Optimization of Small Molecules That Sensitize HIV-1 Infected Cells to Antibody-Dependent Cellular Cytotoxicity
Bibliographic record
Abstract
With approximately 37 million people living with HIV worldwide and an estimated 2 million new infections reported each year, the need to derive novel strategies aimed at eradicating HIV-1 infection remains a critical worldwide challenge. One potential strategy would involve eliminating infected cells via antibody-dependent cellular cytotoxicity (ADCC). HIV-1 has evolved sophisticated mechanisms to conceal epitopes located in its envelope glycoprotein (Env) that are recognized by ADCC-mediating antibodies present in sera from HIV-1 infected individuals. Our aim is to circumvent this evasion via the development of small molecules that expose relevant anti-Env epitopes and sensitize HIV-1 infected cells to ADCC. Rapid elaboration of an initial screening hit using parallel synthesis and structure-based optimization has led to the development of potent small molecules that elicit this humoral response. Efforts to increase the ADCC activity of this class of small molecules with the aim of increasing their therapeutic potential was based on our recent cocrystal structures with gp120 core.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".