MétaCan
Menu
Back to cohort
Record W2156954694 · doi:10.2147/dddt.s89338

A novel small-molecule inhibitor of HIV-1 entry

2015· article· en· W2156954694 on OpenAlexfundno aff
Erik de Leeuw, Alonso Heredia, Olga Latinovic, Florent Barbault

Bibliographic record

VenueDrug Design Development and Therapy · 2015
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsnot available
FundersUniversity of California, San FranciscoMcGill University
KeywordsHuman immunodeficiency virus (HIV)Small moleculeDrugDrug resistanceAntiretroviral therapyANTIRETROVIRAL AGENTSPharmacologyLentivirusMedicineVirologyChemistryViral loadBiologyViral diseaseBiochemistryMicrobiology

Abstract

fetched live from OpenAlex

BACKGROUND: Antiretroviral therapy has transformed HIV-1 infection into a managed condition with near-normal life expectancy. However, a significant number of patients remain with limited therapeutic options due to HIV-1 resistance, side effects, or drug costs. Further, it is likely that current drugs will not retain efficacy, due to risks of side effects and transmitted resistance. RESULTS: We describe compound 5660386 (3-ethyl-2-[3-(1,3,3-trimethyl-1,3-dihydro-2H-indol-2-ylidene)-1-propen-1-yl]-1,3-benzothiazol-3-ium) as a novel inhibitor of HIV-1 entry. Compound 5660386 inhibits HIV-1 entry in cell lines and primary cells, binds to HIV-1 envelope protein, and inhibits the interaction of GP120 to CD4. Further, compound 5660386 showed a unique and broad-range activity against primary HIV-1 isolates from different subtypes and geographical areas. CONCLUSION: Development of small-molecule entry inhibitors of HIV-1 such as 5660386 may lead to novel classes of anti-HIV-1 therapeutics. These inhibitors may be particularly effective against viruses resistant to current antiretroviral drugs and could have potential applications in both treatment and prevention.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.050
GPT teacher head0.253
Teacher spread0.203 · 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

Citations10
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueDrug Design Development and TherapySame topicHIV/AIDS drug development and treatmentFrench-language works237,207