CDS&E: D3SC: Developing A Molecular Mechanics Modeling Platform (MMMP) for Studying Molecular Interactions

University Of Pittsburgh, Pittsburgh PA

Investigators

Abstract

Junmei Wang of The University of Pittsburgh is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to develop a set of computational tools and build a publicly available platform to facilitate users to study biomolecular systems. The award is cofunded by the Office of Advanced Cyberinfrastructure. High quality molecular mechanics force field (MMFF) parameters are critical to the successful modeling and simulations of various molecular systems. However, users naïve to molecular modeling may find it a daunting task to obtain high-quality MMFF parameters and models without assistance. Dr. Wang and his team are conducting research to develop novel software tools, derive MMFF parameters, build high-quality models, and then integrate them into a freely accessible Molecular Mechanics Modeling Platform (MMMP). MMMP will help users from a broad range of disciplines to study molecular mechanisms of biomolecule-ligand interactions and to calculate the binding affinity accurately and efficiently with ease. Researchers from the drug discovery community can employ MMMP to increase the success rate on the discovery of drug candidates for combating a variety of diseases including the Coronavirus Disease 2019 (COVID-19). A major bottleneck for studying novel molecular systems is the availability, accuracy and validation of consistent molecular mechanics parameter sets. Dr. Junmei Wang is developing a Molecular Mechanics Modeling Platform (MMMP) which integrates force field parameters and residue topologies, novel online tools, and Application Programming Interfaces (APIs) to break the bottleneck. He is conducting research to (1) improve the atom type and bond type perception algorithm to handle arbitrary small molecules; (2) develop molecular mechanics model databases for non-standard amino acid/nucleic acid residues and co-crystallized ligands in the Protein Data Bank, and other compounds (3) develop and advance a software tool coined re-Affinity to bridge the the gap between the efficient docking methods and more computer resource-demanding yet more accurate free energy-based methods; (4) develop a physical, efficient and highly transferrable charge model which can significantly improve the accuracy of free energy calculations; and (5) create a user-friendly Graphic User Interface (GUI), ClickFF, which allows users to generate energy profiles, compare force fields, and optimize force field parameters for selected bonded force field parameters with a few clicks. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.