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Chemically Modified “Polar Patch” Mutants of Subtilisin in Peptide Synthesis with Remarkably Broad Substrate Acceptance: Designing Combinatorial Biocatalysts

2002· article· en· W2157136966 on OpenAlexafffund
Kazutsugu Matsumoto, Benjamin G. Davis, J. Bryan Jones

Bibliographic record

VenueChemistry - A European Journal · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical Synthesis and Analysis
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of OxfordAmerican Academy of Periodontology Foundation
KeywordsSubtilisinChemistryYield (engineering)StereochemistrySubstrate (aquarium)Peptide synthesisAmino acidMutagenesisSerine proteasePeptideProtein engineeringSite-directed mutagenesisEnzymeCombinatorial chemistryProteaseMutantOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

A significant enhancement of the applicability of the serine protease subtilisin Bacillus lentus (SBL) in peptide synthesis was achieved by using the strategy of combined site-directed mutagenesis and chemical modification to create chemically modified mutant (CMM) enzymes. The introduction of polar and/or homochiral auxiliary substituents, such as X=oxazolidinones, alkylammonium groups, and carbohydrates at position 166 at the base of the primary specificity S(1) pocket created SBL CMMs S166C-S-X with strikingly broad structural substrate specificities. These CMMs are capable of catalyzing the coupling reactions of not only L-amino acid esters but also D-amino acid esters as acyl donors with glycinamide to give the corresponding dipeptides in good yields. These powerful enzymes are also applicable to the coupling of L-amino acid acyl donors with alpha-branched acyl acceptor, L-alaninamide. Typical increases in isolated yields of dipeptides of 60-80 % over SBL-WT (e.g. 0 % yield of Z-D-Glu-GlyNH(2) using SBL-WT-->74 % using S166C-S-(CH(2))(2) NMe(3) (+)) demonstrate the remarkable synthetic utility of this "polar patch" strategy. Such wide-ranging systems displaying broadened and therefore similarly high, balanced yields of products (e.g. 91 % Z-L-Ala-GlyNH(2) and 86 % yield of Z-D-Ala-GlyNH(2) using S166C-S-(3R,4S)-indenooxazolidinone) may now allow the use of biocatalysts in parallel library synthesis.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.012
GPT teacher head0.202
Teacher spread0.189 · 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.

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

Citations28
Published2002
Admission routes2
Has abstractyes

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