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Record W3046516409 · doi:10.1039/d0sc03060k

Increasing protein stability by engineering the n → π* interaction at the β-turn

2020· article· en· W3046516409 on OpenAlexfundno aff
Bhavesh Khatri, Puja Majumder, Jayashree Nagesh, Aravind Penmatsa, Jayanta Chatterjee

Bibliographic record

VenueChemical Science · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsnot available
FundersScience and Engineering Research BoardThe Wellcome Trust DBT India AllianceMinistry of Education, IndiaCompute CanadaDepartment of Science and Technology, Ministry of Science and Technology, IndiaDepartment of Biotechnology, Ministry of Science and Technology, IndiaWellcome TrustIndian Institute of Science
KeywordsStability (learning theory)Turn (biochemistry)Amino acid residueProtein engineeringChemistryAmino acidProtein structureStructural stabilityBiophysicsComputer sciencePeptide sequenceEngineeringBiochemistryBiologyStructural engineeringMachine learning

Abstract

fetched live from OpenAlex

torsion angle. Our results also suggest that amino acid side-chain identity and its rotameric conformation play an important and decisive role in dictating the strength of an n → π* interaction.

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 score0.009
Threshold uncertainty score0.150

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 head0.007
GPT teacher head0.219
Teacher spread0.212 · 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

Citations45
Published2020
Admission routes1
Has abstractyes

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