Abstract
It is frequently mentioned that QSARs have not generally lived up to expectations, especially in cases where high predictability is expected yet failed to deliver satisfactory results. Even though outliers can provide an increased opportunity in drug discovery research, outliers in SAR and QSAR can contort predictions and affect the accuracy if proper attention is not given. The percentages of outliers in QSARs have not changed appreciably over the last decade. In our previous studies, we suggested two possible sources of outliers in SAR and QSAR. In this paper, we suggest an additional possible source of outliers in QSAR. We presented several literature examples that show one or more water molecules that play a critical role in protein–ligand binding interactions as observed in their crystal structures. These examples illustrate that failing to account for the effects of water molecules in protein–ligand interactions could mislead interpretation and possibly yield outliers in SAR and QSAR. Examples include cases where QSAR, considering the role of water molecules in protein–ligand crystal structures, provided deeper insight into the understanding and interpretation of the developed QSAR.
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References
Kurup A (2003) C-QSAR: a database of 18,000 QSARs and associated biological and physical data. J Comput-Aided Mol Des 17:187–196
Hansch C, Hoekman D, Leo A, Weininger D, Selassie CD (2002) Chem-bioinformatics: comparative QSAR at the interface between chemistry and biology. Chem Rev 102:783–812
Leo A, Medlin ML, BioByte: 201 W 4th St, #204, Claremont, CA 91711-4707 clogp@biobytecom 909-624-5992
Maggiora GM (2006) On outliers and activity cliffs - why QSAR often disappoints. J Comput-Aided Mol Des 46:1535
Cherkasov AM, Eugene N, Fourches D, Varnek A, Baskin II, Cronin M, Gramatica P, Martin YC, Todeschini R, Consonni V, Kuz’min VE, Cramer R, Benigni R, Yang C, Rathman J, Terfloth L, Gasteiger J, Richard A, Tropsha A (2014) QSAR modeling: where have you been? Where are you going to? J Med Chem 57(12):4977–5010
Reunanen N, Raty T, Lintonen T (2020) Automatic optimization of outlier detection ensembles using a limited number of outlier examples. Int J Data Sci Anal 10:377–394
Furusjo E, Svenson A, Rahmberg M, Andersson M (2006) The importance of outlier detection and training set selection for reliable environmental QSAR predictions. Chemosphere 63:99–108
Prabhakaran S. Why outliers detection is important? R-statisticsco. https://www.vshsolutions.com/blogs/using-isolation-forest-for-outlier-detection-in-python%ef%bb%bf/#:~:text=Outlier%20detection%20is%20important%20for%20two%20reasons.%20Outliers,customer%20take%20place%20from%20a%20certain%20geographical%20location
Zhao L, Wang W, Sedykh A, Zhu H (2017) Experimental errors in QSAR modeling sets: what we can do and what we cannot do. ACS Omega 2:2805–2812
Kim KH (2007) Outliers in SAR and QSAR: Is unusual binding mode a possible source of outliers? J Comput Aided Mol Des 21:63–86
Kim KH (2007) Outliers in SAR and QSAR: 2. Is a flexible binding site a possible source of outliers? J Comput Aided Mol Des 21:421–435
Dearden JC, Cronin MTD, Kaiser KLE (2009) How not to develop a quantitative structure-activity or structure-property relationship (QSAR/QSPR). SAR QSAR Environ Res 20:241–266
Toropov AA, Toropova AP (2020) QSPR/QSAR: state-of-art, weirdness, the future. Molecules 25:1292–1396
