Journal of Molecular Modeling

, Volume 9, Issue 3, pp 172–182

WaterScore: a novel method for distinguishing between bound and displaceable water molecules in the crystal structure of the binding site of protein-ligand complexes

  • Alfonso T. García-Sosa
  • Ricardo L. Mancera
  • Philip M. Dean
Original Paper

DOI: 10.1007/s00894-003-0129-x

Cite this article as:
García-Sosa, A.T., Mancera, R.L. & Dean, P.M. J Mol Model (2003) 9: 172. doi:10.1007/s00894-003-0129-x

Abstract

We have performed a multivariate logistic regression analysis to establish a statistical correlation between the structural properties of water molecules in the binding site of a free protein crystal structure, with the probability of observing the water molecules in the same location in the crystal structure of the ligand-complexed form. The temperature B-factor, the solvent-contact surface area, the total hydrogen bond energy and the number of protein–water contacts were found to discriminate between bound and displaceable water molecules in the best regression functions obtained. These functions may be used to identify those bound water molecules that should be included in structure-based drug design and ligand docking algorithms.

Figure The binding site (thin sticks) of penicillopepsin (3app) with its crystallographically determined water molecules (spheres) and superimposed ligand (in thick sticks, from complexed structure 1ppk). Water molecules sterically displaced by the ligand upon complexation are shown in cyan. Bound water molecules are shown in blue. Displaced water molecules are shown in yellow. Water molecules removed from the analysis due to a lack of hydrogen bonds to the protein are shown in white. WaterScore correctly predicted waters in blue as Probability=1 to remain bound and waters in yellow as Probability<1×10−20 to remain bound.

Keywords

Protein hydrationDrug designBound water moleculesMultivariate logistic regression

Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  • Alfonso T. García-Sosa
    • 1
  • Ricardo L. Mancera
    • 2
  • Philip M. Dean
    • 2
  1. 1.Department of PharmacologyUniversity of CambridgeCambridgeUK
  2. 2.De Novo PharmaceuticalsCambridgeUK