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Abstract The hydrolysis of extremely stable peptide and phosphoester bonds by metalloenzymes is of great interest in biotechnology and industry. However, due to various shortcomings only a handful of these enzymes have been used for industrial applications. Therefore, in the last two decades intensive scientific efforts have been made in rational development of small molecules to imitate the activities of natural enzymes. Despite these efforts, their currently available synthetic analogues are inferior in terms of selectivity, catalytic rate, and turnover and the designing of efficient artificial metalloenzymes remains a distant goal. This is a challenging area of research that necessitates a rigorous integration between experiments and theory. The realization of this goal requires knowledge of the catalytic activities of both enzymes and their existing analogues and an effective fusion of that knowledge. This article reviews several studies in which a plethora of computational techniques have been successfully employed to investigate the functioning of two chemically promiscuous mono‐ and binuclear metalloenzymes (insulin degrading enzyme and glycerophosphodiesterase) and two synthetic analogues. These studies will help us derive fundamental principles of peptide and phosphoester hydrolysis and pave the way to design efficient small molecule catalysts for these reactions. This article is categorized under:Structure and Mechanism > Reaction Mechanisms and Catalysis
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Transition Path Sampling Study of Engineered Enzymes That Catalyze the Morita–Baylis–Hillman Reaction: Why Is Enzyme Design so Difficult?
It is hoped that artificial enzymes designed in laboratories can be efficient alternatives to chemical catalysts that have been used to synthesize organic molecules. However, the design of artificial enzymes is challenging and requires a detailed molecular-level analysis to understand the mechanism they promote in order to design efficient variants. In this study, we computationally investigate the mechanism of proficient Morita-Baylis-Hillman enzymes developed using a combination of computational design and directed evolution. The powerful transition path sampling method coupled with in-depth post-processing analysis has been successfully used to elucidate the different chemical pathways, transition states, protein dynamics, and free energy barriers of reactions catalyzed by such laboratory-optimized enzymes. This research provides an explanation for how different chemical modifications in an enzyme affect its catalytic activity in ways that are not predictable by static design algorithms.
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- Award ID(s):
- 2244981
- PAR ID:
- 10540726
- Editor(s):
- Merz, K
- Publisher / Repository:
- American Chemical Society
- Date Published:
- Journal Name:
- Journal of Chemical Information and Modeling
- Volume:
- 64
- Issue:
- 6
- ISSN:
- 1549-9596
- Page Range / eLocation ID:
- 2101 to 2111
- Subject(s) / Keyword(s):
- directed evolution, transition path sampling, free energy, mechanism
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1021/acs.jcim.4c00045
