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Optimization of a Piperidine CD4-Mimetic Scaffold Sensitizing HIV-1 Infected Cells to Antibody-Dependent Cellular Cytotoxicity

2024· article· en· W4403812034 on OpenAlexafffund
Daniel Lee, Ling Niu, Shilei Ding, Huile Zhu, William D. Tolbert, Halima Medjahed, Guillaume Beaudoin-Bussières, Cameron F. Abrams, Andrés Finzi, Marzena Pazgier, Amos B. Smith

Bibliographic record

VenueACS Medicinal Chemistry Letters · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health ResearchNational Institutes of HealthCanada Foundation for InnovationFonds de Recherche du Québec - SantéUniversity of Pennsylvania
KeywordsCytotoxicityPiperidineScaffoldHuman immunodeficiency virus (HIV)AntibodyChemistryVirologyCell biologyCancer researchMedicineImmunologyBiologyBiochemistryIn vitroStereochemistryBiomedical engineering

Abstract

fetched live from OpenAlex

The ability of the HIV-1 accessory proteins Nef and Vpu to decrease CD4 protects infected cells from antibody-dependent cellular cytotoxicity (ADCC) by limiting the exposure of vulnerable epitopes to envelope glycoprotein (Env). Small-molecule CD4 mimetics (CD4mcs) based on piperidine scaffolds represent a new family of agents capable of sensitizing HIV-1-infected cells to ADCC by exposing CD4-induced (CD4i) epitopes on Env that are recognized by non-neutralizing antibodies which are abundant in plasma of people living with HIV. Here, we employed the combined methods of parallel synthesis, structure-based design, and optimization to generate a new line of piperidine-based CD4mcs, which sensitize HIV-1 infected cells to ADCC activity. The X-ray crystallographic study of the CD4mcs within the gp120 residues suggests that the positioning of the CD4mc inside the Phe43 cavity and synergistic contact of the CD4mc with the β 20–21 loop and the α 1 -helix lead to improved antiviral activity.

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)0.000
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 score0.010
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.246
Teacher spread0.238 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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