Department of Chemistry Seminar - Integrated Computational Chemistry Approach for Protein Function Analysis and Application to Drug Discovery

Speaker: Prof. Yasuteru Shigeta

Institution: Center for Computational Sciences, University of Tsukuba, Japan

Hosted by: Prof. Haibin SU

Abstract

Computational chemistry has become indispensable for protein function analysis and drug discovery. However, conventional molecular dynamics (MD) simulations face significant challenges, including limited accessible timescales (typically microseconds) relative to biological functions and an inability to describe chemical reactions with standard force fields. To address these limitations, this research presents an integrated computational workflow that combines enhanced sampling techniques with quantum mechanical (QM) descriptions.

Central to this approach is Parallel Cascade Selection Molecular Dynamics (PaCS-MD), which accelerates the exploration of conformational transitions and protein folding problems. For high-precision interaction analysis, the Fragment Molecular Orbital (FMO) method is used to quantitatively evaluate residue-residue and protein-ligand binding energies at the quantum-chemical level, providing superior accuracy over classical molecular mechanics. We utilize the PaCS-MD for flexible docking and estimate the binding energy by FMO to explore the appropriate docking pose.

A major highlight of this work is the development of PaCS-Q, a novel toolkit designed for path sampling in both MD and QM/MM MD simulations. PaCS-Q enables the unbiased, time-resolved exploration of complex biochemical reactions by integrating quantum-level accuracy into the PaCS-MD framework. This allows for the direct observation of bond formation and cleavage without the need for predefined reaction coordinates. The practical utility of these methods is demonstrated in SARS-CoV-2 drug discovery efforts, specifically by analyzing the inhibitory mechanisms of repurposed drugs such as Lopinavir and Ritonavir. Additionally, PaCS-Q has identified transition state structures in enzymatic processes, such as the Claisen rearrangement from chorismate to prephenate, successfully. This integrated methodology offers a powerful platform for bridging the gap between computational simulations and biological reality.

Keywords: Computational chemistry, Quantum chemistry, Molecular dynamics