Some Critical Aspects of Molecular Interactions Between Drugs and Receptors

María J. R. Yunta^1,

¹Departamento de Química Orgánica I, Facultad de Química, Universidad Complutense, Madrid, Spain

Cite this paper:
María J. R. Yunta. Some Critical Aspects of Molecular Interactions Between Drugs and Receptors. American Journal of Modeling and Optimization. 2014; 2(4):84-102. doi: 10.12691/ajmo-2-4-1

Abstract

Protonation states are sometimes crucial for free energy calculations to predict binding ability of molecules to receptors, a main subject for drug design. This mini-review seeks to identify the importance of knowing the influence of pH in such studies to better achieve correct predictions for drug candidates. Protonation states, for both proteins and drugs, need to be considered in docking studies although they have been usually neglected.

Keywords:
molecular modeling protonation state computer aided drug design

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References:

[1]	Pauling, L. The nature of the chemical bond. IV. The energy of single bonds and the relative electronegativity of atoms. J. Am. Chem. Soc., 1932, 54, 3570-3582.
[2]	Pearson, R.G. Chemical hardness, in: Sen, K. D. (Ed.), Structure and Bonding, vol. 80, Springer, Berlin, 1993.
[3]	Fukui, K.; Yonesawa, Y.; Shingu, H.A molecular orbital theory of reactivity in aromatic hydrocarbons.J. Chem. Phys., 1952, 20, 722-725.
[4]	Yang, W.; Parr, R.G. Hardness, softness, and the Fukui function in the electronic theory of metals and catalysis, Proc. Natl. Acad. Sci. USA, 1985, 82, 6723-6726.
[5]	Lengauer, T.; Rarey, M. Computational methods for biomolecular docking. Curr. Opin. Struct. Biol., 1996, 6, 402-406.
[6]	Kitchen, D. B.; Decornez, H.; Furr, J. R.; Bajorath, J. Docking and scoring in virtual screening for drug discovery: Methods and applications. Nat. Drug Discovery, 2004, 3, 935-949.
[7]	Pearlman, D. A.; Kollman, P. A. The calculated free energy effects of 5-methyl cytosine on the B to Z transition in DNA, Biopolymers, 1990, 29, 1193-1209.
[8]	Gohlke, H.; Klebe, G. Approaches to the description and prediction of the binding affinity of small-molecule ligands to macromolecular receptors, Angew. Chem. Int. Ed. Engl., 2002, 41, 2644-2676.
[9]	Abagyan, R.; Totrov, M.; Kuznetsov, D. ICM-A new method for protein modeling and design: Applications to docking and structure prediction from the distorted native conformation. J. Comput. Chem., 1994, 15, 488-506.
[10]	Jones, G.; Willett, P.; Glen, R. C. Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation. J. Mol. Biol., 1995, 245, 43-53.
[11]	Rarey, M.; Kramer, B.; Lengauer, T.; Klebe, G. A fast flexible docking method using an incremental construction algorithm. J. Mol. Biol., 1996, 261, 470-489.
[12]	Ewing, T. J. A.; Kuntz, I. D. Critical evaluation of search algorithms for automated molecular docking and database screening. J. Comput. Chem., 1997, 18, 1175-1189.
[13]	Morris, G. M.; Goodsell, D. S.; Halliday, R. S.; Huey, R.; Hart, W. E.; Belew, R. K.; Olson, A. J. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J. Comput. Chem., 1998, 19, 1639-1662.
[14]	Wu, G.; Robertson, D. H.; Brooks, C. L., III; Vieth, M. Detailed analysis of grid-based molecular docking: A case study of CDOCKERA CHARMm-based MD docking algorithm. J. Comput. Chem., 2003, 24, 1549-1562.
[15]	Bühm, H. J.; Stahl, M. The use of scoring functions in drug discovery applications. In Reviews in Computational Chemistry; Lipkowitz, K. B., Boyd, D. B., Eds.; Wiley-VCH: New York, 2002; Vol. 18, pp 41-87.
[16]	Shao, M.; Wang, S.; Wang, C.; Yuan, X.; Li, S. C.; Zheng, W.; Bu, D. Incorporating Ab Initio energy into threading approaches for protein structure prediction. BMC Bioinformatics. 2011, 12 (Suppl 1), 54-67.
[17]	de Jongel, M. R.; Vinkers, M.; van Lenthe, J. H.; Daeyaert, F.; Bush, I. J.; van Dam, H. J. J.; Sherwood, P.; Guest, M. F. Ab Initio potential grid based docking: From High Performance Computing to In Silico Screening. COMPLIFE, 2007, 940, 168-178.
[18]	V. Vasilyev, V.; Bliznyuk, A. Application of semiempirical quantum chemical methods as a scoring function in docking. Theor. Chem. Acc., 2004, 112, 313-317.
[19]	Bietz, S.; Urbaczek, S.; Schulz, B.; Rarey, M. Protoss: a holistic approach to predict tautomers and protonation states in protein-ligand complexes. J. Cheminf., 2014, 6, 1-12.
[20]	Linderstrøm-Lang. K. On the ionization of proteins. Cr. Trav. Lab. Carlsberg, 1924, 15, 1-29.
[21]	Stewart, R. The proton: appellation to organic chemistry. Academic Press, New York, 1985.
[22]	Carrol, F.A. Perspectives on structure and mechanism in organic chemistry. Brooks-Cole, New York, 1998.
[23]	Zhao, J.; Zhang, R. Proton transfer reaction rate constants between hydronium ion (H3O+) and volatile organic compounds. Atmos. Environ., 2004, 38, 2177-2185.
[24]	Kennedy, R. A.; Mayhew, Ch. A.; Thomas, R.; Watts, P. Reactions of H3O+ with a number of bromine containing fully and partially halogenated hydrocarbons. Int. J. Mass Spectrom., 2003, 223, 627-637.
[25]	Bouchoux, G. Gas-phase basicities of polyfunctional molecules. Part 1: Theory and methods. Mass Spectrom. Rev., 2007, 26, 775-835.
[26]	Deakyne, C.A. Proton affinities and gas-phase basicities: theoretical methods and structural effects.Int. J. Mass. Spectrom., 2003, 227, 601-616.
[27]	Lias, S. G.; Liebman, J. F.; Levine, R. D. Evaluated gas phase basicities and proton affinities of molecules; heats of formation of protonated molecules.J. Phys. Chem. Ref. Data, 1984, 13, 695-808.
[28]	Rajak, S. J.; Ghosha, D. C. Correlating the site selectivity of protonation in some ambidentate molecules in terms of the dual descriptor. Eur. Phys. J. D., 2012, 66: 66, 6 pp.
[29]	Ghosh, D. C. A theoretical study of some selected molecules and their protonation by the application of CNDO method (Premch and Roych and Research Studentship Award, University of Calcutta, 1976).
[30]	Halperin, I.; Ma, B.; Wolfson, H.; Nussinov, R. Principles of docking: an overview of search algorithms and a guide to scoring functions. Proteins: Struct. Funct. Bioinf., 2002, 47, 409-443.
[31]	Smith, G. R.; Sternberg, M. J. E. Prediction of protein-protein interactions by docking methods. Curr. Opin. Struct. Biol., 2002, 12, 28-35.
[32]	Ritchie, D. Recent progress and future directions in protein-protein docking. Curr. Prot. Pept. Sci., 2008, 9, 1-15.
[33]	Chen, R.; Li, L.; Weng, Z. ZDOCK: an initial-stage protein-docking algorithm. Proteins: Struct. Funct. Bioinf., 2003, 52, 80-87.
[34]	Macindoe, G.; Mavridis, L.; Venkatraman, V.; Devignes, M.; Ritchie, D. HexServer: an FFT-based protein docking server powered by graphics processors. Nucleic Acids Res., 2010, 38, W445-W449.
