G Teresk and Aaron
	P Benfield and Hilary R Plake and Laura E Millspaugh and Stephen
	F Martin},
  title = {Thermodynamic and structural effects of conformational constraints
	in protein-ligand interactions. Entropic paradoxy associated with
	ligand preorganization.},
  journal = {J. Am. Chem. Soc.},
  year = {2009},
  volume = {131},
  pages = {16758--16770},
  number = {46},
  month = {Nov},
  abstract = {Succinate- and cyclopropane-derived phosphotyrosine (pY) replacements
	were incorporated into a series of Grb2 SH2 binding ligands wherein
	the pY+1 residue was varied to determine explicitly how variations
	in ligand preorganization affect binding energetics and structure.
	The complexes of these ligands with the Grb2 SH2 domain were examined
	in a series of thermodynamic and structural investigations using
	isothermal titration calorimetry and X-ray crystallography. The binding
	enthalpies for all ligands were favorable, and although binding entropies
	for all ligands having a hydrophobic residue at the pY+1 site were
	favorable, binding entropies for those having a hydrophilic residue
	at this site were unfavorable. Preorganized ligands generally bound
	with more favorable Gibbs energies than their flexible controls,
	but this increased affinity was the consequence of relatively more
	favorable binding enthalpies. Unexpectedly, binding entropies of
	the constrained ligands were uniformly disfavored relative to their
	flexible controls, demonstrating that the widely held belief that
	ligand preorganization should result in an entropic advantage is
	not necessarily true. Crystallographic studies of complexes of several
	flexible and constrained ligands having the same amino acid at the
	pY+1 position revealed extensive similarities, but there were some
	notable differences. There are a greater number of direct polar contacts
	in complexes of the constrained ligands that correlate qualitatively
	with their more favorable binding enthalpies and Gibbs energies.
	There are more single water-mediated contacts between the domain
	and the flexible ligand of each pair; although fixing water molecules
	at a protein-ligand interface is commonly viewed as entropically
	unfavorable, entropies for forming these complexes are favored relative
	to those of their constrained counterparts. Crystallographic b-factors
	in the complexes of constrained ligands are greater than those of
	their flexible counterparts, an observation that seems inconsistent
	with our finding that entropies for forming complexes of flexible
	ligands are relatively more favorable. This systematic study highlights
	the profound challenges and complexities associated with predicting
	how structural changes in a ligand will affect enthalpies, entropies,
	and structure in protein-ligand interactions.},
  doi = {10.1021/ja904698q},
  institution = {Department of Chemistry and Biochemistry, The Institute of Cellular
	and Molecular Biology, University of Texas, Austin, Texas 78712,
	USA.},
  keywords = {Asparagine; Crystallography, X-Ray; Entropy; GRB2 Adaptor Protein;
	Hot Temperature; Ligands; Protein Conformation; Protons; Tyrosine;
	src Homology Domains},
  owner = {emilio},
  pmid = {19886660},
  timestamp = {2010.05.05},
  url = {http://dx.doi.org/10.1021/ja904698q}
}

