Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Abstract

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

Activation Heat Capacities in Pyridoxal Phosphate Enzymes

“…This view falls nicely under the more general framework of the transition-state-like conformation (TLC) recently propounded by Arcus and co-workers . One difference is that they consider larger scale conformational changes such as loop closures and domain movements as part of forming the TLC, while the discussion here is restricted to fully domain- and loop-closed, catalytically competent ES complexes whose conformational fluctuations modulate the detailed positioning of active site residues and the structure of the electrostatic field, thereby modulating the chemical barrier of the single elementary step converting enzyme-bound substrate to enzyme-bound product. − …”

“…Computational studies provide supporting evidence for this hypothesis . Schwartz and co-workers have demonstrated that a very small fraction of high energy lactate dehydrogenase ES conformations allows hydride transfer to occur with reduced chemical barriers. , Ribeiro et al showed that the barrier to chemistry in the active site of HIV-1 protease fluctuates greatly with enzyme conformation on the ns time scale. , They demonstrated that small (0.1 Å) changes in TS structure between different conformations cause large (∼10 kcal/mol) changes in the chemical barrier.…”

Puerarin—A Promising Flavonoid: Biosynthesis, Extraction Methods, Analytical Techniques, and Biological Effects

“…The demand for eco-friendly and cost-effective synthetic routes, particularly for addressing puerarin issues, will make enzymatic synthesis a key factor in innovation and progress in the years ahead [141]. Furthermore, enzymatic synthesis will be enhanced by applying advanced computational tools and machine learning algorithms to design and optimize enzymes for specific synthesis pathways for different drugs or natural compounds, such as puerarin [142,143].…”

CHARMM-GUI QM/MM Interfacer for a Quantum Mechanical and Molecular Mechanical (QM/MM) Simulation Setup: 1. Semiempirical Methods

“…The exploration of enzyme-catalyzed reactions and their remarkable rate acceleration has been the subject of extensive computational research. − Among the methods employed, the hybrid quantum mechanical and molecular mechanical (QM/MM) approach stands out as the most widely adopted method. − In contrast to MM potentials, QM methods offer a more accurate description of chemical events involving the formation and cleavage of chemical bonds, as well as oxidation and reduction processes at the active site. However, representing the entire enzyme system at a QM level of theory is computationally prohibitive, especially when multiple protein and solvent configurations must be sampled to estimate free energies and other thermodynamic properties. , In the QM/MM method, regions of the system with chemical relevance are treated with electronic structure methods, such as ab initio (ai) or semiempirical (se) QM and density functional theories (DFTs), while the remaining regions are described with simplified MM force fields. − ,− Because of such effectiveness, this method is considered the most practical method for simulating enzymatic reactions and is often combined with various free energy simulation methods, including umbrella sampling, metadynamics, , and string methods, , to facilitate the investigation of enzyme reaction mechanisms. ,,,− …”

“…The exploration of enzyme-catalyzed reactions and their remarkable rate acceleration has been the subject of extensive computational research. 1 − 7 Among the methods employed, the hybrid quantum mechanical and molecular mechanical (QM/MM) approach stands out as the most widely adopted method. 8 − 11 In contrast to MM potentials, QM methods offer a more accurate description of chemical events involving the formation and cleavage of chemical bonds, as well as oxidation and reduction processes at the active site.…”