Muratov EN, Bajorath J, Sheridan RP, Tetko IV, Filimonov D, Poroikov V, Oprea TI, Baskin II, Varnek A, Roitberg A, Isayev O, Curtalolo S, Fourches D, Cohen Y, Aspuru-Guzik A, Winkler DA, Agrafiotis D, Cherkasov A, Tropsha A (2020) QSAR without borders. Chem Soc Rev 49:3525–3564
Gramatica P (2020) Principles of QSAR modeling: comments and suggestions from personal experience. Int J Quant Struct-Property Relat 5:61–97
Tinkov O, Polishchuk P, Grigorev V, Porozov Y (2020) The cross-interpretation of QSAR toxicological models. ISBRA 2020:262–273
Dearden JC (2017) Whither QSAR? Pharm Sci 23:82–83
Doweyko AM (2008) QSAR: dead or alive? J Comput-Aided Mol Des 22:81–89
Cramer RD (2011) Rethinking 3D-QSAR. J Comput-Aided Mol Des 25:197–201
Cramer RD (2012) The inevitable QSAR renaissance. J Comput-Aided Mol Des 26:35–38
Singh A, Singh R (2013) QSAR and its role in target-ligand interaction. Open Bioinform J 7:63–67
Pur G, Kahn I, Garcia-Sosa AT, Sild S, Ahte P, Maran U (2018) Best practices for QSAR model reporting: physical and chemical properties, ecotoxicity, environmental fate, human health, and toxicokinetics endpoints. Environ Health Perspect 126:1–20
Micro Focus, Reflection 50 W Big Beaver, Troy, MI 48084 800-688-3270
Hansch C, Leo A, Unger SH, Kim KH, Nikaitani D, Lien EJ (1973) “Aromatic” substituent constants for structure-activity correlations. J Med Chem 16:1207–1216
Verma RP, Hansch C (2005) An approach toward the problem of outliers in QSAR. Bioorg Med Chem 13:4597–4621
Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov INE, Bourne E (2000) The protein data bank. Nucleic Acids Res 28:235–242
Burley SK, Berman HM, Bhikadiya C, Bi C, Chen L, Costanzo LD, Christie C, Dalenberg K, Duarte JM, Dutta S, Feng Z, Ghosh S, Goodsell DS, Green RK, Guranović V, Guzenko D, Hudson BP, Kalro T, Liang Y, Lowe R, Namkoong H, Peisach E, Periskova I, Prlić A, Randle C, Rose A, Rose P, Sala R, Sekharan M, Shao C, Tan L, Tao YP, Valasatava Y, Voigt M, Westbrook J, Woo J, Yang H, Young J, Zhuravleva M, Zardecki C (2019) RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy. Nucleic Acids Res 47:D464–D474
Madeira F, Park YM, Lee J, Buso N, Gur T, Madhusoodanan N, Basutkar P, Tivey ARN, Potter SC, Finn RD, Lopez R (2019) The EMBL-EBI search and sequence analysis tools APIs in 2019. Nucleic Acids Res 47:W636–W641
Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE (2004) UCSF Chimera–a visualization system for exploratory research and analysis. J Comput Chem 25:1605–1612
Grigoreva LD, Grigorev VY, Yarkov AV (2019) Outlier detection in QSAR modeling of the biological activity of chemicals by analyzing the structure–activity–similarity map. Moscow Univ Chem Bull 74:1–9
Begam BF, Kumar JS (2016) Computer assisted QSAR/QSPR approaches - a review. Indian J Sci Technol 9(8):1–8
Cronin MTD, Schultz TW (2003) Pitfalls in QSAR. J Mol Struct THEOCHEM 622:39–51
Zsido BZ, Hetenyi C (2021) The role of water in ligand binding. Curr Opin Struct Biol 67:1–8
Maurer M, Oostenbrink C (2019) Water in protein hydration and ligand recognition. J Mol Recognit 32:e2810-2818
Yunta MJR (2015) How important is to account for water when modeling biomolecular complexes? Am J Model Optim 3:68–86
Carugo O (2016) Statistical survey of the buried waters in the protein data bank. Amino Acids 48:193–202
Spyrakis F, Ahmed MH, Bayden AS, Cozzini P, Mozzarelli A, Kellogg GE (2017) The roles of water in the protein matrix: a largely untapped resource for drug discovery. J Med Chem 60:6781–6827
Barillari C, Taylor J, Viner R, Essex JW (2007) Classification of water molecules in protein binding sites. J Am Chem Soc 129:2577–2587