@ARTICLE{Demchuk:Wade:96,
  author = {Demchuk, E. and Wade, R.},
  journal = {J. Phys. Chem.},
  year = {1996},
  volume = {100},
  pages = {17373-17387},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Deng2011,
  author = {Deng, N. and Zheng, W. and Gallicchio, E. and Levy, R.M.},
  title = {Insights into the Dynamics of HIV-1 Protease: a Kinetic Network Model
	Constructed from Atomistic Simulations},
  journal = {J. Am. Chem. Soc.},
  year = {2011},
  volume = {133},
  pages = {9387-9894},
  doi = {10.1021/ja2008032},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Deng2011a,
  author = {Deng, Nan-jie and Zheng, Weihua and Gallicchio, Emillio and Levy,
	Ronald M.},
  title = {Insights into the Dynamics of HIV-1 Protease: A Kinetic Network Model
	Constructed from Atomistic Simulations},
  journal = {Journal of the American Chemical Society},
  year = {2011},
  volume = {133},
  pages = {9387--9394},
  number = {24},
  month = jun,
  abstract = {The conformational dynamics in the flaps of HIV-1 protease plays a
	crucial role in the mechanism of substrate binding. We develop a
	kinetic network model, constructed from detailed atomistic simulations,
	to determine the kinetic mechanisms of the conformational transitions
	in HIV-1 PR. To overcome the time scale limitation of conventional
	molecular dynamics (MD) simulations, our method combines replica
	exchange MD with transition path theory (TPT) to study the diversity
	and temperature dependence of the pathways connecting functionally
	important states of the protease. At low temperatures the large-scale
	flap opening is dominated by a small number of paths; at elevated
	temperatures the transition occurs through many structurally heterogeneous
	routes. The expanded conformation in the crystal structure 1TW7 is
	found to closely mimic a key intermediate in the flap-opening pathways
	at low temperature. We investigated the different transition mechanisms
	between the semi-open and closed forms. The calculated relaxation
	times reveal fast semi-open ↔ closed transitions, and infrequently
	the flaps fully open. The ligand binding rate predicted from this
	kinetic model increases by 38-fold from 285 to 309 K, which is in
	general agreement with experiments. To our knowledge, this is the
	first application of a network model constructed from atomistic simulations
	together with TPT to analyze conformational changes between different
	functional states of a natively folded protein.},
  comment = {doi: 10.1021/ja2008032},
  issn = {0002-7863},
  owner = {emilio},
  publisher = {American Chemical Society},
  timestamp = {2011.07.15},
  url = {http://pubs.acs.org/doi/abs/10.1021/ja2008032}
}

@ARTICLE{Deng2009,
  author = {Yuqing Deng and Beno\^{i}t Roux},
  title = {Computations of standard binding free energies with molecular dynamics
	simulations.},
  journal = {J. Phys. Chem. B},
  year = {2009},
  volume = {113},
  pages = {2234--2246},
  number = {8},
  month = {Feb},
  abstract = {An increasing number of studies have reported computations of the
	standard (absolute) binding free energy of small ligands to proteins
	using molecular dynamics (MD) simulations and explicit solvent molecules
	that are in good agreement with experiments. This encouraging progress
	suggests that physics-based approaches hold the promise of making
	important contributions to the process of drug discovery and optimization
	in the near future. Two types of approaches are principally used
	to compute binding free energies with MD simulations. The most widely
	known is the alchemical double decoupling method, in which the interaction
	of the ligand with its surroundings are progressively switched off.
	It is also possible to use a potential of mean force (PMF) method,
	in which the ligand is physically separated from the protein receptor.
	For both of these computational approaches, restraining potentials
	may be activated and released during the simulation for sampling
	efficiently the changes in translational, rotational, and conformational
	freedom of the ligand and protein upon binding. Because such restraining
	potentials add bias to the simulations, it is important that their
	effects be rigorously removed to yield a binding free energy that
	is properly unbiased with respect to the standard state. A review
	of recent results is presented, and differences in computational
	methods are discussed. Examples of computations with T4-lysozyme
	mutants, FKBP12, SH2 domain, and cytochrome P450 are discussed and
	compared. Remaining difficulties and challenges are highlighted.},
  doi = {10.1021/jp807701h},
  institution = {Biosciences Division, Argonne National Laboratory, 9700 South Cass
	Avenue, Argonne, Illinois, USA.},
  keywords = {Computational Biology; Computer Simulation; Kinetics; Protein Binding;
	Protein Conformation; Proteins; Structure-Activity Relationship;
	Thermodynamics},
  owner = {emilio},
  pii = {10.1021/jp807701h},
  pmid = {19146384},
  timestamp = {2010.04.27},
  url = {http://dx.doi.org/10.1021/jp807701h}
}

