Our Science

Our Science : Drug Discovery Platforms : STRUCTURAL AND COMPUTATIONAL DRUG DESIGN

CS-Map identifies high-density consensus sites where diverse probe-types cluster, which suggest possible druggable sites capable of high affinity ligand binding.

We strive to gain structural insights as early as possible in the drug discovery process to guide our medicinal chemistry. Structure-based drug discovery (SBDD) methodologies complement our biochemical and cell-based screening activities and provide new scaffolds to expand the chemical diversity that can be explored in each project.

COMPUTATIONAL SOLVENT MAPPING (CS-MAP)

For SBDD, FORMA utilizes Computational Solvent Mapping (CS-Map), a proprietary computational tool that probes the global surface of target proteins to identify and characterize favorable binding positions, or “hot spots.” This methodology is based on experimental X-ray crystallography and NMR screening studies and is implemented as a multi-stage mapping algorithm using a full molecular mechanics force field energy evaluation. CS-Map identifies high-density consensus sites where diverse probe-types cluster, which suggest possible druggable sites capable of high affinity ligand binding. Given the exquisite sensitivity of CS-Map, we can achieve a direct comparison of binding sites in different structures of a protein or across related protein family members.

The Protein Data Bank (PDB) provides rapid access to publically available protein structure information. CS-Mapping of relevant human protein structures in the PDB (nearly 17,000) has allowed our scientists to study their surface features and organize them into defined categories, which guides the production of shape-directed libraries for screening against target proteins. Furthermore, analysis of “hot spot” patterns, shapes and content from the CS-Map can guide the design of specific inhibitors or focused compound libraries against a single-target structure.