Nittinger E, Schneider N, Lange G, Rarey M (2015) Evidence of water molecules - a statistical evaluation of water molecules based on electron density. J Chem Inf Model 55:771–783
Kim KH (2001) Thermodynamic quantitative structure-activity relationship analysis for enzyme-ligand interactions in aqueous phosphate buffer and organic solvent. Bioorg Med Chem 9:1951–1955
Ringe D (1995) What makes a binding site a binding site? Curr Opin Struct Biol 5:825–829
Hong S, Kim D (2016) Interaction between bound water molecules and local protein structures: a statistical analysis of the hydrogen bond structures around bound water molecules. PROTEINS 84:43–51
Darby JF, Hopkins AP, Shimizu S, Robert SM, Brannigan JA, Turkenburg JP, Thomas GH, Hubbard RE, Fischer M (2019) Water networks can determine the affinity of ligand binding to proteins. J Am Chem Soc 141:15818–15826
Klebe G (2006) Virtual ligand screening: strategies, perspectives and limitations. Drug Discov Today 11:580–594
Lu Y, Wang R, Yang CY, Wang S (2007) Analysis of ligand-bound water molecules in high-resolution crystal structures of protein-ligand complexes. J Chem Inf Model 47:668–675
Bembenek SD, Venkatesan H, Peltier HM, Rosen MD, Barrett TD, Kanelakis KC, Palomino HL, Brondstetter TI, Mirzadegan T, Rabinowitz MH (2019) Beyond traditional structure-based drug design: the role of iron complexation, strain, and water in the binding of inhibitors for hypoxia-inducible factor prolyl hydroxylase 2. ACS Omega 4:6703–6708
Rosen M, Venkatesan H, Peltier HM, Bembenek SD, Kanelakis KC, Zhao LX, Leonard BE, Hocutt FM, Wu X, Palomino HL, Brondstetter TI, Haugh PV, Cagnon L, Yan W, Liotta LA, Young A, Mirzadegan T, Shankley NP, Barrett TD, Rabinowitz MH (2010) Benzimidazole-2-pyrazole HIF Prolyl 4-hydroxylase inhibitors as oral erythropoietin secretagogues. ACS Med Chem Lett 1:526–529
Kack H, Doyle K, Hughes SJ, Bodnarchuk MS, Lonn H, Van De Poel A, Palmer N (2019) DPP1 inhibitors: exploring the role of water in the S2 pocket of DPP1 with substituted pyrrolidines. ACS Med Chem Lett 10:1222–1227
Fischer M, Hopkins AP, Severi E, Hawkhead J, Bawdon D, Watts AG, Hubbard RE, Thomas GH (2015) Tripartite ATP-independent Periplasmic (TRAP) transporters use an arginine-mediated selectivity filter for high affinity substrate binding. J Biol Chem 290:27113–27123
Muller A, Severi E, Mulligan C, Watts AG, Kelly DJ, Wilson KS, Wilkinson AJ, Thomas GH (2006) Conservation of structure and mechanism in primary and secondary transporters exemplified by SiaP, a Sialic acid binding virulence factor from haemophilus influenzae. J Biol Chem 281:22212–22222
Johnston JW, Coussens NP, Allen S, Houtman JCD, Turner KH, Zaleski A, Ramaswamy S, Gibson BW, Apicella MA (2008) Characterization of the N-Acetyl-5-neuraminic acid-binding site of the extracytoplasmic solute receptor (SiaP) of nontypeable haemophilus influenzae Strain 2019. J Biol Chem 283:855–865
Thomaston JL, Polizzi NF, Konstantinidi A, Wang J, Kolocouris A, DeGrado WF (2018) Inhibitors of the M2 proton channel engage and disrupt transmembrane networks of hydrogen-bonded waters. J Am Chem Soc 140:15219–15226
Balgi AD, Wang J, Cheng DYH, Ma C, Pfeifer TA, Shimizu Y, Anderson HA, Pinto LH, Lamb RA, DeGrado WF, Roberge M (2013) Inhibitors of the influenza A Virus M2 proton channel discovered using a high-throughput yeast growth restoration assay. PLoS ONE 8:e55271
