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Record W2011309585 · doi:10.1002/jcc.10176

A density functional study of the hydrogen‐bond network within the HIV‐1 protease catalytic site cleft

2003· article· en· W2011309585 on OpenAlexaff
Suzanne Sirois, Emil Proynov, Jean‐François Truchon, Chris Tsoukas, D. R. Salahub

Bibliographic record

VenueJournal of Computational Chemistry · 2003
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsMontreal General HospitalUniversité de MontréalCompute Canada
Fundersnot available
KeywordsProtonationChemistryActive siteCatalytic triadCatalysisProteaseHydrogen bondHIV-1 proteaseMonomerAcetic acidAmine gas treatingInteraction energyStereochemistryCrystallographyComputational chemistryEnzymeMoleculeOrganic chemistry

Abstract

fetched live from OpenAlex

The relative energy between two different protonation sites of the Asp25' catalytic site residue is computed and analyzed for various HIV-1 Protease/inhibitor complexes and compared to the wild-type structure. By comparing calculations of negatively charged fragments of gradually increasing size up to 105 atoms we show that correct modeling of the HIV-1 Protease active site requires much larger models than the commonly used acetic acid/acetate moieties. The energy difference between the two proposed protonation sites decreases as the size of the system increases and tends to converge only when the entire catalytic triad of both monomers is taken into account. The importance of the Gly27 backbone amine groups in the stabilization of the negative charge within the catalytic site cleft is revealed. Comparison of the wild-type structure with the structures from various Pr/drug complexes indicates that the HIV-1 protease has a particular catalytic site flexibility.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.011
GPT teacher head0.230
Teacher spread0.218 · 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 designSimulation or modeling
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

Citations8
Published2003
Admission routes1
Has abstractyes

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