Modeling conformational heterogeneity in biomolecules
Date
2023
Journal Title
Journal ISSN
Volume Title
Abstract
Regulation of biocatalytic cascades is essential for biological processes but has yet to be exploited in real-world applications. Allostery is a prime example, where binding of an effector molecule alters function in a remote location of the same biomolecule. V-type allostery is especially fascinating, as the reaction rate can be either increased or decreased in response to effector binding. Determining how conformational changes affect the reaction rate is challenging due to the disparity of timescales between the underlying molecular processes. Experimental methods, such as X-ray crystallography, can help to capture large-scale conformational change. However, the resulting structures are not guaranteed to correspond to the biophysical state relevant to the research questions being addressed. Structural changes that occur during the chemical reaction are particularly elusive to this approach. To understand the connection between conformational change and catalytic consequence, a description of the reaction mechanism and relevant configurations is needed. Quantum mechanical (QM) methods can be used to propose enzyme reaction mechanisms by modeling femtosecond motions of forming and breaking bonds. Large-scale conformational changes take place over much longer timescales that cannot be simulated at the QM level, therefore requiring classical simulation techniques. This dissertation focuses on the challenges posed by conformational change in the field of computational biocatalysis. The first chapter examines the prevalence of conformational change in enzymes, its relationship to catalysis, and the difficulties it presents. The second chapter looks at the influence of active site structural features on reaction rates in the allosteric enzyme IGPS using QM approaches and energy decomposition schemes. The third chapter covers the development of methods that use molecular dynamics (MD) simulations to analyze relevant structural states from simulation data and identify long-range communication pathways in biomolecules. The fourth chapter presents a Python code, enzyASM, that automates the generation of QM-based truncated active site models and discusses ongoing developments that will aid reproducibility and standardization in this field of research. The fifth and final chapter summarizes the implications of this Thesis work in computational biocatalysis and envisions how remaining challenges can be addressed to maximize potential to solve real-world problems.
Description
Rights Access
Embargo expires: 08/28/2024.
Subject
biocatalysis
quantum chemical cluster approach
allostery
truncated active site
molecular dynamics