Orville AM, Elango N, Lipscomb JD, Ohlendorf DH (1997) Structures of competitive inhibitor complexes of protocatechuate 3,4-dioxygenase: multiple exogenous ligand binding orientations within the active site. Biochemistry 36:10039–10051
Elgren TE, Orville AM, Kelly KA, Lipscomb JD, Ohlendorf DH, Que L Jr (1997) Crystal structure and resonance raman studies of protocatechuate 3,4-dioxygenase complexed with 3,4-dihydroxyphenylacetate. Biochemistry 36:11504–11513
Chen D, Li Y, Zhao M, Tan W, Li X, Savidge T, Guo W, Fan X (2018) Effective lead optimization targeting the displacement of bridging receptor ligand water molecules. Phys Chem Chem Phys 20:24399–24407
Orville AM, Lipscomb JD, Ohlendorf DH (1997) Crystal structures of substrate and substrate analog complexes of protocatechuate 3,4-dioxygenase: endogenous Fe3+ ligand displacement in response to substrate binding. Biochemistry 36:10052–10066
Que L Jr, Lipscomb JD, Munck E, Wood JM (1997) Protocatechuate 3,4-dioxygenase inhibitor studies and mechanistic implications. Biochim Biophys Acta 485:60–74
Jordan DB, Lessen TA, Wawrzak Z, Bisaha JJ, Gehret TC, Hansen SL, Schwartz RS, Basarab GS (1999) Design of scytalone dehydratase inhibitors as rice blast fungicides: (N-Phenoxypropyl)-Carboxamides. Bioorg Med Chem Lett 9:1607–1612
Chen JM, Xu SL, Wawrzak Z, Basarab GS, Jordan DB (1998) Structure-based design of potent inhibitors of scytalone dehydratase: displacement of a water molecule from the active site. Biochemistry 51:17735–17744
Wawrzak Z, Sandalova T, Steffems JJ, Basarab GS, Lindqvist T, Lindqvist Y, Jordan DB (1999) High-resolution structures of scytalone dehydratase-inhibitor complexes crystallized at physiological pH. PROTEINS 35:425–439
Guo J, Collins S, Miller WT, Rizzo RC (2018) Identification of a water-coordinating HER2 inhibitor by virtual screening using similarity-based scoring. Biochemistry 57:4934–4951
Fleming FF, Yao L, Ravikumar PC, Funk L, Shook BC (2010) Nitrile-containing pharmaceuticals: efficacious roles of the nitrile pharmacophore. J Med Chem 53:7902–7917
Nazare M, Dill DW, Matter H, Schreuder H, Ritter K, Urmann M, Essrich M, Bauer A, Wagner M, Czech J, Lorenz M, Laux V, Wehner V (2005) Probing the subpockets of factor Xa reveals two binding modes for inhibitors based on a 2-carboxyindole scaffold: a study combining structure-activity relationship and X-ray crystallography. J Med Chem 48:4511–4525
Abel R, Young T, Farld R, Berne BJ, Friesner RA (2008) The role of the active site solvent in the thermodynamics of factor Xa-ligand binding. J Am Chem Soc 130:2817–2831
de Beer SBA, Vermeulen NPE, Oostenbrink C (2010) The role of water molecules in computational drug design. Curr Topics Med Chem 10:55–66
Lam PY, Jadhav PK, Eyermann CJ, Hodge CN, Ru Y, Bacheler LT, Meek JL, Otto MJ, Rayner MM, Wong YN, Chang CH, Weber PC, Jackson DA, Sharpe TR, Erickson-Viitanen S (1994) Rational design of potent, bioavailable, nonpeptide cyclic ureas as HIV protease inhibitors. Science 263:380–384
Grzesiek S, Bax A, Nicholson LK, Yamazaki T, Wingfield P, Stahl SJ, Eyermann CJ, Torchia DA, Hodge CN, Lam PYS, Jadhav PK, Chang CH (1994) NMR evidence for the displacement of a conserved interior water molecule in hiv protease by a non-peptide cyclic urea-based inhibitor. J Am Chem Soc 116:1581–1582
Tame JRH, Murshudov GN, Dodson EJ, Neil TK, Dodson GG, Higgins CF, Wilkinson AJ (1994) The structural basis of sequence-independent peptide binding by OppA protein. Protein Sci 264:1578–1581
