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Record W4309089057 · doi:10.1139/cjc-2022-0140

A molecular dynamics simulation investigation on the effects of Ser/Cys exchange in the Ser–<i>cis</i>Ser–Lys catalytic triad of malonamidase E2

2022· article· en· W4309089057 on OpenAlexaffvenue
Anupom Roy, James W. Gauld

Bibliographic record

VenueCanadian Journal of Chemistry · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Molecular Research
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCatalytic triadTriad (sociology)ChemistryHydrogen bondStereochemistryMolecular dynamicsCatalysisResidue (chemistry)CrystallographyActive siteMoleculeBiochemistryComputational chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The enzyme malonamidase E2 catalytically hydrolyzes malonamate (MLA) into malonate and ammonia. Its active site contains an uncommon Ser– cisSer–Lys catalytic triad that is critical to its functioning. Mutations of the residues in this triad can not only provide insight into its key features but also potentially identify how it may be influenced or adapted, i.e., decreased or increased. In this study, the effects of single and double Ser/Cys exchanges on the wild-type Ser155– cisSer131–Lys62 catalytic triad (i.e., Cys155– cisSer131–Lys62 (S155C), Ser155– cisCys131–Lys62 (S131C), and Cys155– cisCys131–Lys62 (S131C/S155C)) were examined. In particular, the dynamics and stability of the resulting substituted triads were examined along with their inter-triad residue hydrogen bonding interactions as well as those with other nearby residues and the MLA substrate. The present results suggest that some mutations are more impactful than others. Indeed, mutation of cisSer131 to cisCys131 disrupts the triad and causes inconsistent hydrogen bonding interactions among the triad residues (i.e., Ser155, Cys131, and Lys62). In contrast, in the double mutant Cys155– cisCys131–Lys62, the triad's residues appear to exhibit greater conformation stability with more consistent hydrogen bond interactions, though not necessarily as in the wild type.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.228
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes2
Has abstractyes

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