@ARTICLE{Deng2008a,
  author = {Yuqing Deng and Beno\^{î}t Roux},
  title = {Computation of binding free energy with molecular dynamics and grand
	canonical Monte Carlo simulations.},
  journal = {J Chem Phys},
  year = {2008},
  volume = {128},
  pages = {115103},
  number = {11},
  month = {Mar},
  abstract = {The binding of a ligand to a receptor is often associated with the
	displacement of a number of bound water molecules. When the binding
	site is exposed to the bulk region, this process may be sampled adequately
	by standard unbiased molecular dynamics trajectories. However, when
	the binding site is deeply buried and the exchange of water molecules
	with the bulk region may be difficult to sample, the convergence
	and accuracy in free energy perturbation (FEP) calculations can be
	severely compromised. These problems are further compounded when
	a reduced system including only the region surrounding the binding
	site is simulated. To address these issues, we couple molecular dynamics
	(MD) with grand canonical Monte Carlo (GCMC) simulations to allow
	the number of water to fluctuate during an alchemical FEP calculation.
	The atoms in a spherical inner region around the binding pocket are
	treated explicitly while the influence of the outer region is approximated
	using the generalized solvent boundary potential (GSBP). At each
	step during thermodynamic integration, the number of water in the
	inner region is equilibrated with GCMC and energy data generated
	with MD is collected. Free energy calculations on camphor binding
	to a deeply buried pocket in cytochrome P450cam, which causes about
	seven water molecules to be expelled, are used to test the method.
	It concluded that solvation free energy calculations with the GCMC/MD
	method can greatly improve the accuracy of the computed binding free
	energy compared to simulations with fixed number of water.},
  doi = {10.1063/1.2842080},
  institution = {Biosciences Division, Argonne National Laboratory, Argonne, IL 60439,
	USA.},
  keywords = {Binding Sites; Camphor; Camphor 5-Monooxygenase; Computer Simulation;
	Models, Chemical; Models, Molecular; Molecular Conformation; Monte
	Carlo Method; Thermodynamics; Water},
  owner = {emilio},
  pmid = {18361618},
  timestamp = {2010.04.27},
  url = {http://dx.doi.org/10.1063/1.2842080}
}

@ARTICLE{Deng2006,
  author = {Deng, Yuqing and Roux, Beno\^{i}t},
  title = {Calculation of Standard Binding Free Energies: Aromatic Molecules
	in the T4 Lysozyme L99A Mutant},
  journal = {J. Chem. Theory Comput.},
  year = {2006},
  volume = {2},
  pages = {1255--1273},
  number = {5},
  month = sep,
  abstract = {Calculations of the binding free energy of various nonpolar aromatic
	ligands with the L99A mutant of T4 lysozyme using molecular dynamics
	(MD) simulation are presented. To ensure better convergence, biasing
	potentials are used to restrain the ligand orientation and center-of-mass
	movement relative to the binding site when the ligand is decoupled
	from its environment in the binding pocket. The bias introduced by
	the restraint potentials is removed once the ligand fully interacts
	with the rest of the system and the calculated binding free energy
	is independent of the applied restraints. To decrease the computational
	cost, the simulations are generated with a reduced system in which
	protein and water atoms within a 15 Å-radius sphere around the ligand
	are included explicitly, while the rest of the system is treated
	with the generalized solvent boundary potential (GSBP). For all the
	ligands, the precision of the calculated free energy is less than
	0.5 kcal/mol. For small nonpolar ligands such as benzene, toluene,
	and ethylbenzene, the calculated binding free energies are within
	1.1 kcal/mol of the experimental values. For larger ligands, the
	computed binding free energies are slightly more favorable than the
	experimental values. The nonbinding polar molecule, phenol, has a
	calculated binding free energy of −0.88 kcal/mol. The simulation
	protocol presented here provides a way to calculate the binding free
	energy of small molecules to receptors at moderate computational
	cost.},
  comment = {doi: 10.1021/ct060037v},
  issn = {1549-9618},
  owner = {emilio},
  publisher = {American Chemical Society},
  timestamp = {2010.04.27},
  url = {http://dx.doi.org/10.1021/ct060037v}
}

@ARTICLE{Deng:Roux:2004,
  author = {Deng, Yuqing and Roux, Beno\^{i}t},
  title = {Hydration of Amino Acid Side Chains; Nonpolar and Electrostatic Contributions
	Calculated from Staged Molecular Dynamics Free Energy Simulations
	with Explicit Water Molecules},
  journal = {The Journal of Physical Chemistry B},
  year = {2004},
  volume = {108},
  pages = {16567-16576},
  number = {42},
  doi = {10.1021/jp048502c},
  eprint = {http://pubs.acs.org/doi/pdf/10.1021/jp048502c},
  owner = {emilio},
  timestamp = {2011.01.18},
  url = {http://pubs.acs.org/doi/abs/10.1021/jp048502c}
}

