Harnessing Biomolecular Simulations to Understand Protein Dynamics and Allostery

Enzyme malfunction underlies countless human diseases, and enzymes are both important drug targets, and therapeutics, with over a century of use of enzymes to treat a range of disorders. Enzymes are dynamic entities, and their conformational dynamics is essential to regulating their function and catalytic activities. There is increasing evidence that enzyme conformational dynamics can be effectively targeted both in drug discovery and for protein engineering purposes (for instance to generate new enzyme therapeutics). Successfully exploiting such dynamics for drug discovery or engineering, however, requires intimate understanding of the conformational transitions involved, how they are regulated, and how they link with the chemical step(s) of catalysis. This proposal will use computational tools to in detail explore the links between conformational dynamics, allosteric regulation and function in two sets of key biomedically important enzymes: PriA and TrpC, which are central enzymes of tryptophan biosynthesis, as well as the eyes absent protein tyrosine phosphatase EYA2. Specifically, simulation will be used to (1) understand loop dynamics and catalysis in PriA and TrpC, (2) understand the role of allosteric regulation in EYA2, and (3) develop novel computational tools for mapping residue and water communication networks in proteins. It should be noted that the enzymes that form the focus of this proposal were selected both for the importance of conformational dynamics and allostery to their activity and regulation, and for their biomedical importance, as the enzymes of tryptophan biosynthesis and PTPs are important drug targets for the treatment of tuberculosis and multiple cancers, respectively. Further, these enzymes are important model systems for the regulation of proteins from the ubiquitous (βα)8- or TIM barrel fold by catalytic loop dynamics, and of haloacid dehalogenase (HAD) phosphatases and PTPs by allostery (EYA PTPs are, unusually, HAD phosphatases). Insights obtained from studying these systems in detail, as well as the associated computational workflows, thus have broader impact for understanding how conformational dynamics can be engineered and manipulated across these enzyme families. Finally, all novel computational tools to be developed in this project will be made open-source and available under liberal licenses, providing valuable resources for the broader simulation community. Project Number: 1R35GM161177-01 | Fiscal Year: 2026 | NIH Institute/Center: National Institute of General Medical Sciences (NIGMS) | Principal Investigator: Shina Caroline Lynn Kamerlin | Institution: GEORGIA INSTITUTE OF TECHNOLOGY, ATLANTA, GA | Award Amount: $432,850 | Activity Code: R35 | Study Section: Special Emphasis Panel[ZRG1 MBBC-A (57)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11255116