Jagdish S. Patel, Ph.D.

Summary:  We are driven by a deep intellectual curiosity to explore the complementary synergies between molecular modeling techniques and artificial intelligence (AI) to advance human health. Our research focuses on using molecular modeling to unravel the arrangement and dynamics of protein atoms that dictate their behavior and interactions. In parallel, we harness AI to analyze vast datasets, uncovering and predicting complex biological relationships. We are particularly dedicated to designing proteins, peptides, and synthetic small molecules with significant implications for various disease conditions. Students with a passion for research and a keen interest in learning/applying computational tools like molecular modeling and AI, will find a stimulating and rewarding environment in our lab. You will be supported by a collaborative mentorship structure that includes access to undergraduates, graduate students, postdoc, and the PI.

Minimum Courses:  None, but a background/interest in any of the following classes is preferred: physics, biology, biophysics, biochemistry, medicinal chemistry, statistics, and computer science.

Projects: 

INBRE projects are specifically tailored to align with each student’s experience and interests, whether they focus on molecular modeling, AI, or a combination of both. Below are examples of a few ongoing projects from the many that are currently in progress:

1. Development of Novel Anti-Bacterial Therapeutics: We are using molecular modeling techniques to screen a library of millions of synthetic small molecules, aiming to identify those that could inhibit a histidine kinase protein in Pseudomonas aeruginosa, a pathogenic bacterium responsible for infections such as pneumonia and cystic fibrosis complications in humans. This project is done in close collaboration with experimentalist researcher who validates our modeling predictions by testing molecules in the wet lab.

2. Development of an AI Model to Predict Protein Function: We are working with a large dataset of amino acid sequences of opsin protein (a protein responsible for vision in human) to develop an AI model capable of predicting its biological function of sensing light. This model will have applications that extend beyond human health to various other fields.