@ARTICLE{Deprez2002,
  author = {Eric Deprez and Edward Gill and Volkhard Helms and Rebecca C Wade
	and Gaston Hui Bon Hoa},
  title = {Specific and non-specific effects of potassium cations on substrate-protein
	interactions in cytochromes P450cam and P450lin.},
  journal = {J Inorg Biochem},
  year = {2002},
  volume = {91},
  pages = {597--606},
  number = {4},
  month = {Sep},
  abstract = {Substrate binding to cytochrome P450cam is generally considered to
	be a two-step process. The first step corresponds to the entrance
	of the substrate, camphor, into the heme pocket. The second step
	corresponds to a spin transition (low spin-->high spin) of the iron
	in the protein-substrate complex. This spin transition is related
	to the mobility of the substrate inside the active site [Biochim
	Biophys Acta 1338 (1997) 77]. Potassium cations (K(+)) have a specific
	effect on the spin equilibrium. This is generally attributed to the
	K(+) ion-induced conformational change of tyrosine 96, the hydroxyl
	group of which is hydrogen bonded to the keto group of camphor and
	results in optimum substrate orientation and reduced mobility of
	this substrate in the active site. In the present paper, we show
	that K(+) not only affects the substrate-Tyr 96 couple, but acts
	more globally since K(+) effects are also observed in the Tyr96Phe
	mutant as well as in complexes with camphor-analogues. Large compounds,
	that fit well in the heme pocket and bind with higher affinity than
	camphor, display high spin contents that are less dependent on the
	presence of K(+). In contrast, K(+) has a significant effect on the
	high spin content of substrate-cytochrome P450cam complexes with
	looser interactions. We conclude that large compounds with higher
	affinities than camphor have more van der Waals contacts with the
	active site residues. Their mobilities are then reduced and less
	dependent on the presence of K(+). In this study, we also explored,
	for comparison, the K(+) effect on the spin transition state of another
	member of the P450 superfamily, cytochrome P450lin. This effect is
	not as strong as those observed for cytochrome P450cam. Even though
	the spin equilibrium does not change dramatically in the presence
	of K(+) or Na(+), the value of the dissociation constant (K(d)) for
	linalool binding is significantly affected by ionic strength. Analysis
	of the thermodynamic parameters for the linalool binding strongly
	suggests that, similarly to our previous finding for cytochrome P450cam,
	electrostatic gates participate in the control of substrate access.},
  institution = {Laboratoire de Biotechnologies et Pharmacologie Génétique Appliquée
	(UMR-CNRS 8532), Ecole Normale Supérieure de Cachan, Cachan, France.},
  keywords = {Amino Acid Sequence; Amino Acid Substitution; Binding Sites; Calorimetry;
	Camphor; Camphor 5-Monooxygenase; Cytochrome P-450 Enzyme System;
	Kinetics; Mixed Function Oxygenases; Models, Molecular; Potassium;
	Protein Binding; Protein Conformation; Pseudomonas putida; Recombinant
	Proteins; Substrate Specificity},
  owner = {emilio},
  pii = {S0162013402004671},
  pmid = {12237225},
  timestamp = {2010.09.07}
}

