2020
DOI: 10.26434/chemrxiv.12756245
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Towards a cheminformatic design for quantum mechanical enzyme models: the case of catechol-O-methyltransferase

Abstract: The efficiency, accuracy, and replicability of enzyme simulations is often hampered by ad hoc model design. To address this problem, we have developed the Residue Interaction Network ResidUe Selector (RINRUS) toolkit. RINRUS utilizes residue contact networks to automate construction of rational quantum mechanical cluster models. This work examines this problem by computing the reaction kinetics and thermodynamics for 508 models of the active site of catechol-o-methyltransferase, an enzyme which catalyzes the m… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
2
0

Year Published

2020
2020
2020
2020

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 41 publications
0
2
0
Order By: Relevance
“…Recent advances [96][97][98][99][100][101][102] in hardware and algorithms have made large-scale QM treatments (e.g., with hybrid density functional theory) tractable for the study of proteins 96, 103 . This has motivated increasingly large-scale QM region treatments in QM/MM models of enzyme catalysis 35, [104][105][106][107][108][109][110][111][112][113][114][115][116][117][118][119] , which have revealed unexpectedly large dependence of properties such as the favorability of proton or charge transfer 106 , electric fields 35,75 , excitation energies [114][115]120 , bond critical points 117 and partial charges 116 on the selection of the QM region. These observations have motivated renewed interest in systematic methods for atom-economical QM region selection 76,[121][122][123] for QM/MM properties obtained from single point energies and optimizations, but the application of these methods is still in its infancy in dynamics simulation 124 . Recently, we carried out 124 large-scale free energy simulations with ca.…”
Section: Introductionmentioning
confidence: 99%
“…Recent advances [96][97][98][99][100][101][102] in hardware and algorithms have made large-scale QM treatments (e.g., with hybrid density functional theory) tractable for the study of proteins 96, 103 . This has motivated increasingly large-scale QM region treatments in QM/MM models of enzyme catalysis 35, [104][105][106][107][108][109][110][111][112][113][114][115][116][117][118][119] , which have revealed unexpectedly large dependence of properties such as the favorability of proton or charge transfer 106 , electric fields 35,75 , excitation energies [114][115]120 , bond critical points 117 and partial charges 116 on the selection of the QM region. These observations have motivated renewed interest in systematic methods for atom-economical QM region selection 76,[121][122][123] for QM/MM properties obtained from single point energies and optimizations, but the application of these methods is still in its infancy in dynamics simulation 124 . Recently, we carried out 124 large-scale free energy simulations with ca.…”
Section: Introductionmentioning
confidence: 99%
“…This has motivated increasingly large-scale QM region treatments in QM/MM models of enzyme catalysis 35, [104][105][106][107][108][109][110][111][112][113][114][115][116][117][118][119] , which have revealed unexpectedly large dependence of properties such as the favorability of proton or charge transfer 106 , electric fields 35,75 , excitation energies [114][115]120 , bond critical points 117 and partial charges 116 on the selection of the QM region. These observations have motivated renewed interest in systematic methods for atom-economical QM region selection 76,[121][122][123] for QM/MM properties obtained from single point energies and optimizations, but the application of these methods is still in its infancy in dynamics simulation 124 . Recently, we carried out 124 large-scale free energy simulations with ca.…”
Section: Introductionmentioning
confidence: 99%