Pharmacological Cyclin-Dependent Kinase Inhibitors (PCIs) as Potential Antiviral Drugs
Bibliographic record
Abstract
Targeting viral proteins has led to many successful antivirals. However, such drugs have certain limitations. They rapidly select for resistance and tend to be active against only a few related viruses. And a significant time is required to identify and characterize targets encoded by new viral pathogens, a major concern in emerging diseases. As a result of such limitations, cellular proteins are now considered as potential targets for antivirals. Drugs targeting cellular proteins required for several viral functions are less likely to promptly select for drug-resistance and more likely to be active against a variety of unrelated viruses, which commonly required the same cellular proteins. They could also be promptly tested against any emerging viral pathogen, as even distantly related viruses commonly require the same cellular proteins. Cellular cyclin-dependent kinases (CDKs) are required for the replication of many viruses, and specific pharmacological CDK inhibitors (PCIs) are proving to have only limited side effects in clinical trials against cancer. In the last years, PCIs have been found to inhibit replication of several wild-type and drug-resistant viruses. Two PCIs, roscovitine and flavopiridol, were recently proven active in a mouse model of HIV-induced disease. Significant progress has been made toward understanding the antiviral mechanisms of PCIs. Roscovitine was found to act by a unique mechanism, which requires no specific viral proteins but is specific for viral genomes. Consequently, mutations in viral genes cannot easily overcome inhibition by PCIs; no PCI-resistant viral mutant has yet been identified. Owing to the strong antiviral potential shown in cultured cells, their apparently relative safety in animal models and clinical trials (against cancer), and their unique antiviral mechanisms, PCIs are tentatively scheduled to enter clinical trials as antivirals in the near future. Keywords: Antivirals, HSV, HIV, CDK, PCI, roscovitine, flavopiridol, transcription
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".