[35]	Kozakov, D.; Brenke, R.; Comeau, S.; Vajda, S. PIPER: an FFT-based protein docking program with pairwise potentials. Proteins: Struct. Funct. Bioinf., 2006, 65, 392-406.
[36]	Tovchigrechko, A.; Vakser, I. A. GRAMM-X public web server for protein-protein docking. Nucleic Acids Res., 2006, 34, W310-W314.
[37]	Mandell, J. G.; Roberts, V. A.; Pique, M. E.; Kotlovyi, V.; Mitchell, J. C.; Nelson, E.; Tsigelny, I.; ten Eyck, L. F. Protein docking using continuum electrostatics and geometric fit. Protein Eng., 2001, 14, 105-113.
[38]	Andrusier, N.; Mashiach, E.; Nussinov, R.; Wolfson, H.J. Principles of flexible protein-protein docking. Proteins: Struct. Funct. Bioinf., 2008, 73, 271-289.
[39]	Lyskov, S.; Gray, J. J. The Rosetta Dock server for local protein-protein docking. Nucleic Acids Res., 2008, 36, W233-W238.
[40]	Dominguez, C.; Boelens, R.; Bonvin, A. M. J. J. HADDOCK: a protein-protein docking approach based on biochemical or biophysical information. J. Am. Chem. Soc., 2003, 125, 1731-1737.
[41]	Ogmen, U.; Keskin, O.; Aytunas, S.; Nussinov, R.; Gursoy, A. PRISM: protein interactions by structural matching. Nucleic Acids Res., 2005, 134, W331-W336.
[42]	Grosdidier, A.; Zoete, V.; Michielin, O. Swiss Dock, a protein-small molecule docking web service based on EADock DSS. Nucleic Acids Res., 2011, 39, W270-W277.
[43]	Ritchie, D.; Kozakov, D.; Vajda, S. Accelerating and focusing protein-protein docking correlations using multi-dimensional rotational FFT generating functions. Bioinformatics, 2008, 24, 1865-1873.
[44]	ten Brink, T.; Exner, T. E. Influence of protonation, tautomeric, and stereoisomeric states on protein-ligand docking results. J. Chem. Inf. Model., 2009, 49, 1535-1546.
[45]	Sippl, M. J. Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures in globular proteins. J. Mol. Biol., 1990, 213, 859-883.
[46]	DeWitte, R.; Shakhnovich, E. SMoG: De novo design method based on simple, fast, and accurate free energy estimates. 1. Methodology and supporting evidence. J. Am. Chem. Soc., 1996, 118, 11733-11744.
[47]	Mitchell, J. B. O.; Laskowski, R. A.; Alexander, A.; Thornton, J. M. BLEEP-Potential of mean force describing protein-lig and interactions: I. Generating potential. J. Comput. Chem., 1999, 20, 1165-1176.
[48]	Muegge, I.; Martin, Y. C. A general and fast scoring function for protein-ligand interactions: A simplified potential approach. J. Med. Chem., 1999, 42, 791-804.
[49]	Gohlke, H.; Hendlich, M.; Klebe, G. Knowledge-based scoring function to predict protein-ligand interactions. J. Mol. Biol., 2000, 295, 337-356.
[50]	Stubbs, M. T.; Reyda, S.; Dullweber, F.; Möller, M.; Klebe, G.; Dorsch, D.; Mederski, W.; Wurziger, H. pH-dependent binding modes observed in trypsin crystals: Lessons for structure-based drug design. Chem Bio Chem, 2002, 3, 246-249.
[51]	Mardis, K. L.; Luo, R.; Gilson, M. K. Interpreting trends in the binding of cyclic ureas to HIV-1 protease. J. Mol. Biol., 2001, 309, 507-517.
[52]	Warshel, A.; Sharma, P. K.; Kato, M.; Parson, W. W. Modeling electrostatic effects in proteins. Biochim. Biophys. Acta, 2006, 1764, 1647-1676.
[53]	Brock, K.; Talley, K.; Coley, K.; Kundrotas, P.; Alexov, E. Optimization of electrostatic interactions in protein-protein complexes. Biophys. J., 2007, 83, 3340-3352.
[54]	Tjong, H.; Zhou, H-X. Accurate calculations of binding, folding, and transfer free energies by a scaled generalized born method. J. Chem. Theory Comput., 2008, 4, 1733-1744.
[55]	Bertonati, C.; Honig, B.; Alexov, E. Poisson-Boltzmann calculations of nonspecific salt effects on protein-protein binding free energies. Biophys. J., 2007, 92, 1891-1899.
[56]	Schmidt, M.; Lopes, A.; Amara, N.; Bathelt, C.; Simonson, T. Testing the coulomb/accessible surface area solvent model for protein stability, ligand binding, and protein design. BMC Bioinformatics, 2008, 9, 148.
[57]	Schreiber, G.; Haran, G.; Zhou, H-X. Fundamental aspects of protein-protein association kinetics. Chem. Rev., 2009, 109, 839-860.
[58]	Shaul, Y.; Schreiber, G. Exploring the charge space of protein-protein association: a proteomic study. Proteins: Struct. Funct. Bioinf., 2005, 60, 341-352.
[59]	Alsallaq, R.; Zhou, H-X. Electrostatic rate enhancement and transient complex of protein-protein association. Proteins: Struct. Funct. Bioinf., 2008, 71, 320-335.
[60]	Dong, F.; Zhou, H-X. Electrostatic contribution to the binding stability of protein-protein complexes. Proteins: Struct. Funct. Bioinf., 2006, 65, 87-102.
[61]	Czodrowski, P.; Sotriffer, C. A.; Klebe, G. Protonation changes upon ligand binding to trypsin and thrombin. Structural interpretation based on pKa calculations and ITC experiments. J. Mol. Biol., 2007, 367, 1347-1356.
[62]	Djurdjevic-Pahl, A.; Hewage, C.; Malthouse, J. P. G. Ionisations within a subtilisin-glyoxal inhibitor complex. Biochim. Biophys. Acta, 2005, 1749, 33-41.
[63]	Blundell, C. D.; Mahoney, D. J.; Cordell, M. R.; Almond, A.; Kahmann, J. D.; Perczel, A.; Taylor, J. D.; Campbell, I. D.; Day, A. J. Determining the molecular basis for the pH-dependent interaction between the link module of human TSG-6 and hyaluronan. J. Biol. Chem., 2007, 282, 12976-12988.
[64]	Lu, Y.; Yang, C-Y.; Wang, S. Binding free energy contributions of interfacial waters in HIV-1 protease/inhibitor complexes. J. Am. Chem. Soc., 2006, 128, 11830-11839.
[65]	Mason, A. C.; Jensen, J. H. Protein-protein binding is often associated with changes in protonation state. Proteins: Struct. Funct. Bioinf., 2008, 71, 81-91.
[66]	Archontis, G.; Simonson, T. Proton binding to proteins. A free-energy component analysis using a dielectric continuum model. Biophys. J., 2005, 88, 3888-3904.
[67]	Alexov, E. G. Calculating proton uptake/release and binding free energy taking into account ionization and conformation changes induced by protein-inhibitor association. Application to plasmepsin, cathepsin D and endothiapepsin-pepstatin complexes. Proteins: Struct. Funct. Bioinf., 2004, 56, 572-584.
[68]	Mitra, R.; Shyam, R.; Mitra, I.; Miteva, M.; Alexov, E. Calculating the protonation states of proteins and small molecules. Implications to ligand-receptor interactions. Curr. Comput.-Aided Drug Des., 2008, 4, 169-179.
[69]	Polgar, T.; Keseru, G. M. Virtual screening for β-secretase (BACE1) inhibitors reveals the importance of protonation states at Asp32 and Asp228. J. Med. Chem., 2005; 48, 3749-3755.
