SILCS — SITE-IDENTIFICATION BY LIGAND COMPETITIVE SATURATION
Our proprietary CADD software technology, SILCS, is a computational functional group mapping technique that provides a detailed view of the entire protein surface and any particular cavities that might be available for drug design.
SILCS gives chemists an intuitive way of interacting with and
visualizing this information.
Site Identification by Ligand Competitive Saturation (SILCS) offers rigorous free energy evaluation of functional group affinity pattern for the entire 3D space in and around a protein. The SILCS method yields functional group free energy maps, or FragMaps, which are precomputed and rapidly used in a variety of ways to facilitate ligand design. FragMaps are generated by molecular dynamics (MD) simulations that include protein flexibility and explicit solvent/solute representation, thus providing an accurate, detailed, and comprehensive collection of information that can be used qualitatively in database screening, fragment-based drug design and lead optimization.
By generating FragMaps using various small solutes representing different functional groups including benzene, propane, methanol, imidazole, formamide, acetaldehyde, methylammonium, acetate, and water, it is possible to map the functional group affinity pattern of a protein. FragMaps encompass the entire protein such that all FragMap types are in all regions. Thus, information on the affinity of all the different types of functional groups is available in and around the full 3D space of the protein or other target molecule.
FragMaps may be used in a qualitative fashion to facilitate ligand design by allowing the medicinal chemist to readily visualize regions where the ligand can be modified or functional groups added to improve affinity and specificity. As the FragMaps include protein flexibility, they indicate regions of the target protein that can “open” thereby identifying regions under the protein surface accessible for ligand binding. In addition to FragMaps, an “exclusion map” is generated based on regions of the system that are not sampled by water or probe molecules during the MD simulations. The exclusion map represents a strictly inaccessible surface.
Many proteins contain binding sites that are partially or totally inaccessible to the surrounding solvent environment that may require partial unfolding of the protein for ligand binding to occur. SILCS sampling of such deep or inaccessible pockets is facilitated by the use of a Grand Canonical Monte Carlo (GCMC) sampling technique in conjunction with MD simulations. Thus, the SILCS technology is especially well suited for ligand design pockets targeting the deep and inaccessible binding sites found in GPCRs, nuclear receptors and so on.
APPLICATIONS OF SILCS METHODOLOGY INCLUDE:
Binding Site Identification
- Binding pocket searching with known ligands
- Binding pocket identification via pharmacophore generation
- Binding pocket identification via fragment screening
- Qualitative ligand optimization by FragMaps visualization
- Quantitative evaluation of ligand atom contributions to binding
- Quantitative estimation of relative ligand affinities
- Quantitative estimation of large numbers of ligand chemical transformations
- Receptor-based 3D pharmacophore models
- Ligand posing using available techniques (Catalyst, etc.)
- Ligand ranking
Fragment-based Ligand Design
- Identification of fragment binding sites
- Estimation of ligand affinity following fragment linking
- Expansion of fragment types
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