@ARTICLE{Dill:97,
  author = {Dill, K. A.},
  title = {Additivity Principles in Biochemistry},
  journal = {J. Biol. Chem.},
  year = {1997},
  volume = {272},
  pages = {701-704},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Dill:90,
  author = {Dill, K. A.},
  title = {Dominant Forces in Protein Folding},
  journal = {Biochemistry},
  year = {1990},
  volume = {29},
  pages = {7133-7155},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Dill:85,
  author = {Dill, K. A.},
  title = {Theory for the Folding and Stability of Globular Proteins},
  journal = {Biochemistry},
  year = {1985},
  volume = {24},
  pages = {1501-1509},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Ding:92,
  author = {Ding, H. Q. and Karasawa, N. and Goddard, W. A.},
  journal = {J. Chem. Phys.},
  year = {1992},
  volume = {97},
  pages = {4309-4318},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@PHDTHESIS{Ding:96,
  author = {Ding, Y.},
  title = {Computational Studies of Medium Effects},
  school = {Rutgers, The State University of New Jersey},
  year = {1996},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Ding:K-J:Levy:95,
  author = {Ding, Y. and Bernardo, D. N. and Krogh-Jespersen, K. and Levy, R.
	M.},
  journal = {J. Phys. Chem.},
  year = {1995},
  volume = {99},
  pages = {11575},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Dinner:Lazaridis:Karplus:99,
  author = {Dinner, A. R. and Lazaridis, T. and Karplus, M.},
  title = {Understanding $\beta$-hairpin formation},
  journal = {Proc. Natl. Acad. Sci. USA},
  year = {1999},
  volume = {96},
  pages = {9068-9073},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Dominy:Brooks:99,
  author = {Dominy, B. N. and Brooks, C. L. III},
  title = {Development of a Generalized Born Model Parameterization for Proteins
	and Nucleic Acids},
  journal = {J. Phys. Chem. B},
  year = {1999},
  volume = {103},
  pages = {3765-3773},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Dong:Wagoner:Baker:2008,
  author = {Dong, F. and Wagoner, {J. A.} and Baker, {N. A.}},
  title = {Assessing the performance of implicit solvation models at a nucleic
	acid surface},
  journal = {Phys. Chem. Chem. Phys},
  year = {2008},
  volume = {10},
  pages = {4889-4902},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Donnini2004,
  author = {Serena Donnini and André H Juffer},
  title = {Calculation of affinities of peptides for proteins.},
  journal = {J Comput Chem},
  year = {2004},
  volume = {25},
  pages = {393--411},
  number = {3},
  month = {Feb},
  abstract = {Several methodologies were employed to calculate the Gibbs standard
	free energy of binding for a collection of protein-ligand complexes,
	where the ligand is a peptide and the protein is representative for
	various protein families. Almost 40 protein-ligand complexes were
	employed for a continuum approach, which considers the protein and
	the peptide at the atomic level, but includes solvent as a polarizable
	continuum. Five protein-ligand complexes were employed for an all-atom
	approach that relies on a combination of the double decoupling method
	with thermodynamic integration and molecular dynamics. These affinities
	were also computed by means of the linear interaction energy method.
	Although it generally proved rather difficult to predict the absolute
	free energies correctly, for some protein families the experimental
	ranking order was correctly reproduced by the continuum and all-atom
	approach. Considerable attention has also been given to correctly
	analyze the affinities of charged peptides, where it is required
	to judge the effect of one or more ions that are being decoupled
	in an all-atom approach to preserve electroneutrality. The various
	methods are further judged upon their merits.},
  doi = {10.1002/jcc.10387},
  institution = {The Biocenter and the Department of Biochemistry, University of Oulu,
	P.O. Box 3000, FIN-90014 University of Oulu, Finland.},
  keywords = {Algorithms; Binding Sites; Ligands; Models, Molecular; Peptides; Protein
	Binding; Proteins; Thermodynamics},
  owner = {emilio},
  pmid = {14696074},
  timestamp = {2010.04.20},
  url = {http://dx.doi.org/10.1002/jcc.10387}
}

@ARTICLE{Dunitz:95,
  author = {Dunitz, J. D.},
  title = {Win some, lose some: enthalpy-entropy compensation in weak intermolecular
	interactions},
  journal = {Chem. \& Biol.},
  year = {1995},
  volume = {2},
  pages = {709-712},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Durell:Wallqvist:96,
  author = {Durell, S. R. and Wallqvist, A.},
  title = {Atomic-Scale Analysis of the Solvation Thermodynamics of Hydrophobic
	Hydration},
  journal = {Biophys. J.},
  year = {1996},
  volume = {71},
  pages = {1695},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Dzubiella2006,
  author = {J. Dzubiella and J. M J Swanson and J. A. McCammon},
  title = {Coupling hydrophobicity, dispersion, and electrostatics in continuum
	solvent models.},
  journal = {Phys Rev Lett},
  year = {2006},
  volume = {96},
  pages = {087802},
  number = {8},
  month = {Mar},
  abstract = {An implicit solvent model is presented that couples hydrophobic, dispersion,
	and electrostatic solvation energies by minimizing the system Gibbs
	free energy with respect to the solvent volume exclusion function.
	The solvent accessible surface is the output of the theory. The method
	is illustrated with the solvation of simple solutes on different
	length scales and captures the sensitivity of hydration to the particular
	form of the solute-solvent interactions in agreement with recent
	computer simulations.},
  institution = {NSF Center for Theoretical Biological Physics (CTBP), and Department
	of Chemistry and Biochemistry, University of California, San Diego,
	La Jolla, California 92093-0365, USA. jdzubiella@ucsd.edu},
  keywords = {Alkanes, chemistry; Computer Simulation; Hydrophobic and Hydrophilic
	Interactions; Models, Chemical; Solvents, chemistry; Static Electricity;
	Thermodynamics},
  language = {eng},
  medline-pst = {ppublish},
  owner = {emilio},
  pmid = {16606226},
  timestamp = {2011.02.03}
}