[70]	Polgar, T.; Magyar, C.; Simon, I.; Keseru, G. M. Impact of ligand protonation on virtual screening against β-secretase (BACE1). J. Chem. Inf. Mod., 2007, 47, 2366-2373.
[71]	Jensen, J. H. Calculating pH and salt dependence of protein-protein binding. Curr. Pharm. Biotechnol., 2008, 9, 96-102.
[72]	Kukić, P.; Nielsen, J. E. Electrostatics in proteins and protein-ligand complexes. Future Med. Chem., 2010, 2, 647-666.
[73]	Li, H.; Robertson, A. D.; Jensen, J. H. Very fast empirical prediction and rationalization of protein pKa values.Proteins: Struct. Funct. Bioinf., 2005, 61, 704-721.
[74]	Khandogin, J.; Brooks, C. L.Linking folding with aggregation in Alzheimer's β-amyloid peptides.Proc. Natl. Acad. Sci. USA, 2007, 104, 16880-16885.
[75]	Chen, X.; Deng, Y. F. Long-time molecular dynamics simulations of botulinum biotoxin type-A at different pH values and temperatures.J. Mol. Model., 2007, 13, 559-572.
[76]	Khandogin, J.; Raleigh, D. P.; Brooks, C. L. Folding intermediate in the villin headpiece domain arises from disruption of a N-terminal hydrogen-bonded network. J. Am. Chem. Soc., 2007, 129, 3056-3057.
[77]	Srivastava, J.; Barber, D. L.; Jacobson, M. P. Intracellular pH sensors: design principles and functional significance. Physiology, 2007, 22, 30-39.
[78]	Khandogin, J.; Brooks, C. L. Toward the accurate first-principles prediction of ionization equilibria in proteins. Biochemistry, 2006, 45, 9363-9373.
[79]	Dlugosz, M.; Antosiewicz, J. M. Effects of solute−solvent proton exchange on polypeptide chain dynamics:  A constant-pH molecular dynamics study.J. Phys. Chem. B., 2005, 109, 13777-13784.
[80]	Mongan, J.; Case, D.A. Biomolecular simulations at constant pH. Curr. Opin. Strucl. Biol., 2005, 15, 157-163.
[81]	Mitra, R. C.; Zhang, Z.; Alexov, E. In silico modeling of pH-optimum of protein-protein binding. Proteins: Struct. Funct. Bioinf., 2011, 79, 925-936.
[82]	Yang, A-S.; Honig, B. On the pH dependence of protein stability. J. Mol. Biol., 1993, 231, 459-474.
[83]	Whitten, S.; Garcia-Moreno, B. pH Dependence of stability of staphyloccocal nuclease: Evidence of substantial electrostatic interactions in the denaturated state. Biochemistry, 2000, 39, 14292-14304.
[84]	Tollinger, M.; Crowhurst, K.; Kay, L.; Forman-Kay, J. Site-specific contributions to the pH dependence of protein stability. Proc. Natl. Acad. Sci. USA, 2003, 100, 4545-4550.
[85]	Bauman, A. T.; Jaron, S.; Yukl, E.T.; Burchfiel, J. R.; Blackburn, N. J. pH Dependence of peptidylglycine monooxygenase. Mechanistic implications of Cu-methionine binding dynamics. Biochemistry, 2006, 45, 11140-11150.
[86]	Bidwai, A. K.; Ok, E. Y.; Erman, J. E. pH Dependence of cyanide binding to the ferric heme domain of the direct oxygen sensor from Escherichia coli and the effect of alkaline denaturation. Biochemistry, 2008, 47, 10458-10470.
[87]	Matthew, J. B.; Gurd, F. R. N.; Garcia-Moreno, B.; Flanagan, M. A.; March, K. L.; Shire, S. J. pH-Dependent processes in proteins. CRC Criti. Rev. Biochem., 1985; 18, 91-197.
[88]	Anderson, D. E.; Becktel, W. J.; Dahlquist, F. W. pH-Induced denaturation of proteins: A single salt bridges contributes 3-5 kcal/mol to the free energy of folding of T4-lysozyme. Biochem., 1990, 29, 2403-2408.
[89]	Pace, C. N.; Laurents, D. V.; Erickson, R. E. Urea denaturation of barnase: pH dependence and characterzation of the unfolded state. Biochemistry, 1992, 31, 2728-2734.
[90]	Khurana, R.; Hate, A.; Nath, U.; Udgaonkar, B. pH dependence of the stability of barstar to chemical and thermal denaturation. Prot. Sci., 1995, 4, 1133-1144.
[91]	Chan, P.; Lovric, J.; Warwicker, J. Subcellular pH and predicted pH-dependent features of proteins. Proteomics, 2006, 6, 3494-3501.
[92]	Chan, P.; Warwicker, J. Evidence for the adaptation of protein pH-dependence to subcellular pH. BMC Biol., 2009, 7, 69, 10 pp.
[93]	Gilson, M. K.; Honig, B. H. Calculation of electrostatic potentials in an enzyme active site. Nature, 1987, 330, 84-86.
[94]	Bashford, D.; Karplus, M. pKa’s of ionizable groups in proteins: atomic detail from a continuum electrostatic model. Biochemistry, 1990, 29, 10219-10225.
[95]	Gilson, M. K. Multiple-site titration and molecular modeling: two rapid methods for computing energies and forces for ionizable groups in proteins. Proteins: Struct. Funct. Bioinf., 1993, 15, 266-282.
[96]	Yang, A.; Gunner, M. R.; Sampogna, R.; Sharp, K.; Honig, B. On the calculation of pKa in proteins. Proteins: Struct. Funct. Bioinf., 1993, 15, 252-265.
[97]	Dixon, S. J.; Jurs, P. C. Estimation of pKa for organic oxyacids using calculated atomic charges. J. Comput. Chem. 1993, 14, 1460-1467.
[98]	Antosiewicz, J.; McCammon, J. A.; Gilson, M. K. Prediction of pH-dependent properties of proteins. J. Mol. Biol., 1994, 238, 415-436.
[99]	Honig, B.; Nicholls, A. Classical electrostatics in biology and chemistry. Science, 1995, 268, 1144-1149.
[100]	Antosiewicz, J.; Briggs, J. M.; Elcock, A. H.; Gilson, M. K.; McCammon, J. A. Computing ionization states of proteins with a detailed charged model. J. Comput. Chem., 1996, 17, 1633-1644.
[101]	Antosiewicz, J.; McCammon, J. A.; Gilson, M. K. The determinants of pKas in proteins. Biochemistry, 1996, 35, 7819-7833.
[102]	Sham, Y. Y.; Chu, Z. T.; Warshel, A. Consistent calculations of pKa’s of ionizable residues in proteins: Semi-microscopic and microscopic approaches. J. Phys. Chem. B, 1997, 101, 4458-4472.
[103]	Duarte, H. A.; Carvalho, S.; Paniago, E. B.; Simas, A. M. Importance of tautomers in the chemical behavior of tetracyclines. J. Pharm. Sci., 1999, 88, 111-120.
[104]	Briggs, J. M.; Antosiewicz, J. Simulation of pH-dependent properties of proteins using mesoscopic models. Rev. Comput. Chem., 1999, 13, 249-311 and references therein.
[105]	Ullmann, G. M.; Knapp, E. W. Electrostatic models for computing protonation and redox equilibria in proteins. Eur. Biophys. J., 1999, 28, 533-551.
[106]	Crnogorac, M. M.; Ullmann, G. M.; Kostic N. M. Effects of pH on protein association: modification of the proton-linkage model and experimental verification of the modified model in the case of cytochrome c and plastocyanin. J. Am. Chem. Soc., 2001, 123 (44), 10789-10798.
