QM and QM/MM Methods Compared

Borowski, Tomasz; Quesne, Matthew G.; Szaleniec, Maciej

doi:10.1016/bs.apcsb.2015.06.005

Cited by 12 publications

(2 citation statements)

References 113 publications

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“…Although DFT‐based methods generally represent the best trade‐off between reliability and computational cost for describing metals, [112] their accuracy may be limited for metals with both high‐ and low‐spin states, [113–114] although such systems are uncommon in the pathways of most metalloproteins [113] . Some metalloproteins have also been found to be particularly sensitive to the embedding scheme (the QM and MM connection region), [115] and QM/MM calculations often cannot cover the long timescales required for optimization of the metal coordination spheres [112,116] …”

Section: Methods In Computational Enzyme Engineeringmentioning

confidence: 99%

Curse and Blessing of Non‐Proteinogenic Parts in Computational Enzyme Engineering

Korbeld

Fürst

2023

ChemBioChem

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Enzyme engineering aims to improve or install a new function in biocatalysts for applications ranging from chemical synthesis to biomedicine. For decades, computational techniques have been developed to predict the effect of protein changes and design new enzymes. However, these techniques may have been optimized to deal with proteins composed of the standard amino acid alphabet, while the function of many enzymes relies on non‐proteogenic parts like cofactors, nucleic acids, and post‐translational modifications. Enzyme systems containing such molecules might be handled or modeled improperly by computational tools, and thus be unsuitable, or require additional tweaking, parameterization, or preparation. In this review, we give an overview of common and recent tools and workflows available to computational enzyme engineers. We highlight the various pitfalls that come with including non‐proteogenic compounds in computations and outline potential ways to address common issues. Finally, we showcase successful examples from the literature that computationally engineered such enzymes.

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Section: Methods In Computational Enzyme Engineeringmentioning

confidence: 99%

Curse and Blessing of Non‐Proteinogenic Parts in Computational Enzyme Engineering

Korbeld

Fürst

2023

ChemBioChem

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“…But compared to molecular dynamics simulations, only part of the protein can be simulated efficiently and thus this general approach is applied here to only simulate around the first coordination shell around the metal coordination center [31]. The QM approach undertaken here is beneficial for the close examination of the local coordination chemistry, however, it largely misses the other protein-protein interactions important for ligand selectivity as well as complex stability, thus the scope of this work is limited to the events around the coordination center, and a more sophisticated approach using the QM/ MM methods has to be utilized to understand the behavior of the MMPs systematically [32].…”

Section: Plos Onementioning

confidence: 99%

Computational analysis of the metal selectivity of matrix metalloproteinase 8

Long

2020

PLoS ONE

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Matrix metalloproteinase (MMP) is a class of metalloenzyme that cleaves peptide bonds in extracellular matrices. Their functions are important in both health and disease of animals. Here using quantum mechanics simulations of the MMP8 protein, the coordination chemistry of different metal cofactors is examined. Structural comparisons reveal that Jhan-Teller effects induced by Cu(II) coordination distorts the wild-type MMP8 active site corresponding to a significant reduction in activity observed in previous experiments. In addition, further analysis suggests that a histidine to glutamine mutation at residue number 197 can potentially allow the MMP8 protein to utilize Cu(II) in reactions. Simulations also demonstrates the requirement of a conformational change in the ligand before enzymatic cleavage. The insights provided here will assist future protein engineering efforts utilizing the MMP8 protein.

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The Quest for Accurate Theoretical Models of Metalloenzymes: An Aid to Experiment

Quesne

Visser

2019

Transition Metals in Coordination Environments

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QM and QM/MM Methods Compared

Cited by 12 publications

References 113 publications

Curse and Blessing of Non‐Proteinogenic Parts in Computational Enzyme Engineering

Curse and Blessing of Non‐Proteinogenic Parts in Computational Enzyme Engineering

Computational analysis of the metal selectivity of matrix metalloproteinase 8

The Quest for Accurate Theoretical Models of Metalloenzymes: An Aid to Experiment

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