Monitoring Binding of HIV‐1 Capsid Assembly Inhibitors Using <sup>19</sup>F Ligand‐and <sup>15</sup>N Protein‐Based NMR and X‐ray Crystallography: Early Hit Validation of a Benzodiazepine Series
Bibliographic record
Abstract
The emergence of resistance to existing classes of antiretroviral drugs underlines the need to find novel human immunodeficiency virus (HIV)-1 targets for drug discovery. The viral capsid protein (CA) represents one such potential target. Recently, a series of benzodiazepine inhibitors was identified via high-throughput screening using an in vitro capsid assembly assay (CAA). Here, we demonstrate how a combination of NMR and X-ray co-crystallography allowed for the rapid characterization of the early hits from this inhibitor series. Ligand-based (19)F NMR was used to confirm inhibitor binding specificity and reversibility as well as to identify the N-terminal domain of the capsid (CA(NTD)) as its molecular target. Protein-based NMR ((1)H and (15)N chemical shift perturbation analysis) identified key residues within the CA(NTD) involved in inhibitor binding, while X-ray co-crystallography confirmed the inhibitor binding site and its binding mode. Based on these results, two conformationally restricted cyclic inhibitors were designed to further validate the possible binding modes. These studies were crucial to early hit confirmation and subsequent lead optimization.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".