[107]	Nielsen, J. E.; McCammon, J. A. On the evaluation and optimization of protein X-ray structures for pKa calculations. Protein Sci., 2003, 12, 313-326.
[108]	Tannock, I. F.; Rotin, D. Acid pH in tumors and its potential for therapeutic exploitation. Cancer Res., 1989, 49, 4373-4384.
[109]	Ojugo, A. S.; McSheehy, P. M.; McIntyre, D. J.; McCoy, C.: Stubbs, M.; Leach, M. O.; Judson, I. R.; Griffiths, J. R. Measurement of the extracellular pH of solid tumours in mice by magnetic resonance spectroscopy: a comparison of exogenous 19F and 31P probes. NMR Biomed., 1999, 12, 495-504.
[110]	Said, H. M.; Mohammadkhani, R. Folate transport in intestinal brush border membrane: involvement of essential histidine residue(s). Biochem. J., 1993, 290, 237-240.
[111]	Fei, Y. J; Liu, W.; Prasad, P. D.; Kekuda, R.; Oblak, T. G.; Ganapathy, V.; Leibach, F. H. Identification of the histidyl residue obligatory for the catalytic activity of the human H+/peptide cotransporters PEPT1 and PEPT2. Biochemistry, 1997, 36, 452-460.
[112]	Metzner, L.; Natho, K.; Zebisch, K.; Dorn, M.; Bosse-Doenecke, E.; Ganapathy, V.; Brandsch, M. Mutational analysis of histidine residues in the human proton-coupled amino acid transporter PAT1. Biochim. Biophys. Acta, 2008, 1778, 1042-1050.
[113]	Unal, E. S.; Zhao, R.; Chang. M. H.; Fiser, A., Romero, M. F.; Goldman, I. D. The functional roles of the His 247 and His 281 residues in folate and proton translocation mediated by the human proton-coupled folate transporter SLC46A1. J. Biol. Chem., 2009, 284, 17846-17857.
[114]	Bartlett, P. A.; Hanson, J. E.; Giannousis, P. P. Potent Inhibition of Pepsin and Penicillopepsin by Phosphorus-Containing Peptide Analogues. J. Org. Chem., 1990, 55, 6268-6274.
[115]	Alexov, E. Numerical calculations of the pH of maximal protein stability. The effect of the sequence composition and 3D structure. Eur. J. Biochem., 2004, 271, 173-185.
[116]	Miranda, C.; Escartí, F.; Lamarque, L; Yunta, M. J. R.; Navarro, P.; García-España, E.; Jimeno, M.L. New 1H-pyrazole-containing polyamine receptors able to complex L-glutamate in water at physiological pH values. J. Am. Chem. Soc., 2004, 126, 823-833.
[117]	Alexov, E.; Mehler, E. L.; Baker, N.; Baptista, A. M.; Huang, Y.; Milletti, F.; Nielsen, J. E, Farrell, D.; Carstensen, T.; Olsson, M. H.; Shen, J. K.; Warwicker, J.; Williams, S.; Word, J. M. Progress in the prediction of pKa values in proteins. Proteins: Struct. Funct. Bioinf., 2011, 79, 3260-3275.
[118]	Nielsen, J. E.; Gunner, M. R.; Garcia-Moreno, B. E. The pKa cooperative: a collaborative effort to advance structure-based calculations of pKa values and electrostatic effects in proteins. Proteins: Struct. Funct. Bioinf., 2011, 79, 3249-3259.
[119]	Rose, P. W.; Beran, B.; Bi, C.; Bluhm, W. F.; Dimitropoulos, D.; Goodsell, D. S.; Prlic, A.; Quesada, M.; Quinn, G. B.; Westbrook, J. D.; Young, J.; Yukich, B.; Zardecki, C.; Berman, H. M.; Bourne, P. E. The RCSB protein data bank: redesigned web site and web services. Nucleic Acids Res., 2011, 39, D392-401.
[120]	Janin, J.; Bahadur, R. P.; Chakrabarti, P. Protein-protein interaction and quaternary structure. Q. Rev. Biophys., 2008, 41, 133-80.
[121]	Ozbabacan, S. E.; Engin, H. B.; Gursoy, A.; Keskin, O. Transient protein-protein interactions. Protein Eng. Des. Sel., 2011, 24, 635-648.
[122]	Sheinerman, F. B.; Honig, B. On the role of electrostatic interactions in the design of protein-protein interfaces. J. Mol. Biol., 2002, 318, 161-77.
[123]	Lawrence, M. C.; Colman, P. M. Shape complementarity at protein/protein interfaces. J. Mol. Biol., 1993; 234, 946-50.
[124]	Vakser, I. A.; Aflalo, C. Hydrophobic docking: a proposed enhancement to molecular recognition techniques. Proteins: Struct. Funct. Bioinf., 1994, 20, 320-9.
[125]	McCoy, A. J.; Epa, V. C.; Colman, P. M. Electrostatic complementarity at protein/protein interfaces. J. Mol. Biol., 1997, 268, 570-584.
[126]	Vijayakumar, M.; Wong, K. Y.; Schreiber, G.; Fersht, A. R.; Szabo, A.; Zhou, H-X. Electrostatic enhancement of diffusion-controlled protein-protein association: comparison of theory and experiment on barnase and barstar. J. Mol. Biol., 1998, 278, 1015-24.
[127]	Qin, S.; Pang, X.; Zhou, H. X. Automated prediction of protein association rate constants. Structure, 2011, 19, 1744-1751.
[128]	Keskin, O.; Gursoy, A.; Ma, B.; Nussinov, R. Principles of protein-protein interactions: What are the preferred ways for proteins to interact? Chem. Rev., 2008, 108, 1225-1244.
[129]	Prada-Gracia, D.; Gomez-Gardenes, J.; Echenique, P.; Falo, F. Exploring the free energy landscape: from dynamics to networks and back. PLoS Comput. Biol., 2009, 5, e1000415, 9 pp.
[130]	Jackson, R. M.; Sternberg, M. J. A continuum model for protein-protein interactions: application to the docking problem. J. Mol. Biol., 1995, 250, 258-75.
[131]	Frederick, K. K.; Marlow, M. S.; Valentine, K. G.; Wand, A. J. Conformational entropy in molecular recognition by proteins. Nature, 2007; 448, 325-9.
[132]	Caffrey, D. R.; Somaroo, S.; Hughes, J. D.; Mintseris, J.; Huang, E. S. Are protein-protein interfaces more onserved in sequence than the rest of the protein surface? Protein Science, 2004, 13, 190-202.
[133]	Meszaros, B.; Simon, I.; Dosztanyi, Z. The expanding view of protein-protein interactions: complexes involving intrinsically disordered proteins. Phys. Biol., 2011, 8, 035003, 10 pp.
[134]	Collins, K. D. Charge density-dependent strength of hydration and biological structure. Biophys. J., 1997, 72, 65-76.
[135]	Wadsö, I. Isothermal microcalorimetry for the characterization of interactions between drugs and biological materials. Thermochim. Acta, 1995, 267, 45-59.
[136]	Jelesarov, I.; Bosshard, H. R. Isothermal titration calorimetry and differential scanning calorimetry as complementary tools to investigate the energetics of bimolecular recognition. J. Molec. Recog., 1999, 12, 3-18.
[137]	Fukada, H.; Takahashi, K. Enthalpy and heat capacity changes for the proton dissociation of various buffer components in 0.1 M potassium chloride. Proteins: Struct. Funct. Bioinf., 1998, 33, 159-166.
[138]	Raffaa, R. B.; Staglianoa, G. W.; Spencera, S. D. Protonation effect on drug affinity. Eur. J. Pharmacol., 2004, 483, 323-324.
