Modeling Ligand Binding Site Water Networks with Site-Identification by Ligand Competitive Saturation: Impact on Ligand Binding Orientations and Relative Binding Affinities

09 September 2024, Version 2
This content is a preprint and has not undergone peer review at the time of posting.

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.

Keywords

Binding Affinity
Docking
Ligand
Protein
Water
Drug Design
Molecular Dynamics
GCMC
SILCS
SILCS-MC
SILCS-WATER

Supplementary materials

Title
Description
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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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