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Record W7132901585

Progress Towards the De Novo Design of a Novel Protein Secondary Structure

2023· dissertation· W7132901585 on OpenAlexaff
Hankyu Lee

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsToronto Rehabilitation Institute
Fundersnot available
KeywordsProtein secondary structureSequence (biology)Protein structurePeptide sequenceProtein designSpiral (railway)Nucleic acid secondary structureSecondary flow
DOInot available

Abstract

fetched live from OpenAlex

Nature has sampled a very small fraction of the protein sequence space through evolutionary processes. The structures that these sequences adopt are relegated to permutations of just a few secondary structures. In fact, there are only two types of ‘regular’ secondary structures – the α-helix and β-sheet, although other types of non-regular secondary structures and random coils do exist. We hypothesized that novel secondary structures may exist in the unsampled space. To test this, we conceived of a spiral shaped secondary structure element not seen in nature. We created in-silico structural models and found amino acid sequences best predicted to stabilize the models. We synthesized designs and used CD and NMR spectroscopy to validate that our novel spiral secondary structure self assembles with an RMSD of ~4.5Å to the in-silico design. This study offers the first glimpse into a potentially vast world of undiscovered secondary structures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.309
Teacher spread0.291 · 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 source (direct Gemma or distilled Codex), 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
Published2023
Admission routes1
Has abstractyes

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