Smith KJ, Reid SW, Harlos K, McMichael AJ, Stuart DI, Bell JI, Jones EY (1996) Bound water structure and polymorphic amino acids act together to allow the binding of different peptides to MHC class I HLA-B53. Immunity 4:215–228
Szabo KE, Kyriakis E, Psarra AMG, Karra AG, Sipos A, Docsa T, Stravodimos GA, Katsidou E, Skamnaki VT, Liggri PGV, Zographos SE, Mandi A, Kiraly SB, Kurtan T, Leonidas DD, Somsak L (2019) Glucopyranosylidene-spiro-imidazolinones, a new ring system: synthesis and evaluation as glycogen phosphorylase inhibitors by enzyme kinetics and X-ray crystallography. J Med Chem 62:6116–6136
Brown DG, Sanderson MR, Skelly JV, Jenkins TC, Brown T, Garman E, Stuart DI, Neidle S (1990) Crystal structure of a berenil - dodecanucleotide complex: the role of water in sequence-specific ligand binding. EMBO J 9:1329–1334
Kadirvelra R, Foley BL, Dyekjaer JD, Woods RJ (2008) Involvement of water in carbohydrate-protein binding: concanavalin a revisited. J Am Chem Soc 130:16933–16942
Gregoriou A, Noble MEM, Watson KA, Garman EF, Krulle TM, De La Fuente C, Fleet GWJ, Oikonomakos NG, Hohnson LN (1998) The structure of a glycogen phosphorylase glucopyranose spirohydantoin complex at 1.8 A resolution and 100 K: the role of the water structure and its contribution to binding. Protein Sci 7:915–927
Ladbury JE (1996) Just add water! The effect of water on the specificity of protein ligand binding sites and its potential application to drug design. Chem Biol 3:973–980
Jeszenol N, Balint M, Horvath I, Van Der Spoel D, Hetenyl C (2016) Exploration of interfacial hydration networks of target-ligand complexes. J Chem Inf Model 56:148–158
Wang L, Berne BJ, Friesner RA (2011) Ligand binding to protein-binding pockets with wet and dry regions. Proc Natl Acad Sci USA 108:1326–1330
Schiebel J, Gaspari R, Wulsdorf T, Ngo K, Sohn C, Schrader TE, Cavalli A, Ostermann A, Heine A, Klebe G (2018) Intriguing role of water in protein-ligand binding studied by neutron crystallography on trypsin complexes. Nat Commun 9:3559–3563
Cui D, Zhang BW, Matubayasi N, Levy RM (2018) The role of interfacial water in protein−ligand binding: insights from the indirect solvent mediated potential of mean force. J Chem Theory Comput 14:512–526
Sondergaar CR, Garrett AE, Carstensen T, Pollastri G, Nielsen JE (2009) Structural artifacts in protein-ligand X-ray structures: implications for the development of docking scoring functions. J Med Chem 52:5673–5684
Huang WJ, Binov N, Wishart DS, Kovalenko A (2015) Role of water in ligand binding to maltose-binding protein: insight from a new docking protocol based on the 3D-RISM-KH molecular theory of solvation. J Chem Inf Model 55:317–328
Kim KH (2001) Thermodynamic aspects of hydrophobicity and biological QSAR. J Comput-Aided Mol Des 15:367–380
Gilli G, Gilli P (2009) The nature of the hydrogen bond - outline of a comprehensive hydrogen bond theory. Oxford University Press, New York
Desiraju GR, Steiner T (1999) The weak hydrogen bond. Oxford University Press, Oxford
Jeffrey GA, Saenger W (1994) Hydrogen bonding in biological structures. Springer-Verlag, Berlin
Ferreira de Freitas R, Schapira M (2017) A systematic analysis of atomic protein–ligand interactions in the PDB. Med Chem Commun 8:1970–1981
Dearden JC, Ghafourian T (1998) Hydrogen bonding parameters for QSAR: comparison of indicator variables, hydrogen bond counts, molecular orbital and other parameters. J Chem Inform Comput Sci 39:231–235
Gancia E, Montana JG, Manallack DT (2001) Theoretical hydrogen bonding parameters for drug design. J Mol Graph Model 19:349–362
