SBIR/STTR Award attributes
Project Summary Computational chemistry has revolutionized drug discovery, reducing by months or even years the amount of time it takes to discover and refine a lead candidate. Nowhere has the contribution of computational chemistry been greater than in the realm of virtual screening (VS) to identify an initial hit to a drug target receptor. It is now routine to screen 106-108 virtual compounds via molecular docking to identify potential binders. A small number of these will be purchased and screened, which is a slower and more expensive process. While docking is demonstrably useful for brute force triage, it is also generally unreliable for rank-ordering the compounds that survive the triage. There is a substantial and unmet need for computational methods that are better at rank ordering that can further reduce the number of compounds that survive to purchase/screening. Interest is growing in an approach termed ABFE, in which the Absolute Binding Free Energies of diverse ligands can be evaluated for a common protein receptor target. This approach is a natural outgrowth of relative binding free energy (RBFE) methods, the most well-known of which is Free Energy Perturbation (FEP). In recent years, the application of FEP for hit-to-lead optimization has exploded, thanks to increasing computer resources and automized workflows. With a reliable ABFE approach, further enrichment of the potential binders that come from dock-based screening can be obtained, improving the cost/hit ratio for the expensive experimental tail of the screening campaign. Based on FEP, the computational formalism that would make ABFE calculations possible within the screening paradigm has been described, and a few publications have demonstrated that it is, indeed, capable of further enriching the compounds that survive the molecular docking screen. These calculations have still been limited by two issues: 1) Computational throughput; 2) Limitations of the Molecular Mechanics (MM) force field that has been exclusively used in these ABFE/FEP simulations. The limitations of computational throughput are increasingly addressed by expansion in the availability of cloud resources, so the limitations of the MM force field are the primary issue. We propose an ABFE/FEP approach that replaces the limited MM representation with one based on a combined quantum mechanics (QM) +MM approach: QM/MM—where the region of ligand binding is treated using QM. In contrast to MM, QM describes molecular energetics much more exactly, and is broadly appliable to all classes of molecular ligands, unlike MM, which has a large number of known limitations/deficiencies. We will apply ABFE/FEP calculations to a variety of systems to validate the approach within the context of virtual screening, and to demonstrate the improvements that QM/MM allows versus traditional MM approaches.
