Testing inhomogeneous solvation theory in structure-based ligand discovery

Abstract

Binding-site water is often displaced upon ligand recognition, but is commonly neglected in structure-based ligand discovery. Inhomogeneous solvation theory (IST) has become popular for treating this effect, but it has not been tested in controlled experiments at atomic resolution. To do so, we turned to a grid-based version of this method, GIST, readily implemented in molecular docking. Whereas the term only improves docking modestly in retrospective ligand enrichment, it could be added without disrupting performance. We thus turned to prospective docking of large libraries to investigate GIST's impact on ligand discovery, geometry, and water structure in a model cavity site well-suited to exploring these terms. Although top-ranked docked molecules with and without the GIST term often overlapped, many ligands were meaningfully prioritized or deprioritized; some of these were selected for testing. Experimentally, 13/14 molecules prioritized by GIST did bind, whereas none of the molecules that it deprioritized were observed to bind. Nine crystal complexes were determined. In six, the ligand geometry corresponded to that predicted by GIST, for one of these the pose without the GIST term was wrong, and three crystallographic poses differed from both predictions. Notably, in one structure, an ordered water molecule with a high GIST displacement penalty was observed to stay in place. Inclusion of this water-displacement term can substantially improve the hit rates and ligand geometries from docking screens, although the magnitude of its effects can be small and its impact in drug binding sites merits further controlled studies.water | inhomogeneous solvation theory | ligand discovery | structure-based drug design | docking T he treatment of receptor-bound water molecules, which are crucial for ligand recognition, is a widely recognized challenge in structure-based discovery (1-4). The more tightly bound a water in a site, the greater the penalty for its displacement upon ligand binding, ultimately leading to its retention and the adoption of ligand geometries that do not displace it. More problematic still is when a new bridging water mediates interactions between the ligand and the receptor. Because the energetics of bound water molecules have been challenging to calculate and bridging waters hard to anticipate, large-scale docking of chemical libraries has typically been conducted against artificially desolvated sites or has kept a handful of ordered water molecules that are treated as part of the site, based on structural precedence (5-8).Recently, several relatively fast approaches, pragmatic for early discovery, have been advanced to account for the differential displacement energies of bound water molecules (9-20), complementing more rigorous but computationally expensive approaches (18)(19)(20)(21)(22). Among the most popular of these has been inhomogeneous solvation theory (IST) (23)(24)(25). IST uses populations from molecular dynamics (MD) simulations on protein (solute) surfaces to calculate the cost of di...

Thermodynamic Insight into the Effects of Water Displacement and Rearrangement upon Ligand Modifications using Molecular Dynamics Simulations

“…Structure–activity relationships are then explained by displacement of strongly or weakly bound solvent molecules, where displacement of weakly bound solvent is expected to increase binding affinities. This treatment of binding site desolvation can help to improve the accuracy of docking algorithms and lead to enhanced scoring functions …”

“…This treatment of binding site desolvation can help to improvet he accuracy of docking algorithms and lead to enhanceds coring functions. [14][15][16] While this approach has the advantage that it typically only needs one simulation per target structure, it neglectst he contribution of water rearrangement upon ligand binding. This approach seems to be the methodo fc hoice for structure-based virtuals creening applicationsd ue to the lower number of simulations required, yet we expect that for lead optimization stages, water rearrangement should be accountedf or.G ilson and co-workersp roposed the application of grid inhomogeneous solvation theory to assess the change in solvation free energy upon chemical modification of the ligand.…”

Hidden Bias in the DUD-E Dataset Leads to Misleading Performance of Deep Learning in Structure-Based Virtual Screening

“…Using the single target CNN model approach, we independently trained the protein-ligand and protein-ligand-water CNN models on 10 targets from the DUD-E dataset. Originally, we hypothesized that adding water information channels could improve virtual screening performance as shown in previous work by Balius et al, in which adding water energy terms to scoring functions improved the virtual screening performance of DOCK3.7 [5].…”

“…Therefore, developing computational tools that can identify lead compounds with pharmacological activity against a selected protein target has been a long-standing goal for computational chemists. A number of structure-based docking tools that aim to predict ligand binding poses and binding affinities have been developed and have enjoyed moderate success over the last three decades [3][4][5][6][7][8][9][10][11][12].…”

The Role of Displacing Confined Solvent in the Conformational Equilibrium of β-Cyclodextrin

“…GIST has been used to analyze the solvation of small molecules, DNA, host-guest, and protein-ligand systems and has also been incorporated into docking scoring functions. 14,16,[31][32][33][34][35][36][37] These studies have emphasized the impact of displacing high energy water molecules from the receptor surface upon ligand binding, which have been thought to indicate binding site "hot spots" in the context of drug design.…”