[139]	Raffa, R. B. (Ed.), Drug-Receptor Thermodynamics: Introduction and Applications. John Wiley and Sons, Chichester, 2001, pp. 1-781.
[140]	Lo Conte, L.; Chothia, C.; Janin, J. The atomic structure of protein-protein recognition sites. J. Mol. Biol., 1999, 285, 2177-98.
[141]	Harms, M. J.; Castaneda, C. A.; Schlessman, J. L.; Sue, G. R.; Isom, D. G.; Cannon, B. R.; Garcia-Moreno, E. B. The pKa values of acidic and basic residues buried at the same internal location in a protein are governed by different factors. J. Mol. Biol., 2009, 389, 34-47.
[142]	Gerstein, M.; Lesk, A. M.; Chothia, C. Structural mechanisms for domain movements in proteins. Biochemistry, 1994, 33, 6739-49.
[143]	Wilson, I. A.; Stanfield, R. L. Antibody-antigen interactions: New structures and new conformational changes. Curr. Opin. Struct. Biol., 1994, 4, 857-67.
[144]	DuBay, K. H.; Geissler, P. L. Calculation of proteins’ total side-chain torsional entropy and its influence on protein-ligand interactions. J. Mol. Biol., 2009; 391, 484-97.
[145]	Todorov, N. P.; Monthoux, P. H.; Alberts, I. L. The influence of variations of ligand protonation and tautomerism on protein-ligand recognition and binding energy landscape. J. Chem. Inf. Mod., 2006, 46, 1134-1142.
[146]	Knox, A. J. S.; Meegan, M. J.; Carta, G.; Lloyd, D. G. Considerations in compound database preparation: “Hidden” impact on virtual screening results. J. Chem. Inf. Mod., 2005, 45, 1908-1919.
[147]	Brooijmans N, Kuntz ID. Molecular recognition and docking algorithms. Ann. Rev. Biophys. Biomol. Struct., 2003, 32, 335-373.
[148]	Kundrotas, P. J.; Alexov, E. Electrostatic properties of protein-protein complexes. Biophys. J., 2006, 91, 1724-36.
[149]	Mitra, R. C.; Zhang, Z.; Alexov, E. In silico modeling of pH-optimum of protein-protein binding. Proteins: Struct. Funct. Bioinf., 2011, 79, 925-936.
[150]	Gilson, M. K.; Zhou, H. X. Calculation of protein-ligand binding affinities. Annu. Rev. Biophys. Biomol. Struct., 2007, 36, 21-42.
[151]	Witham, S.; Talley, K.; Wang, L.; Zhang, Z.; Sarkar, S.; Gao, D.; Yang, W.; Alexov, E. Developing hybrid approaches to predict pKa values of ionizable groups. Proteins: Struct. Funct. Bioinf., 2011, 79, 3389-3399.
[152]	Jones, G.; Willett, P.; Leach, A. R.; Taylor, R. Development and validation of a genetic algorithm for flexible docking. J. Mol. Biol., 1997, 267, 727-748.
[153]	Bayden, A. S.; Fornabaio, M.; Scarsdale, J. N.; Kellogg, G. E. Web application for studying the free energy of binding and protonation states of protein-ligand complexes based on HINT. J .Comput. Aided Mol. Des., 2009, 23, 621-32.
[154]	Rapp, C. S.; Schonbrun, C.; Jacobson, M. P.; Kalyanaraman, C.; Huang, N. Automated site preparation in physics-based rescoring of receptor ligand complexes. Proteins: Struct. Funct. Bioinf., 2009, 77, 52-61.
[155]	Kalliokoski, T.; Salo, H. S.; Lahtela-Kakkonen, M.; Poso, A. The effect of ligand-based tautomer and protomer prediction on structure-based virtual screening. J. Chem. Inf. Mod., 2009, 49, 2742-2748.
[156]	Fornabaio, M.; Cozzini, P.; Mozzarelli, A.; Abraham, D. J.; Kellogg, G. E. Simple, intuitive calculations of free energy of binding for protein-ligand complexes. 2. Computational titration and pH effects in molecular models of neuraminidase-inhibitor complexes. J. Med. Chem., 2003, 46, 4487-4500.
[157]	Cozzini, P.; Fornabaio, M.; Marabotti, A.; Abraham, D. J.; Kellogg, G. E.; Mozzarelli, A. Simple, intuitive calculations of free energy of binding for protein-ligand complexes. 1. Models without explicit constrained water. J. Med. Chem., 2002; 45, 2469-2483.
[158]	Pospisil, P.; Ballmer, P.; Scapozza, L.; Folkers, G. Tautomerism in computer-aided drug design. J. Recept. Signal Transduct. Res., 2003, 23, 361-371.
[159]	Kirchmair, J.; Markt, P.; Distinto, S.; Wolber, G.;, Langer, T. Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection--what can we learn from earlier mistakes? J. Comput. Aided Mol. Des., 2008, 22, 213-28.
[160]	Ferrara, P.; Gohlke, H.; Price, D.J.; Klebe, G.; Brooks C. L. III. Assessing scoring functions for protein-ligand interactions J. Med. Chem., 2004, 47, 3032-3047.
[161]	Zou, X.; Sun, Y.; Kuntz, I. D. Inclusion of solvation in ligand binding free energy calculations using the generalized-Born model. J. Am. Chem. Soc., 1999, 121, 8033-8043.
[162]	Kellenberger, E.; Rodrigo, J.; Muller, P.; Rognan, D. Comparative evaluation of eight docking tools for docking and virtual screening accuracy. Proteins: Struct. Funct. Bioinf., 2004, 57, 225-242.
[163]	Perola, E.; Walters, W. P.; Charifson, P. S. A detailed comparison of current docking and scoring methods on systems of pharmaceutical relevance. Proteins: Struct. Funct. Bioinf., 2004, 56, 235-249.
[164]	Krovat, E. M.; Steindl, T.; Langer, T. Recent advances in docking and scoring. Curr. Comput.-Aided Drug Des., 2005, 1, 93-102.
[165]	Taylor, R. D.; Jewsbury, P. J.; Essex, J. W. A review of protein small molecule docking methods. J. Comput.-Aided Mol. Des., 2002, 16, 151-166.
[166]	Kuntz, I. D.; Blaney, J. M.; Oatley, S. J.; Langridge, R.; Ferrin; Th, E. A geometric approach to macromolecule-ligand interactions. J. Mol. Biol., 1982, 161, 269-288.
[167]	DesJarlais, R. L.; Sheridan, R. P.; Seibel, G. L.; Dixon, J. S.; Kuntz, I. D.; Venkataraghavan, R. Using shape complementarity as an initial screen in designing ligands for a receptor binding site of known threedimensional structure. J. Med. Chem., 1988, 31, 722-729.
[168]	Gschwend, D. A.; Kuntz, I. D. Orientational sampling and rigid-body minimization in molecular docking revisited: On-the-fly optimization and degeneracy removal. J. Comput.-Aided Mol. Des., 1996, 10, 123-132.
[169]	Ewing, T. J. A.; Makino, S.; Skillman, A. G.; Kuntz, I. D. DOCK 4.0: Search strategies for automated molecular docking of flexible molecule databases. J. Comput.-Aided Mol. Des., 2001, 15, 411-428.
[170]	Rarey, M.; Wefing, S.; Lengauer, T. Placement of medium-sized molecular fragments into active sites of proteins. J. Comput.-Aided Mol. Des., 1996, 10, 41-54.
[171]	Zavodszky, M. I.; Sanschagrin, P. C.; Korde, R. S.; Kuhn, L. A. Distilling the essential features of a protein surface for improving protein-ligand docking, scoring, and virtual screening. J. Comput.-Aided Mol. Des., 2002, 16, 883-902.
