Abstract
Appropriate treatment of water contributions to protein-ligand interactions is a very challenging problem in
the context of adequately determining the number of waters to investigate and undertaking the conformational
sampling of the ligands, the waters, and the surrounding protein. In the present study, an extension of the Site
Identification by Ligand Competitive Saturation-Monte Carlo (SILCS-MC) docking approach is presented that
enables determination of the location of water molecules in the binding pocket and their impact on the predicted
ligand binding orientation and affinities. The approach, termed SILCS-WATER, involves MC sampling of the
ligand along with explicit water molecules in a binding site followed by selection of a subset of waters within
specified energetic and distance cutoffs that contribute to ligand binding and orientation. To allow for
convergence of both the water and ligand orientations, SILCS-WATER is based on just the overlap of the
ligand and water with the SILCS FragMaps and the interaction energy between the waters and ligand. Results
show that the SILCS-WATER methodology is able to capture important waters and improve ligand binding
orientations. For 6 of 10 multiple-ligand protein systems the method improved relative binding affinity
prediction against experimental results, with substantial improvements in three systems, when compared to
standard SILCS-MC. Improved reproduction of crystallographic ligand binding orientations is shown to be an indicator of when SILCS-WATER will yield improved binding affinity correlations. The method also identifies
waters interacting with ligands that occupy unfavorable locations with respect to the protein whose
displacement through the appropriate ligands modifications should improve ligands binding affinity. Results
are consistent with the binding affinity being modeled as a ligand-water complex interacting with the protein.
The presented approach offers new possibilities in revealing water networks and their contributions to the
binding orientation and affinity of a ligand to a protein and is anticipated to be of utility for computer-aided
drug design.
Supplementary materials
Title
SI for Modeling Ligand Binding Site Water Networks with Site-Identification by Ligand Competitive Saturation: Impact on Ligand Binding Orientations and Relative Binding Affinities
Description
Workflow of SILCS-WATER, detailed energetic output of local pose refinement using very local sampling of crystal ligand and crystal waters, various analyses of local ligand and exhaustive water sampling, exhaustive ligand and exhaustive water sampling, and explicit performance of SILCS-WATER and standard SILCS-MC on 10 ligand sets with corresponding protein systems.
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