Inclusion of Multiple Fragment Types in the Site Identification by Ligand Competitive Saturation (SILCS) Approach

Abstract

The Site Identification by Ligand Competitive Saturation (SILCS) method identifies the location and approximate affinities of small molecular fragments on a target macromolecular surface by performing Molecular Dynamics (MD) simulations of the target in an aqueous solution of small molecules representative of different chemical functional groups. In this study, we introduce a set of small molecules to map potential interactions made by neutral hydrogen bond donors and acceptors, and charged donor and acceptor fragments in addition to nonpolar fragments. The affinity pattern is obtained in the form of discretized probability or, equivalently, free energy maps, called FragMaps, which can be visualized with the target surface. We performed SILCS simulations for four proteins for which structural and thermodynamic data is available for multiple, diverse ligands. Good overlap is shown between high affinity regions identified by the FragMaps and the crystallographic positions of ligand functional groups with similar chemical functionality, thus demonstrating the validity of the qualitative information obtained from the simulations. To test the ability of FragMaps in providing quantitative predictions, we calculate the previously introduced Ligand Grid Free Energy (LGFE) metric and observe its correspondence with experimentally measured binding affinity. LGFE is computed for different conformational ensembles and improvement in prediction is shown with increasing ligand conformational sampling. Ensemble generation includes a Monte Carlo sampling approach that uses the GFE FragMaps directly as the energy function. The results show some, but not all experimental trends are predicted, and warrant improvements in the scoring methodology. In addition, the potential utility of atom-based free energy contributions to the LGFE scores and the use of multiple ligands in SILCS to identify displaceable water molecules during ligand design are discussed.

Pharmacophore Modeling Using Site-Identification by Ligand Competitive Saturation (SILCS) with Multiple Probe Molecules

“…The fifth feature is a POS feature occupying the catalytic site where the ligand hydrogen bond donor groups, usually neutral hydroxyl groups, interact with the two Asp residues. As discussed previously 25 , this inconsistency is due to the Asp residues being deprotonated in the SILCS simulation, while only one Asp residue may be deprotonated 44 . For FXa (Fig.…”

“…The normalized distributions were Boltzmann-transformed to free energies for each FragMap type to yield GFE FragMaps. The convergence of the FragMaps was monitored by calculating overlap coefficients (OC) as previously described 25 . The ten trajectories for each SILCS simulation were divided into two groups as trajectories 1–5 and trajectories 6–10, and FragMaps from each group were separately computed and the OC was calculated between the two groups.…”

Ribosome-Templated Azide–Alkyne Cycloadditions: Synthesis of Potent Macrolide Antibiotics by In Situ Click Chemistry

“…41-44 SILCS maps the free energy affinity pattern of macromolecules onto a grid and may be used to quantitatively estimate relative binding affinities of ligands, yielding ligand grid free energies (LGFE). Details of the SILCS calculation and LGFE analysis are presented in the supporting information.…”

Structure-based design of N-substituted 1-hydroxy-4-sulfamoyl-2-naphthoates as selective inhibitors of the Mcl-1 oncoprotein

“…The FragMaps include contributions from solute-protein interactions and both solute and protein desolvation in the context of protein flexibility. 44,45 In addition, to assure that all regions accessible to solute atoms can be occupied by the studied ligands, the protein surface is defined based on SILCS exclusion maps. 47 Notably, the information content of SILCS may be used to qualitatively direct ligand design as well as to rapidly make quantitative estimates of relative ligand affinities.…”

“…47 Notably, the information content of SILCS may be used to qualitatively direct ligand design as well as to rapidly make quantitative estimates of relative ligand affinities. 48 …”