[172]	Jain, A. N. Surflex: Fully automatic flexible molecular docking using a molecular similarity-based search engine. J. Med. Chem., 2003, 46, 499-511.
[173]	Friesner, R. A.; Banks, J. L.; Murphy, R. B.; Halgren, T. A.; Klicic, J. J.; Mainz, D. T.; Repasky, M. P.; Knoll, E. H.; Shelley, M.; Perry, J. K.; Shaw, D. E.; Francis, P.; Shenkin, P. S. Glide: A new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J. Med. Chem., 2004, 47, 1739-1749.
[174]	Halgren, T. A.; Murphy, R. B.; Friesner, R. A.; Beard, H. S.; Frye, L. L.; Pollard, W. T.; Banks, J. L. Glide: A new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. J. Med. Chem., 2004, 47, 1750-1759.
[175]	Friesner, R. A.; Murphy, R. B.; Repasky, M. P.; Frye, L. L.; Greenwood, J. R.; Halgren, T.A .; Sanschagrin, P. C.; Mainz, D. T. Extra precision Glide: Docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. J. Med. Chem., 2006, 49, 6177-6196.
[176]	Verdonk, M. L.; Cole, J. C.; Hartshorn, M. J.; Murray, C. W.; Taylor, R. D. Improved protein-ligand docking using GOLD. Proteins: Struct. Funct. Bioinf., 2003, 52, 609-623.
[177]	Jones, G.; Willett, P.; Leach, A. R.; Taylor, R. Development and validation of a genetic algorithm for flexible docking. J. Mol. Biol., 1997, 267, 727-748.
[178]	Jones, G.; Willett, P.; Glen, R. C. Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation. J. Mol. Biol., 1995, 245, 43-53.
[179]	Goodsell, D. S.; Olson, A. J. Automated docking of substrates to proteins by simulated annealing. Proteins: Struct. Funct. Bioinf., 1990, 8, 195-202.
[180]	Morris, G. M.; Goodsell, D. S.; Halliday, R. S.; Huey, R.; Hart, W. E.; Belew, R. K.; Olson, A. J. Automated docking using a lamarckian genetic algorithm and an empirical binding free energy function. J. Comput. Chem., 1998, 19, 1639-1662.
[181]	Korb, O.; Stützle, T.; Exner, T. E. PLANTS: Application of ant colony optimization to structure-based drug design. In Ant Colony Optimization and Swarm Intelligence, 5th International Workshop, ANTS 2006, LNCS 4150; Dorigo, M.; Gambardella, L. M.; Birattari, M.; Martinoli, A.; Poli, R.; Stützle, T., Eds. pp 247-258.
[182]	Korb, O.; Stützle, T.; Exner, T. E. An ant colony optimization approach to flexible protein-ligand docking. Swarm Intell., 2007, 2, 115-134.
[183]	Korb, O.; Stützle, T.; Exner, T. E. Empirical scoring functions for advanced protein-ligand docking with PLANTS. J. Chem. Inf. Model., 2009, 49, 84-96.
[184]	Totrov, M.; Abagyan, R. Flexible protein ligand docking by global energy optimization in internal coordinates. Proteins: Struct. Funct. Bioinf., 1997, 1, 215-220.
[185]	McMartin, C.; Bohacek, R. S. QXP: Powerful, rapid computer algorithms for structure-based drug design. J. Comput.-Aided Mol. Des., 1997, 11, 333-344.
[186]	Westhead, D. R.; Clark, D. E.; Murray, C. W. A comparison of heuristic search algorithms for molecular docking. J. Comput.-Aided Mol. Des., 1997, 11, 209-228.
[187]	Baxter, C. A.; Murray, C. W.; Clark, D. E.; Westhead, D. R.; Eldridge, M. D. Flexible docking using tabu search and an empirical estimate of binding affinity. Proteins: Struct. Funct. Bioinf., 1998, 33, 367-382.
[188]	McGann, M.; Almond, H.; Nicholls, A.; Grant, J. A.; Brown, F. Gaussian docking functions. Biopolymers, 2003, 68, 76-90.
[189]	Kontoyianni, M.; McClellan, L. M.; Sokol, G. S. Evaluation of docking performance: Comparative data on docking algorithms. J. Med. Chem., 2004, 47, 558-565.
[190]	Venkatachalam, C. M.; Jiang, X.; Oldfield, T.; Waldman, M. Ligand Fit: A novel method for the shape-directed rapid docking of ligands to protein active sites. J. Mol. Graphics Model., 2003, 21, 289-307.
[191]	Kaul, M.; Pilch, D. S. Thermodynamics of aminoglycoside-rRNA recognition: the binding of neomycin-class aminoglycosides to the A site of 16 S rRNA. Biochemistry, 2002, 41, 7695-7706.
[192]	Kaul, M.; Barbieri, C. M.; Kerrigan, J. E.; Pilch, D. S. Coupling of drug protonation to the specific binding of aminoglycosides to the A site of 16 S rRNA: Elucidation of the number of drug amino groups involved and their identities. J. Mol. Biol., 2003, 326, 1373-1387.
[193]	Schüürmann, G.; Cossi, M.; Barone, V.; Tomasi, J. Prediction of the pKa of carboxilic acids using the ab initio continuum-solvation model PCM-UAHF. J. Phys. Chem. A, 1998, 102, 6706-6712.
[194]	Toth, A. M.; Liptak, M. D.; Phillips, D. L.; Shields, G. C. Accurate relative pKa calculations for carboxylic acids using complete basis set and Gaussian-n models combined with continuum solvation methods. J. Chem. Phys., 2001, 114, 4595-4606.
[195]	Topol, I. A.; Tawa, G. J.; Burt, S. K.; Rashin, A. A. Calculation of absolute and relative acidities of substituted imidazoles in aqueous solvent. J. Phys. Chem. A, 1997, 101, 10075-10081.
[196]	da Silva, C. O.; da Silva, E. C.; Nascimento, M. A. C. Ab initio calculations of absolute pKa values in aqueous solution, I. Carboxylic acids. J. Phys. Chem. A, 1999, 103, 11194-11199.
[197]	Topol, I. A.; Tawa, G. J.; Caldwell, R. A.; Eissenstat, M. A.; Burt, S. K. Acidity of organic molecules in the gas phase and in aqueous solvent. J. Phys. Chem. A, 2000, 104, 9619-9624.
[198]	da Silva, C. O.; da Silva, E. C.; Nascimento, M. A. C. Ab initio calculations of absolute pKa values in aqueous solution, II. Aliphatic alcohols, thiols, and halogenated carboxilic acids. J. Phys. Chem. A, 2000, 104, 2402-2409.
[199]	Liptak, M. D.; Shields, G. C. Accurate pKa calculations for carboxylic acids using complete basis set and Gaussian-n models combined with CPCM continuum solvation methods. J. Am. Chem. Soc., 2001, 123, 7314-7319.
[200]	Jang, Y. H.; Sowers, L. C.; Cagin, T.; Goddard, W. A., III. First principles calculation of pKa values for 5-substituted uracils. J. Phys. Chem. A, 2001, 105, 274-280.
[201]	La Francois, C. J.; Jang, Y. H.; Cagin, T.; Goddard, W. A., III; Sowers, L. C. Conformation and proton configuration of pyrimidine deoxynucleoside oxidation damage products in water. Chem. Res. Toxicol., 2000, 13, 462-470.
[202]	Tomasi, J.; Persico, M. Molecular interactions in solution: An overview of methods based on continuous distributions of the solvent. Chem. Rev., 1994, 94, 2027-2094.
[203]	Cramer, C. J.; Truhlar, D. G. Implicit solvation models: Equilibria, structure, spectra, and dynamics. Chem. Rev., 1999, 99, 2161-2200.
