All atom model of FGF-Heparin unbinding process used to estimate FGF-Heparin binding free energy.
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.
Dylan OgdenEntrepreneurial Lead (EL) Office: Virtual |
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Adithya PolasaCo-Entrepreneurial Lead (Co-EL) Office: Virtual |
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Brian UmbersonI-Corps Mentor Office: Virtual |
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Mahmoud MoradiPrincipal Investigator (PI) Office: Virtual |
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