Fujita T, Nishioka T, Nakajima M (1977) Hydrogen-bonding parameter and its significance in quantitative structure-activity studies. J Med Chem 20:1071–1081
Borges NM, Kenny PW, Montanari CA, Prokopczyk IM, Ribeiro JFR, Rocha JR, Sartori RG (2017) The influence of hydrogen bonding on partition coefficients. J Comput-Aided Mol Des 31:163–181
Abraham MH, Duce PP, Prior DV, Barratt DG, Morris JJ, Taylor PJ (1989) Hydrogen bonding Part 9 Solute proton donor and proton acceptor scales for use in drug design. J Soc Perkin Trans 2(2):1355–1375
Moriguchi I (1974) Quantitative structure activity studies I. Parameters relating to hydrophobicity. Chem Pharm Bull 23:247–257
Hansch C, Leo A (1977) A substituent constants for correlation analysis in chemistry and biology. Wiley, New York
Schultz TW, Moulton BA (1985) Structure-activity relationships of selected pyridines I substituent constant analysis. Ecotoxicol Environ Saf 10:97–111
Charton M, Charton BI (1982) the structural dependence of amino acid hydrophobicity parameters. J Theor Biol 99:629–644
Yang GZ, Lien EJ, Guo ZR (1986) Physical factors contributing to hydrophobic constant p. Quant Struct Act Relat 5:12–18
Yunta MJR (2017) It is important to compute intramolecular hydrogen bonding in drug design? Am J Model Optim 5:24–57
Da YZ, Ito K, Fujiwara H (1992) Energy aspects of oil/water partition leading to the novel hydrophobic parameters for the analysis of quantitative structure-activity relationships. J Med Chem 35:3382–3387
Nakamura K, Hayashi K, Ueda I, Fujiwara H (1995) Micelle/water partition properties of phenols determined by liquid chromatographic method. Proposal for versatile measure of hydrophobicity. Chem Pharm Bull 43:369–373
Raevsky OA, Grigorev VY, Kireev DB, Zefirov NS (1992) Complete thermodynamic description of H-bonding in the framework of multiplicative approach. Quant Struct Act Relat 11:49–63
Raevsky OA, Skvortsov VS (2005) Quantifying hydrogen bonding in QSAR and molecular modeling. SAR QSAR Environ Res 16:287–300
Rosell-Hidalgo A, Young L, Moore AL, Ghafourian T (2020) QSAR and molecular docking for the search of AOX inhibitors: a rational drug discovery approach. J Comput-Aided Mol Des. https://doi.org/10.1007/s10822-020-00360-8
Kim KH (1976) Part I. A quantitative structure-activity correlation study by Hansch analysis, Part II. A study on the role of 1,6-methano[10]annulene nucleus in medicinal agents, M.S. Thesis, Medicinal Chemistry. University of Kansas: Lawrence
Leo A, Hansch C, Elkins D (1971) Partition coefficients and their uses. Chem Rev 71:525–616
Martin YC (1978) Quantitative drug design: a critical introduction. Marcel Dekker, New York
Seiler P (1974) Interconversion of lipophilicites from hydrocarbon/water systems into the octanol/water system. Eur J Med Chem 9:473–479
Leahy DE (1986) Intrinsic molecular volume as a measure of the cavity term in linear solvation energy relationships: octanol-water partition coefficients and aqueous solubilities. J Pharm Sci 75:629–636
Biela A, Nasief NN, Betz M, Heine A, Hangauer D, Klebe G (2013) Dissecting the hydrophobic effect on the molecular level: the role of water, enthalpy, and entropy in ligand binding to thermolysin. Angew Chem Int Ed 4(52):1822–1828
Nasief NN, Tan H, Kong J, Hangauer D (2012) Water mediated ligand functional group cooperativity: the contribution of a methyl group to binding affinity is enhanced by a COO− group through changes in the structure and thermodynamics of the hydration waters of ligand-thermolysin complexes. J Med Chem 55:8283–8302