[204]	Orozco, M.; Luque, F. J. Theoretical methods for the description of the solvent effect in biomolecular systems. Chem. Rev., 2000, 100, 4187-4225.
[205]	Tomasi, J. Thirty years of continuum solvation chemistry: a review, and prospects for the near future.Theor. Chem. Acc., 2004, 112, 184-203.
[206]	Tomasi, J. Quantum mechanical continuum solvation models. Chem. Rev., 2005, 105, 2999-3094.
[207]	Cramer, C. J.; Truhlar, D. G. A universal approach to solvation modeling. Acc. Chem. Res., 2008, 41, 760-768.
[208]	Ho, J.; Coote, M. L. A universal approach for continuum solvent pKa calculations: are we there yet? Theor. Chem. Acc., 2010, 125, 3-21.
[209]	Czodrowski, P. Prediction of protonation states in ligand-protein complexes upon ligand binding Dissertation zur Erlangung des Doktorgrades der Naturwissenschaften (Dr. rer. nat.) dem Fachbereich Pharmazie der Philipps-UniversitÄat Marburg Marburg/Lahn, 2006.
[210]	Ho, J.; Coote, M.L. pKa calculation of some biologically important carbon acids-An assessment of contemporary theoretical procedures. J. Chem. Theory Comput., 2009, 5, 295-306.
[211]	Casasnovas, R.; Frau, J.; Ortega-Castro, J.; Salvà, A.; Donoso, J.; Muñoz, F. Absolute and relative pKa calculations of mono and diprotic pyridines by quantum methods. J .Mol. Struct. Theochem., 2009, 912, 5-12.
[212]	Pliego, J. R. Jr; Riveros, J. M. Theoretical Ccalculation of pKa using the cluster−continuum model. J. Phys. Chem. A, 2002, 106, 7434-7439.
[213]	Kelly, C. P.; Cramer, C. J.; Truhlar, D. G. SM6:  A density functional theory continuum solvation model for calculating aqueous solvation free energies of neutrals, ions, and solute−water clusters. J. Chem. Theory Comput., 2005, 1, 1133-1152.
[214]	Kelly, C. P.; Cramer, C. J.; Truhlar, D. G. Adding explicit solvent molecules to continuum solvent calculations for the calculation of aqueous acid dissociation constants. J. Phys. Chem. A, 2006, 110, 2493-2499.
[215]	Sánchez-Marcos, E.; Terryn, B.; Rivail, J. L. Protonation of nitrogen-containing bases in solution: continuum vs. discrete-continuum models for aqueous solutions. J. Phys. Chem., 1985, 89, 4695-4700.
[216]	Claverie, P.; Daudey, J. P.; Langlet, J.; Pullman, B.; Plazzola, D.; Huron, M. J. Studies of solvent effects. 1. Discrete, continuum, and discrete-continuum models and their comparison for some simple cases: ammonium (1+) ion, methanol, and substituted ammonium (1+) ion. J. Phys. Chem., 1978, 82, 405-418.
[217]	Vyacheslav, S.; Bryantsev, S.; Diallo, M. S.; Goddadrd, W. A. III. Calculation of solvation free energies of charged solutes using mixed cluster/continuum models. J. Phys. Chem. B, 2008, 112, 9709-9719.
[218]	Pliego, J. R. Jr; Riveros, J. M. The cluster−continuum model for the calculation of the solvation free energy of ionic species. J. Phys. Chem. A, 2001, 105, 7241-7247.
[219]	Scherrer, R. A.; Leo, A.J. Multi-pH QSAR: A method to differentiate the activity of neutral and ionized species and obtain true correlations when both species are involved. Mol. Inf., 2010, 29, 687-693.
[220]	Scherrer, R. A.; Donovan, S. F. Automated potentiometric titrations in KCl/water-saturated octanol: Method for quantifying factors influencing ion-pair partitioning. Anal. Chem., 2009, 81, 2768-2778.
[221]	Caron, G.; Ermondi, G.; Scherrer, R. A. Lipophilicity, polarity, and hydrophobicity, in comprehensive medicinal chemistry II, (Eds: B. Testa, H. van de Waterbeemd), Elsevier, Oxford, 2007, ch. 5.18, pp. 425-452.
[222]	Scherrer, R. A.; Donovan, S. F. Species-specific log D in drug design and ADMET analyses. Presented at the 29th National Medicinal Chemistry Symposium, Madison, WI, June 2004, 70 (a copy is available on request).
[223]	Parajuli, R.; Medhi, C. Basicities of some 9-substituted acridine-4-carboxamides: A density functional theory (DFT) calculation. J. Chem. Sci., 2004, 116, 235-241.
[224]	Lehninger, A. L.; Nelson, D. L.; Cox, M. M. Principles of biochemistry, 2nd ed.; Worth Publishers: New York, 1993.
[225]	Steed, J.; Atwood, J. Supramolecular chemistry; John Wiley and Sons, LTD: Chichester, 2000.
[226]	Schneider, H.-J.; Yatsimirsky, A. Principles and methods in supramolecular chemistry; John Wiley and Sons, LTD: Chichester, 2000.
[227]	Fitzmaurice, R. J.; Kyne, G. M.; Douheret, D.; Kilburn, J. D. Synthetic receptors for carboxylic acids and carboxylates. J. Chem. Soc., Perkin Trans., 2002, 1, 841-864.
[228]	Gale, P. A. Anion coordination and anion-directed assembly: highlights from 1997 and 1998. Coord. Chem. Rev., 2000, 199, 181-233.
[229]	Gale, P. A. Anion receptor chemistry: highlights from 1999. Coord. Chem. Rev., 2001, 213, 79-128.
[230]	Sigel, H.; Martin, R. B. Coordinating properties of the amide bond. Stability and structure of metal ion complexes of peptides and related ligands. Chem. Rev., 1982, 82, 385-426.
[231]	Clement, O.; Rapko, B. M.; Hay, B. P. Structural aspects of metal-amide complexes. Coord. Chem. Rev., 1998, 170, 203-243.
[232]	Paz, P. B.; Vega-Hissi, E. G.; Estrada, M. R.; Garro-Martinez, J. C. In silico modeling of the molecular structure and binding of leukotriene A4 into leukotriene A4 hydrolase. Chem. Biol. Drug Des., 2012,80, 902-908.
[233]	Thunnissen, M. M. G. M.; Nordlund ,P.; Haeggstrom, J. Z. Crystal structure of human leukotriene A4 hydrolase, a bifunctional enzyme in inflammation. Nat. Struct. Biol., 2001, 8, 131-135.
[234]	Haeggstrom J. Z. Leukotriene A4 hydrolase/aminopeptidase, the gatekeeper of chemotactic leukotriene B4 biosynthesis. J. Biol. Chem., 2004, 279, 50639-50642.
[235]	Kirkland, T. A.; Adler, M.; Bauman, J. G.; Chen, M.; Haeggstrom, J. Z.; King. B.; Kochanny. M. J.; Liang, A. M.; Mendoza, L.; Phillips, G. B.; Thunnissen, M; Trinh, L.; Whitlow, M.; Ye, B.; Ye ,H., Parkinson, J.; Guilford, W. J. Synthesis of glutamic acid analogs as potent inhibitors of leukotriene A4 hydrolase. Bioorgan. Med. Chem., 2008, 16, 4963-4983.
[236]	Thunnissen, M. M. G. M.; Andersson, B.; Samuelsson, B.; Wong, C. H.; Haeggstrom, J. Z. Crystal structures of leukotriene A4 hydrolase in complex with captopril and two competitive tightbinding inhibitors. FASEB J., 2002, 16, 1648-1650.
[237]	Gavernet, L.; Palestro, P. H.; Bruno-Blanch, L. Docking applied to the study of inhibitors of c-met kinase. ISRN Phys. Chem., 2012, Article ID 391897, 5 pages.
