Decoding Biochemical Complexity with Simulations and AI-Enhanced Sampling

Please join Yale Chemistry for a theory chemistry seminar with Dr. Marco De Vivo, head of the Molecular Modeling & Drug Discovery Lab at the Italian Institute of Technology (IIT), and Associate Director of the IIT, Computational Sciences.

Summary: In my lecture, I will present our efforts in using molecular simulations and AI-guided enhanced sampling to understand complex chemical processes that often involve functional conformational changes, which are difficult to capture and unambiguously interpret experimentally. Examples will include the group II introns, which are self-splicing ribozymes evolutionarily and chemically related to the eukaryotic spliceosome. I will illustrate how we use simulations to delve into the mechanism by which the RNA core of splicing machineries, including the megadalton human spliceosome, operates at the atomic scale. In this regard, I will also discuss our current efforts to guide the design of RNA-targeted small molecules using free-energy perturbation calculations. Then, I will present our computational investigations of the mechanistic steps in nucleic acid polymerization catalyzed by DNA polymerases, which pose mechanistic questions of increasing complexity and where identifying the appropriate collective variable is inherently challenging. This exemplifies well the benefit of deep-learning-guided enhanced sampling of the configurational space. Overall, these examples demonstrate how atomistic molecular simulations can nowadays enable the prospective exploration of ultra-large, realistic multicomponent protein/nucleic acid systems.

Biography: Dr. De Vivo is head of the Molecular Modeling and Drug Discovery laboratory at the Italian Institute of Technology (IIT). He is also the Associate Director of the IIT, responsible for Computational Sciences. He is the Director of the Italian CECAM-IT-SIMUL node of CECAM (https://www.cecam.org), an organization that promotes advanced computational methods for essential problems in frontier areas of science and technology. The lab develops and applies computational methods to achieve an atomic-level comprehension of chemical systems. This information is used to design potent inhibitors and nanoparticles with programmed properties as a promising starting point for drug discovery programs. His research activity is partially supported by the Italian Association for Cancer Research (AIRC), where he is now a Member of the Technical Scientific Committee. In 2017, he received the Outstanding Junior Faculty Award from the American Chemical Society (ACS), Computers in Chemistry Division. He is a member of the Editorial Advisory Board of scientific journals like JCIM (ACS Publications) and Chem (Cell Press). In 2021, he co-founded IAMA Therapeutics, which is now a clinical-stage startup developing new drugs for brain disorders. In 2023, he received the ESMEC International Alumni Award from the European School of Medicinal Chemistry. In 2024, he was elected Vice President (Future President, 2026-2028) of the International Society of Quantum Biology and Pharmacology (ISQBP). He is a Board Member of the Pharmaceutical Chemistry Division of Società Chimica Italiana. He is the Executive Editor of the Journal of Chemical Theory and Computation (ACS publication), the reference journal for the broad community of computational chemists. For more information on Dr. De Vivo’s research: Home - Molecular Modeling and Drug Discovery - IIT.

Hosted by Prof. Bill Jorgensen.