Affinitator:Physics-Based Binding Affinity Estimator

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.

FGF Proteins
All atom model of FGF-Heparin unbinding process used to estimate FGF-Heparin binding free energy.

NSF Award: NSF:2138667

NSF I-Corps Team

Dylan Ogden

Entrepreneurial Lead (EL)

Dylan Ogden is a doctoral student in Cell & Molecular Biology program at the University of Arkansas. Before joining the PhD program in 2018, he received a B.Sc. degreein Biochemistry from the University of Arkansas. Mr. Ogden has technical skills of working with various molecular modeling and visualization software packages and molecular dynamics simulation engines as well as programming in Python, Awk, Perl, and Tcl languages. His current research focus includes developing free energy calculation methods and applying those methods to systems such as glucose transporters glucose transporters and corona virus spike proteins.

Office: Virtual
Phone: 479-575-8497
Email: dsogden@email.uark.edu

Dylan Ogden

Adithya Polasa

Co-Entrepreneurial Lead (Co-EL)

Adithya Polasa is a doctoral student in Cell & Molecular Biology program at the University of Arkansas. Before joining the PhD program in 2018, he received a M.Sc. in Cancer Biology and a B.Sc. in Pharmacy. Mr.Polasa has technical skills of working with various molecular modeling and visualization software packages and molecular dynamics simulation engines as well as programming in Python, Awk, C++, and Tcl languages. His current research focus includes developing free energy calculation methods and applying those methods to systems such as membrane insertase and influenza hemagglutinin.

Office: Virtual
Phone: 479-575-8497
Email: apolasa@email.uark.edu

Adithya Polasa

Brian Umberson

I-Corps Mentor

Brian Umberson has 20+ years of senior leadership experience in startups and bringing deep technologies to the marketplace. Brian has worked in Venture Capital start-ups for most of his career by assisting in product development, launching novel technologies, and commercialization. Venture Capital (VC) portfolios have provided him with extremely rare and valuable experience introducing new technologies to North American Firms. He has a unique blend of experience in Marketing, Sales, Advertising, and Management; yet within a very unique mix of industry segments such as start-up biotech, food processing, FSQR Software, blockchain, medical device & diagnostics, consumer electronics,retail merchandising, construction, commercial development, advertising, and automotive.

Office: Virtual
Phone: 870-273-8020
Email: brian.umberson1024@outlook.com

Brian Umberson

Mahmoud Moradi

Principal Investigator (PI)

Mahmoud Moradi is an Associate Professor in the Department of Chemistry and Biochemistry at the University of Arkansas. After receiving his PhD degree in Physics at the North Carolina State University, Dr. Moradi worked as a Postdoctoral Research Associate at the Beckman Institute, University of Illinois at Urbana-Champaign. Dr. Moradi is an interdisciplinary scientists with rigorous training in various disciplines including computational physics/biophysics, physical chemistry/biochemistry, as well as structural/molecular biology and has conducted research in diverse areas including theoretical and methodological developments for biomolecular simulations as well as application of these methods to study various proteins from fibroblast growth factor to influenza hemagglutinin and multidrug resistance transporters. He has published 34 journal articles and presented 37 talks at national or local conferences or universities. He has three ongoing NSF and NIH projects as a Principal Investigator (PI) including an NSF CAREER award and is a co-PI on an ongoing DOE project.

Office: Virtual
Phone: 479-575-6459
Email: moradi@uark.edu

Mahmoud Moradi

References