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Research Spending & Results

Award Detail

Doing Business As Name:University of Arkansas
  • Mahmoud Moradi
  • (479) 575-6459
Award Date:07/16/2021
Estimated Total Award Amount: $ 50,000
Funds Obligated to Date: $ 50,000
  • FY 2021=$50,000
Start Date:07/15/2021
End Date:12/31/2021
Transaction Type:Grant
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.041
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:I-Corps: Physics-Based Binding Affinity Estimator
Federal Award ID Number:2138667
DUNS ID:191429745
Parent DUNS ID:055600001
Program Officer:
  • Ruth Shuman
  • (703) 292-2160

Awardee Location

Street:1125 W. Maple Street
Awardee Cong. District:03

Primary Place of Performance

Organization Name:University of Arkansas
Street:345 N Campus Dr
Cong. District:03

Abstract at Time of Award

The broader impact/commercial potential of this I-Corps project is the development of a computational tool to make drug design and development more accurate and less time-consuming. Potential users, ranging from small biotech companies and research institutes to major pharmaceutical companies, may take advantage of this technology to filter out a significant number of low-affinity drugs at an early stage of development. A key factor resulting in the high cost of drug development is the high rate of failure, which can be significantly reduced by employing more efficient pre-trial screening methods including using more accurate affinity estimators. The successful implementation of the proposed technology may substantially reduce the research and development spending needed for drug development and eventually make drug development faster and less costly. Such activities may contribute to the public health in the US and around the world by providing more efficient and safer drugs to cure or prevent disease. This I-Corps project is based on the development of a physics-based drug binding affinity estimator that employs state-of-the-art free energy calculation methods based on all-atom molecular dynamics simulations. The proposed estimator can estimate the binding affinity of a drug to its target protein with higher accuracy compared to existing techniques. While the available docking software packages and webservers provide affinity estimates, these estimates are generally rough docking scores rather than true binding affinities because they heavily rely on empirically fitted formulas rather than solely physics-based methods. Unlike the existing docking software, the proposed technology explicitly takes into account important factors such as the effects of the environment and the flexibility of the drug and its target in estimating the binding affinities. The proposed technology may make it possible to calculate binding affinities of the drugs using purely physics-based methods that are much more accurate than their docking software counterparts. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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