Unique Thermodynamic Response of Tipranavir to Human Immunodeficiency Virus Type 1 Protease Drug Resistance Mutations
Bibliographic record
Abstract
Drug resistance is a major problem affecting the clinical efficacy of antiretroviral agents, including protease inhibitors, in the treatment of infection with human immunodeficiency virus type 1 (HIV-1)/AIDS. Consequently, the elucidation of the mechanisms by which HIV-1 protease inhibitors maintain antiviral activity in the presence of mutations is critical to the development of superior inhibitors. Tipranavir, a nonpeptidic HIV-1 protease inhibitor, has been recently approved for the treatment of HIV infection. Tipranavir inhibits wild-type protease with high potency (K(i) = 19 pM) and demonstrates durable efficacy in the treatment of patients infected with HIV-1 strains containing multiple common mutations associated with resistance. The high potency of tipranavir results from a very large favorable entropy change (-TDeltaS = -14.6 kcal/mol) combined with a favorable, albeit small, enthalpy change (DeltaH = -0.7 kcal/mol, 25 degrees C). Characterization of tipranavir binding to wild-type protease, active site mutants I50V and V82F/I84V, the multidrug-resistant mutant L10I/L33I/M46I/I54V/L63I/V82A/I84V/L90M, and the tipranavir in vitro-selected mutant I13V/V32L/L33F/K45I/V82L/I84V was performed by isothermal titration calorimetry and crystallography. Thermodynamically, the good response of tipranavir arises from a unique behavior: it compensates for entropic losses by actual enthalpic gains or by sustaining minimal enthalpic losses when facing the mutants. The net result is a small loss in binding affinity. Structurally, tipranavir establishes a very strong hydrogen bond network with invariant regions of the protease, which is maintained with the mutants, including catalytic Asp25 and the backbone of Asp29, Asp30, Gly48 and Ile50. Moreover, tipranavir forms hydrogen bonds directly to Ile50, while all other inhibitors do so by being mediated by a water molecule.
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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 | 0.001 |
| 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) | 0.002 | 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".