[238]	Patronov, A.; Dimitrov, I.; Flower , D. R.; Doytchinova, I. Peptide binding to HLA-DP proteins at pH 5.0 and pH 7.0: a quantitative molecular docking study. BMC Struct. Biol., 2012, 12, 20-34.
[239]	Warren, G. L.; Andrews, C. W.; Capelli, A.-M.; Clarke, B.; LaLonde, J.; Lambert, M. H.; Lindvall, M.; Nevins, N.; Semus, S. F.; Senger, S.; Tedesco, G.; Wall, I. D.; Woolven, J. M.; Peishoff, E. C.; Head, M. S. A critical assessment of docking programs and scoring functions. J. Med. Chem., 2006, 49, 5912-5931.
[240]	ten Brink, T.; Exner, T. E. A combined combinatorial and pKa-based approach to ligand protonation states. J. Cheminf., 2010, 2 (Suppl 1), P43.
[241]	Aubard, J.; Schwaller, M. A.; Pantigny, J.; Marsault, J. P.; Levi, G. Surface-enhanced Raman spectroscopy of ellipticine, 2-N-methylellipticinium and their complexes with DNAJ . Raman. Spectrosc., 1992, 23, 373-377.
[242]	Warshel, A. Electrostatic basis of structure-function correlation in proteins. Accounts Chem. Res., 1981, 14, 284-290.
[243]	Demchuk ,E.; Wade, R. C. Improving the continuum dielectric approach to calculating pKas of ionizable groups in proteins. J. Phys. Chem., 1996, 100, 17373-17387.
[244]	Nielsen, J. E.; Vriend, G. Optimizing the hydrogen-bond network in Poisson-Boltzmann equation-based pKa calculations. Proteins: Struct. Funct. Bioinf., 2001, 43, 403-412.
[245]	Karshikoff, A. A simple algorithm for the calculation of multiplesite titration curves. Protein Eng., 1995, 8, 243-248.
[246]	Mehler, E. L.; Guarnieri, F. A self-consistent, microenvironment modulated screened Coulomb potential approximation to calculate pH-dependent electrostatic effects in proteins. Biophys. J., 1999, 77, 3-22.
[247]	Wisz, M. S.; Hellinga, H. W. An empirical model for electrostatic interactions in proteins incorporating multiple geometry-dependent dielectric constants. Proteins: Struct. Funct. Bioinf., 2003, 51, 360-377.
[248]	Havranek, J. J.; Harbury, P. B. Tanford-Kirkwood electrostatics for protein modeling. Proc. Natl. Acad. Sci. USA, 1999, 96, 11145-11150.
[249]	Nielsen, J. Calculating pKa values in enzyme active sites. Protein Sci., 2003, 12, 1894-1901.
[250]	Barth, P.; Alber, T.; Harbury, P. B. Accurate, conformation-dependent predictions of solvent effects on protein ionization constants. Proc. Natl. Acad. Sci. USA, 2007, 104, 4898-4903.
[251]	Godoy-Ruiz, R., Perez-Jimenez, R.; Garcia-Mira, M. M.; del Pino, I. M. P.; Sanchez-Ruiz, J. M. Empirical parametrization of pK values for carboxylic acids in proteins using a genetic algorithm. Biophys. Chem., 2005, 115, 263-266.
[252]	He, Y.; Xu, J.; Pan, X. M. A statistical approach to the prediction of pKa values in proteins. Proteins: Struct. Funct. Bioinf., 2007, 69, 75-82.
[253]	Simonson, T.; Carlsson, J.; Case, D. A. Proton binding to proteins: pKa calculations with explicit and implicit solvent models. J. Am. Chem. Soc., 2004, 126, 4167-4180.
[254]	Tynan-Connolly, B. M.; Nielsen, J. E. Redesigning protein pKa values. Protein Sci., 2007, 16, 239-249.
[255]	Del Buono, G. S.; Figueirido, F. E.; Levy, R. M. Intrinsic pKas of ionizable residues in proteins: an explicit solvent calculation for lysozyme. Proteins: Struct. Funct. Genet., 1994, 20, 85-97.
[256]	Warshel, A.; Sussman, F.; King, G. Free energy of charges in solvated proteins: microscopic calculations using a reversible charging process. Biochemistry, 1986, 25, 8368-8372.
[257]	http://www.opensource.org/licenses/BSD-2-Clause (accesed 2014/9/3).
[258]	http://propka.ki.ku.dk/. (accesed 2014/9/3).
[259]	Warr, W. Tautomerism in chemical information management systems. J. Comput.-Aided Mol. Des., 2010, 24, 497-520.
[260]	Brenk, R.; lrwin, J. J.; Shoichet, B. K. Here be dragons: docking and screening in an uncharted region of chemical space. J. Biomol. Screen, 2005, 10, 667-674.
[261]	Kellogg, G. E.; Fornabaio, M.; Spyrakis, F.; Lodola, A.; Cozzini, P.; Mozzarelli, A.; Abraham, D. J. Getting it right: modeling of pH, solvent and “nearly” everything else in virtual screening of biological targets. J. Mol. Graph. Mod., 2004, 22, 479-486.
[262]	Bountis T. (Ed.), Proton transfer in hydrogen-bonded systems, NATO ASI Series B: Physics, vol. 291, Plenum Press, New York, 1992, pp. 1-355.
[263]	Kollman, P. A. Free energy calculations: applications to chemical and biochemical phenomena, Chem. Rev., 1993, 93, 2395-2417.
[264]	Reddy, M. R.; Erion, M. D.; Agarwal, A. Free energy calculations: use and limitations in predicting binding affinities, Rev. Comput. Chem., 2000, 16, 217-304.
[265]	Straatsma, T. P. Free energy by molecular simulation, Rev. Comput. Chem., 1996, 9, 81-127.
[266]	Ota, N.; Stroupe, C.; Ferreira da Silva, J. M.; Shah, S. A.; Mares-Guia, M.; Brunger, A. T. Non-Boltzmann thermodynamic integration (NBTI) for macromolecular systems: Relative free energy of binding of trypsin to benzamidine and benxylamine, Proteins: Struct. Funct. Genet., 1999, 37, 641-653.
[267]	Åqvist, J.; Luzhkov, V. B.; Brandsal, B. O. Ligand binding affinities from MD simulations, Acc. Chem. Res., 2002, 35, 358-365.
[268]	Jorgensen, W. L. Free energy calculations: a breakthrough for modeling organic chemistry in solution, Acc. Chem. Res., 1989, 22, 184-189.
[269]	Grant, J.A.; Pickup, B.T.; Nicholls, A. A smooth permittivity function for Poisson-Boltzmann solvation methods, J. Comput. Chem., 2001, 22, 608-640.
[270]	Kollman, P.A.; Massova, I.; Reyes, C.; Kuhn, B.; Huo, S.; Chong, L.; Lee, M.; Lee, T.; Duan, Y.; Wang, W.; Donini, O.; Cieplak, P.; Srinivasan, J.; Case, D.A.; Cheatham III, T.E. Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. Acc. Chem. Res., 2000, 33, 889-897.
[271]	Fogolari, F.; Brigo, A.; Molinari, H. Protocol for MM/PBSA molecular dynamics simulations of proteins, Biophys. J., 2003, 85, 159-166.
[272]	Gohlke, H.; Kiel, C.; Case, D.A. Insights into protein-protein binding by binding free energy calculation and free energy decomposition for the Ras-Raf and Ras-RaIGDS complexes, J. Mol. Biol., 2003, 330, 891-913.
[273]	Böhm, H.-J.; Stahl, M. Rapid empirical scoring functions in virtual screening applications, Med. Chem. Res., 1999, 9, 445-462.