SBIR/STTR Research Award

Absolute binding free energies for virtual screening: A novel implementation of quantum mechanics/molecular mechanics (QM/MM) for FEP that allows substantial sampling and a significant quantum region

Award identifier 3f90c9c5fb8c80c11a121ffdc2108feb1a14b5782b424de710199b6aeb8a0a14Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$273,361

Program and phase

SBIR · Phase I

Award year

2023

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
QUANTUM SIMULATION TECHNOLOGIES INC
Proposal award date
2023-09-01
Contract end date
2024-08-31
UEI
XH9CRG6SG987
Solicitation number
PA22-176
Topic code
400

Research abstract

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.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

8 SBIR/STTR records share this UEI (2021–2024). Reported award amounts total $3,513,750. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services, National Science Foundation, Department of Energy

Agency intelligence

Department of Health and Human Services

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