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Record W4414654265 · doi:10.1038/s41467-025-63802-7

Distal mutations enhance catalysis in designed enzymes by facilitating substrate binding and product release

2025· article· en· W4414654265 on OpenAlexafffund
Niayesh Zarifi, Pooja Asthana, Hiva Doustmohammadi, Cindy Klaus, Janet Sánchez, Serena E. Hunt, Rojo V. Rakotoharisoa, Sílvia Osuna, James S. Fraser, Roberto A. Chica

Bibliographic record

VenueNature Communications · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Molecular Research
Canadian institutionsUniversity of Ottawa
FundersBasic Energy SciencesLawrence Berkeley National LaboratoryNational Institute of General Medical SciencesBiological and Environmental ResearchNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du CanadaNational Institutes of HealthU.S. Department of Health and Human ServicesGovernment of CanadaCanada Foundation for InnovationU.S. Department of Energy
KeywordsSubstrate (aquarium)CatalysisActive siteMutantEnzymeCatalytic cycleProduct inhibitionMutationMolecular dynamics

Abstract

fetched live from OpenAlex

The role of amino-acid residues distant from an enzyme's active site in facilitating the complete catalytic cycle-including substrate binding, chemical transformation, and product release-remains poorly understood. Here, we investigate how distal mutations promote the catalytic cycle by engineering mutants of three de novo Kemp eliminases containing either active-site or distal mutations identified through directed evolution. Kinetic analyses, X-ray crystallography, and molecular dynamics simulations reveal that while active-site mutations create preorganized catalytic sites for efficient chemical transformation, distal mutations enhance catalysis by facilitating substrate binding and product release through tuning structural dynamics to widen the active-site entrance and reorganize surface loops. These distinct contributions work together to improve overall activity, demonstrating that a well-organized active site, though necessary, is not sufficient for optimal catalysis. Our findings reveal critical roles that distal residues play in shaping the catalytic cycle to enhance efficiency, yielding valuable insights for enzyme design.

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)0.001
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 score0.041
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.010
GPT teacher head0.318
Teacher spread0.308 · 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

Citations16
Published2025
Admission routes2
Has abstractyes

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