Li Z, Lazaridis T (2005) The effect of water displacement on binding thermodynamics: concanavalin A. J Phys Chem B 109:662–670
Henchman RH, Tai K, Shen T, McCammon JA (2002) Properties of water molecules in the active site gorge of acetylcholinesterase from computer simulation. Biophys J 82:2671–2682
Michel J, Ttrado-Rives J, Jorgensen WL (2009) Energetics of displacing water molecules from protein binding sites: consequences for ligand optimization. J Am Chem Soc 131:15403–15411
Wang R, Fang X, Lu Y, Wang S (2004) The PDBbind database: collection of binding affinities for protein-ligand complexes with known three-dimensional structures. J Med Chem 47:2977–2980
Wang R, Fang X, Lu Y, Yang CY, Wang S (2005) The PDBbind database: methodologies and updates. J Med Chem 48:4111–4119
Maveyraud L, Mourey L (2020) Protein X-ray crystallography and drug discovery. Molecules 25:1030–1047
Goodford PJ (1985) A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. J Med Chem 28:849–857
Fornabalo M, Spyrakis F, Mozzarelli A, Cozzini P, Abraham DJ, Kellogg GE (2004) Simple, intuitive calculations of free energy of binding for protein-ligand complexes. 3. The free energy contribution of structural water molecules in HIV-1 protease complexes. J Med Chem 47:4507–4516
Young T, Abel R, Kim B, Berne BJ, Friesner RA (2007) Motifs for molecular recognition exploiting hydrophobic enclosure in protein–ligand binding. PNAS 104:808–813
Rossato G, Ernst B, Vedani A, Smiesko M (2011) AcquaAlta: a directional approach to the solvation of ligand-protein complexes. J Chem Inf Model 51:1867–1881
Sridhar A, Ross GA, Biggin PC (2017) Waterdock 2.0: Water placement prediction for Holo-structures with a pymol plugin. PLoS ONE. https://doi.org/10.1371/journal.pone.0172743
Bodnarchuk MS (2016) Water, water, everywhere… It’s time to stop and think. Drug Discov Today 21:1139–1146
Michel J, Tirado-Rives J, Jorgensen WL (2009) Prediction of the water content in protein binding sites. J Phys Chem B 113:13337–13346
Acknowledgements
The author expresses sincere gratitude to Dr. Albert Leo and Mr. Michael Medlin for their generous permission to use the C-QSAR and Bio-Loom programs. He dedicates this paper to Professor Gary L. Grunewald, the late Professor Corwin H. Hansch, and Dr. Yvonne C. Martin. It was Professor Grunewald’s encouragement, guidance, and help in many ways that the author could satisfactorily complete his Ph.D. program at the University of Kansas. Professor Hansch introduced him to the field of QSAR and medicinal chemistry. The life-long advice, encouragement, and friendship of Professor Hansch had aided the author in various ways in his personal life as well as in his research career. Dr. Martin supported him to complete his Ph.D. program as well as promoted him to the field of molecular modeling and 3D-QSAR at Abbott Laboratories. Her enthusiasm and continuous challenge in various research fields set an outstanding example of the author’s research endeavor. As the author dedicates this paper to these three distinguished scientists, he remembers their warmth and kindness throughout his research life.
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Kim, K.H. Outliers in SAR and QSAR: 3. Importance of considering the role of water molecules in protein–ligand interactions and quantitative structure–activity relationship studies. J Comput Aided Mol Des 35, 371–396 (2021). https://doi.org/10.1007/s10822-021-00377-7
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DOI: https://doi.org/10.1007/s10822-021-00377-7