KGI’s Jeniffer Hernandez and Animesh Ray selected as recipients of the 2021 NIH Director’s Transformative Research Award

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KGI’s Jeniffer Hernandez and Animesh Ray have been selected as the 2021 recipients of the National Institutes of Health (NIH) Director’s Transformative Research Award.

For the project, the team is developing a computational assessment procedure to predict the structure of antibodies that could effectively neutralize a previously unknown antigen or a new virus that may emerge in the future. These findings could have a dramatic impact on any emerging pandemic.

Keck Graduate Institute (KGI) Associate Professor of Biopharmaceutical Sciences, Dr Jeniffer Hernandez and Professor Dr Animesh Ray have been selected as recipients of the National Institutes of Health (NIH) Director’s Transformative Research Award 2021 under the program at NIH High Risk, High Risk – Reward Research Program. This fund supports inherently risky and untested projects that have the potential to create or reverse the paradigms of basic science, technology and medicine.

For the project, the team is developing a computational assessment procedure to predict the structure of antibodies that could effectively neutralize a previously unknown antigen or a new virus that may emerge in the future. These findings could have a dramatic impact on any emerging pandemic.

The project is a multidisciplinary collaboration between Hernandez, Ray and two other principal investigators in the consortium: Dr Stefano Lonardi of the Computer Science Department at UC Riverside, a respected computer scientist who works with machine learning and biological data; and Dr. Matthew Sazinsky of the Department of Chemistry at Pomona College, a protein biochemist trained in the physics of high molecular weight polymers.

In addition to vaccine development, the research project could influence medicine on a larger scale. For example, antibodies could potentially be predicted in a computer to target and neutralize proteins made by cancer cells. Another potential use would be therapies that help patients manage their allergies and hypersensitivity issues.

This five-year project builds on Ray’s 13-year research into machine learning methods to predict new protein-protein interactions.

“Intrinsically, this type of deep machine learning involves a competitive game between some of the real data that it learns by performing a task and random data that the deep learning algorithm itself creates to foil that attempt.” , said Ray. “At the end of the day, we want real data-driven play to be successful.”

This concept is similar in principle to evolution, where random genetic variations emerge and compete with each other. Variations best suited to survival in an organism’s natural environment prevail and are passed on to the next generation.

Another goal of the project is to use single-cell DNA sequencing of the genetic repertoire of antibodies naturally raised against an injected antigen to quickly generate a large amount of data. Subsequent benchmark tests will quantitatively assess the best-performing computational model for predicting a strong binding antibody, then refine it to make a neutralizing antibody that can be quickly tested in the lab.

Monoclonal antibody therapies for COVID-19, which the FDA has urgently approved, have been developed at an unprecedented speed. By the time COVID therapies were being developed, it took them another three months to change from the structure of the viral protein to that of the monoclonal antibody. Ray, Hernandez, and the team believed that if they could do this particular step in a computer in a matter of hours, they felt they likely could have started the clinical trial in March instead of July, saving thousands of lives. . This is the transformative impact of the potential outcomes of this project.

This project, co-led by Ray, Hernandez, Lonardi and Sazinksy, was one of 19 Transformative Research Awards presented this year by the NIH.

“The science brought to the fore by this cohort is exceptionally new and creative and is sure to push the boundaries of what is known,” said NIH Director Francis S. Collins, MD, PhD. “These visionary researchers come from a wide range of career stages and show that revolutionary science can occur at any career level if the right opportunity is given.”

The research project was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under award number R01Al169543. The contents are the sole responsibility of the authors and do not necessarily represent the official opinions of the NIH.

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