- Li Z, Lazaridis T (2006) Thermodynamics of
buried water clusters at a protein-ligand bind-
ing interface. J Phys Chem B 110
(3):1464–1475 - Michel J, Tirado-Rives J, Jorgensen WL (2009)
Energetics of displacing water molecules from
protein binding sites: consequences for ligand
optimization. J Am Chem Soc 131
(42):15403–15411 - Baron R, Setny P, McCammon JA (2010)
Water in cavity-ligand recognition. J Am
Chem Soc 132(34):12091–12097 - Bortolato A, Tehan BG, Bodnarchuk MS,
Essex JW, Mason JS (2013) Water network
perturbation in ligand binding: adenosine A
(2A) antagonists as a case study. J Chem Inf
Model 53(7):1700–1713 - Hummer G (2010) Molecular binding: under
water’s influence. Nat Chem 2(11):906–907 - 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(12):973–980 - Eastman P, Pande VS (2015) OpenMM: a
hardware independent framework for molecu-
lar simulations. Comput Sci Eng 12(4):34–39 - Case DA, Cerutti DS, Cheatham TE et al
(2017) AMBER 16. University of California,
San Francisco - The PyMOL Molecular Graphics System, ver-
sion 1.8, Schro ̈dinger, LLC - Hu B, Lill MA (2014) Watsite: hydration site
prediction program with Pymol interface. J
Comput Chem 35(16):1255–1260 - Word JM, Lovell SC, Richardson JS et al
(1999) Asparagine and glutamine: using
hydrogen atom contacts in the choice of side-
chain amide orientation. J Mol Biol 285
(4):1735–1747 - Maier JA, Martinez C, Kasavajhala K et al
(2015) ff14SB: improving the accuracy of pro-
tein side chain and backbone parameters from
ff99SB. J Chem Theory Comput 11
(8):3696–3713 - Wang J, Wolf RM, Caldwell JW et al (2004)
Development and testing of a general amber
force field. J Comput Chem 25(9):1157–1174 - Wang J, Wang W, Kollman PA, Case DA
(2006) Automatic atom type and bond type
perception in molecular mechanical calcula-
tions. J Mol Graph Model 25(2):247–260- Yang Y, Hu B, Lill MA (2014) Analysis of
factors influencing hydration site prediction
based on molecular dynamics simulations. J
Chem Inf Model 54(10):2987–2995 - Sastry GM, Adzhiqirey M, Day T et al (2013)
Protein and ligand preparation: parameters,
protocols, and influence on virtual screening
enrichments. J Comput Aided Mol Des 27
(3):221–234 - Hornak V, Abel R, Okur A et al (2006) Com-
parison of multiple Amber force fields and
development of improved protein backbone
parameters. Proteins 65(3):712–725 - Lindorff-Larsen K, Piana S, Palmo K et al
(2010) Improved side-chain torsion potentials
for the Amber ff99SB protein force field. Pro-
teins 78(8):1950–1958 - Zielkiewicz J (2005) Structural properties of
water: comparison of the SPC, SPCE, TIP4P,
and TIP5P models of water. J Chem Phys 123
(10):104501 - Horn HW, Swope WC, Pitera JW (2004)
Development of an improved four-site water
model for biomolecular simulations: TIP4P-
Ew. J Chem Phys 120(20):9665–9678 - Izadi S, Anandakrishnan R, Onufriev AV
(2014) Building water models: a different
approach. J Phys Chem Lett 5(21):3863–3871 - Heyer LJ, Kruglyak S, Yooseph S (1999)
Exploring expression data: identification and
analysis of coexpressed genes. Genome Res 9
(11):1106–1115 - Ester M, Kriegel HP, Sander J, Xu X (1996) A
density-based algorithm for discovering clus-
ters in large spatial databases with noise. In:
Proceedings of the second international confer-
ence on knowledge discovery and data mining
(KDD-96). AAAI Press, CA - Bayly CI, Cieplak P, Cornell W, Kollman PA
(1993) A well-behaved electrostatic potential
based method using charge restraints for deriv-
ing atomic charges: the RESP model. J Phys
Chem 97:10269–10280 - Jakalian A, Jack DB, Bayly CI (2002) Fast,
efficient generation of high-quality atomic
charges. AM1-BCC model:
II. Parameterization and validation. J Comput
Chem 23(16):1623–1641
402 Ying Yang et al.