@ARTICLE{Dzubiella2006a,
  author = {J. Dzubiella and J. M J Swanson and J. A. McCammon},
  title = {Coupling nonpolar and polar solvation free energies in implicit solvent
	models.},
  journal = {J Chem Phys},
  year = {2006},
  volume = {124},
  pages = {084905},
  number = {8},
  month = {Feb},
  abstract = {Recent studies on the solvation of atomistic and nanoscale solutes
	indicate that a strong coupling exists between the hydrophobic, dispersion,
	and electrostatic contributions to the solvation free energy, a facet
	not considered in current implicit solvent models. We suggest a theoretical
	formalism which accounts for coupling by minimizing the Gibbs free
	energy of the solvent with respect to a solvent volume exclusion
	function. The resulting differential equation is similar to the Laplace-Young
	equation for the geometrical description of capillary interfaces
	but is extended to microscopic scales by explicitly considering curvature
	corrections as well as dispersion and electrostatic contributions.
	Unlike existing implicit solvent approaches, the solvent accessible
	surface is an output of our model. The presented formalism is illustrated
	on spherically or cylindrically symmetrical systems of neutral or
	charged solutes on different length scales. The results are in agreement
	with computer simulations and, most importantly, demonstrate that
	our method captures the strong sensitivity of solvent expulsion and
	dewetting to the particular form of the solvent-solute interactions.},
  doi = {10.1063/1.2171192},
  institution = {NSF Center for Theoretical Biological Physics (CTBP), University
	of California, San Diego, La Jolla, California 92093-0365, USA. jdzubiella@ucsd.edu},
  keywords = {Computer Simulation; Models, Chemical; Solvents, chemistry; Thermodynamics},
  language = {eng},
  medline-pst = {ppublish},
  owner = {emilio},
  pmid = {16512740},
  timestamp = {2011.02.03},
  url = {http://dx.doi.org/10.1063/1.2171192}
}

@ARTICLE{Eisenberg:McLachlan:86,
  author = {Eisenberg, D. and McLachlan, A. D.},
  title = {Solvation energy in protein folding and binding},
  journal = {Nature},
  year = {1986},
  volume = {319},
  pages = {199-203},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Elcock:Sept:McCammon:2001,
  author = {Elcock, {A. H.} and Sept, D. and McCammon, {J. A.} },
  title = {Computer Simulation of Protein-Protein Interactions},
  journal = {j. Phys. Chem. B},
  year = {2001},
  volume = {105},
  pages = {1504-1518},
  number = {8},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Eldridge1997,
  author = {M. D. Eldridge and C. W. Murray and T. R. Auton and G. V. Paolini
	and R. P. Mee},
  title = {Empirical scoring functions: I. The development of a fast empirical
	scoring function to estimate the binding affinity of ligands in receptor
	complexes.},
  journal = {J. Comput. Aided Mol. Des.},
  year = {1997},
  volume = {11},
  pages = {425--445},
  number = {5},
  month = {Sep},
  abstract = {This paper describes the development of a simple empirical scoring
	function designed to estimate the free energy of binding for a protein-ligand
	complex when the 3D structure of the complex is known or can be approximated.
	The function uses simple contact terms to estimate lipophilic and
	metal-ligand binding contributions, a simple explicit form for hydrogen
	bonds and a term which penalises flexibility. The coefficients of
	each term are obtained using a regression based on 82 ligand-receptor
	complexes for which the binding affinity is known. The function reproduces
	the binding affinity of the complexes with a cross-validated error
	of 8.68 kJ/mol. Tests on internal consistency indicate that the coefficients
	obtained are stable to changes in the composition of the training
	set. The function is also tested on two test sets containing a further
	20 and 10 complexes, respectively. The deficiencies of this type
	of function are discussed and it is compared to approaches by other
	workers.},
  institution = {Proteus Molecular Design Ltd., Macclesfield, Cheshire, U.K.},
  keywords = {Binding Sites; Drug Design; Endopeptidases; Ligands; Protein Binding;
	Proteins; Regression Analysis; Software; Thermodynamics},
  owner = {emilio},
  pmid = {9385547},
  timestamp = {2010.05.01}
}

