Modeling Catalysis in Allosteric Enzymes: Capturing Conformational Consequences.

Abstract

Greater understanding of enzymatic mechanisms aids the discovery of new targets for biologics, the development of biocatalytic transformations, and de novo enzyme design. Methods using quantum mechanical (QM) potentials, such as Density Functional Theory (DFT), have enabled complex multistep enzymatic mechanisms to be studied, often in quantitative detail. Nevertheless, the dynamic interconversion of enzyme conformations between active and inactive catalytic forms, involving length- and timescales inaccessible to QM treatments, presents a formidable challenge for the development of computational models for allosterically modulated enzymes. We present an overview of the key concepts underlying multistate models of enzyme catalysis, enzyme allostery, and the challenge that large-scale conformational changes pose for methods using QM, QM/MM, and MM potentials. Structural clustering is highlighted as a valuable approach to bridge molecular dynamics conformational sampling of MM potentials and quantum chemical cluster models of catalysis. Particularly relevant to this discussion is structural allostery, which serves as the exemplar of conformational consequences. Here, a well-characterized allosteric enzyme, Imidazole Glycerol Phosphate Synthase (IGPS), is used to showcase the importance of multiple conformations and guide a new direction for qualitative understanding and quantitative modeling in enzyme catalysis.