Structural Studies of the HIV-1 Integrase Protein: Compound Screening and Characterization of a DNA-Binding Inhibitor
Bibliographic record
Abstract
Understanding the HIV integrase protein and mechanisms of resistance to HIV integrase inhibitors is complicated by the lack of a full length HIV integrase crystal structure. Moreover, a lentiviral integrase structure with co-crystallised DNA has not been described. For these reasons, we have developed a structural method that utilizes free software to create quaternary HIV integrase homology models, based partially on available full-length prototype foamy virus integrase structures as well as several structures of truncated HIV integrase. We have tested the utility of these models in screening of small anti-integrase compounds using randomly selected molecules from the ZINC database as well as a well characterized IN:DNA binding inhibitor, FZ41, and a putative IN:DNA binding inhibitor, HDS1. Docking studies showed that the ZINC compounds that had the best binding energies bound at the IN:IN dimer interface and that the FZ41 and HDS1 compounds docked at approximately the same location in integrase, i.e. behind the DNA binding domain, although there is some overlap with the IN:IN dimer interface to which the ZINC compounds bind. Thus, we have revealed two possible locations in integrase that could potentially be targeted by allosteric integrase inhibitors, that are distinct from the binding sites of other allosteric molecules such as LEDGF inhibitors. Virological and biochemical studies confirmed that HDS1 and FZ41 share a similar activity profile and that both can inhibit each of integrase and reverse transcriptase activities. The inhibitory mechanism of HDS1 for HIV integrase seems to be at the DNA binding step and not at either of the strand transfer or 3' processing steps of the integrase reaction. Furthermore, HDS1 does not directly interact with DNA. The modeling and docking methodology described here will be useful for future screening of integrase inhibitors as well as for the generation of models for the study of integrase drug resistance.
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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) | 0.001 | 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 | 0.000 |
| 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".