@ARTICLE{Eriksson1992,
  author = {A. E. Eriksson and W. A. Baase and J. A. Wozniak and B. W. Matthews},
  title = {A cavity-containing mutant of T4 lysozyme is stabilized by buried
	benzene.},
  journal = {Nature},
  year = {1992},
  volume = {355},
  pages = {371--373},
  number = {6358},
  month = {Jan},
  abstract = {The hydrophobic cores of proteins are generally well packed, with
	few cavities. Mutations in which a bulky buried residue such as leucine
	or phenylalanine is replaced with a small residue such as alanine
	can create cavities in the core of a protein (our unpublished results).
	The sizes and shapes of such cavities can vary substantially depending
	on factors such as local geometry, whether or not a cavity already
	exists at the site of substitution, and the degree to which the protein
	structure relaxes to occupy the space vacated by the substituted
	residue. We show by crystallographic and thermodynamic analysis that
	the cavity created by the replacement Leu 99----Ala in T4 lysozyme
	is large enough to bind benzene and that ligand binding increases
	the melting temperature of the protein by 6.0 degrees C at pH 3.0.
	Benzene does not, however, bind to the cavity created by the Phe
	153----Ala replacement. The results show that cavities can be engineered
	in proteins and suggest that such cavities might be tailored to bind
	specific ligands. The binding of benzene at an internal site 7 A
	from the molecular surface also illustrates the dynamic nature of
	proteins, even in crystals.},
  doi = {10.1038/355371a0},
  institution = {Institute of Molecular Biology, Howard Hughes Medical Institute,
	University of Oregon, Eugene 97403.},
  keywords = {Amino Acid Sequence; Benzene; Binding Sites; Calorimetry; Enzyme Stability;
	Models, Chemical; Models, Molecular; Muramidase; Mutagenesis, Site-Directed;
	Protein Conformation; Recombinant Proteins; T-Phages},
  owner = {emilio},
  pmid = {1731252},
  timestamp = {2010.04.27},
  url = {http://dx.doi.org/10.1038/355371a0}
}

@ARTICLE{Essman:Perera:Pedersen:1995,
  author = {Essman, U. and Perera, L. and Berkowitz. {M. L.} and Darden, T. and
	Lee,H. and Pedersen, {L. G.}},
  title = {A smooth particle mesh Ewald method},
  journal = {J. Chem. Phys},
  year = {1995},
  volume = {103},
  pages = {8577-8593},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Evans2004,
  author = {David A Evans and David J Wales},
  title = {Folding of the GB1 hairpin peptide from discrete path sampling.},
  journal = {J Chem Phys},
  year = {2004},
  volume = {121},
  pages = {1080--1090},
  number = {2},
  month = {Jul},
  abstract = {The discrete path sampling technique is used to calculate folding
	pathways of the 16-amino acid beta hairpin-forming sequence from
	residues 41-56 of the B1 domain of protein G. The folding time is
	obtained using master equation dynamics and kinetic Monte Carlo simulations,
	and the time evolution of different order parameters and occupation
	probabilities of groups of minima are calculated and used to characterize
	intermediates on the folding pathway.},
  doi = {10.1063/1.1759317},
  institution = {University Chemical Laboratories, Lensfield Road, Cambridge CB2 1EW,
	United Kingdom.},
  keywords = {Binding Sites; Computer Simulation; Models, Chemical; Models, Molecular;
	Motion; Nerve Tissue Proteins; Peptides; Protein Binding; Protein
	Conformation; Protein Folding; Protein Structure, Tertiary},
  owner = {emilio},
  pmid = {15260643},
  timestamp = {2011.01.18},
  url = {http://dx.doi.org/10.1063/1.1759317}
}

@ARTICLE{Eyrich:Standley:Felts:Friesner:99,
  author = {Eyrich, V. A. and Standley, D. M. and Felts, A. K. and Friesner,
	R. A.},
  title = {Protein tertiary structure prediction using a branch and bound algorithm},
  journal = {Proteins},
  year = {1999},
  volume = {35},
  pages = {41-57},
  owner = {emilio},
  timestamp = {2011.01.18}
}

@ARTICLE{Fajer2

license: MIT

license_type: permissive

branch_name: refs/heads/master

gha_license_id: MIT

gha_language: TeX

extension: bib