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Record W2795002660 · doi:10.1021/acs.biochem.8b00274

Rational Engineering of Multiple Active Sites in an Ester Hydrolase

2018· article· en· W2795002660 on OpenAlexfundno aff
Gerard Santiago, Mónica Martínez‐Martínez, Sandra Alonso, Rafael Bargiela, Cristina Coscolín, Peter N. Golyshin, Vı́ctor Guallar, Manuel Ferrer

Bibliographic record

VenueBiochemistry · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsnot available
FundersEuropean Regional Development FundBiotechnology and Biological Sciences Research CouncilMinisterio de Economía y CompetitividadMinisterio de Asuntos Económicos y Transformación Digital, Gobierno de EspañaH2020 EnvironmentEuropean CommissionGenome Canada
KeywordsActive siteOxyanion holeCatalytic triadSerine hydrolaseHydrolaseBinding siteCatalysisChemistrySubstrate (aquarium)Ligand (biochemistry)SerineProtein engineeringEnzymeCombinatorial chemistryStereochemistryBiochemistryBiology

Abstract

fetched live from OpenAlex

Effects of altering the properties of an active site in an enzymatic homogeneous catalyst have been extensively reported. However, the possibility of increasing the number of such sites, as commonly done in heterogeneous catalytic materials, remains unexplored, particularly because those have to accommodate appropriate residues in specific configurations. This possibility was investigated by using a serine ester hydrolase as the target enzyme. By using the Protein Energy Landscape Exploration software, which maps ligand diffusion and binding, we found a potential binding pocket capable of holding an extra catalytic triad and oxyanion hole contacts. By introducing two mutations, this binding pocket became a catalytic site. Its substrate specificity, substrate preference, and catalytic activity were different from those of the native site of the wild type ester hydrolase and other hydrolases, due to the differences in the active site architecture. Converting the binding pocket into an extra catalytic active site was proven to be a successful approach to create a serine ester hydrolase with two functional reactive groups. Our results illustrate the accuracy and predictive nature of modern modeling techniques, opening novel catalytic opportunities coming from the presence of different catalytic environments in single enzymes.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.005
GPT teacher head0.226
Teacher spread0.221 · 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

Citations62
Published2018
Admission routes1
Has abstractyes

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