Novel Inhibitor Binding Site Discovery on HIV-1 Capsid N-Terminal Domain by NMR and X-ray Crystallography
Bibliographic record
Abstract
The HIV-1 capsid (CA) protein, a domain of Gag, which participates in formation of both the mature and immature capsid, represents a potential target for anti-viral drug development. Characterization of hits obtained via high-throughput screening of an in vitro capsid assembly assay led to multiple compounds having this potential. We previously presented the characterization of two inhibitor series that bind the N-terminal domain of the capsid (CA(NTD)), at a site located at the bottom of its helical bundle, often referred to as the CAP-1 binding site. In this work we characterize a novel series of benzimidazole hits. Initial optimization of this series led to compounds with improved in vitro assembly and anti-viral activity. Using NMR spectroscopy we found that this series binds to a unique site on CA(NTD), located at the apex of the helical bundle, well removed from previously characterized binding sites for CA inhibitors. 2D (1)H-(15)N HSQC and (19)F NMR showed that binding of the benzimidazoles to this distinct site does not affect the binding of either cyclophilin A (CypA) to the CypA-binding loop or a benzodiazepine-based CA assembly inhibitor to the CAP-1 site. Unfortunately, while compounds of this series achieved promising in vitro assembly and anti-viral effects, they also were found to be quite sensitive to a number of naturally occurring CA(NTD) polymorphisms observed among clinical isolates. Despite the negative impact of this finding for drug development, the discovery of multiple inhibitor binding sites on CA(NTD) shows that capsid assembly is much more complex than previously realized.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".