Five Years of Progress on Cyclin-Dependent Kinases and other Cellular Proteins as Potential Targets for Antiviral Drugs
Bibliographic record
Abstract
In 1997-1998, the pharmacological cyclin-dependent kinase (CDK) inhibitors (PCIs) were independently discovered to inhibit replication of human cytomegalovirus, herpes simplex virus type 1 and HIV-1. The results from small clinical trials against cancer were then suggesting that PCIs could be safe enough to be used clinically. It was thus hypothesized that PCIs could have the potential to be developed as novel antivirals targeting cellular proteins. Consequently, Antiviral Chemistry & Chemotherapy published in 2001 the first review on the potential of CDKs, and cellular proteins in general, as potential targets for antivirals. The viral functions inhibited by PCIs, or their cellular targets, were then just starting to be characterized. The antiviral spectrum of PCIs and their effects on viral disease were still mostly untested. Even their actual specificity was not yet completely characterized. In addition, cellular proteins were not accepted as valid targets for antivirals. Significant progress has been made in the last 5 years in understanding the antiviral activities of PCIs and the potential roles of cellular proteins in general as targets for antivirals. The first clinical trials of the antiviral activities of PCIs and other inhibitors of cellular protein kinases have now been scheduled. Herein, we review the progress made since the publication of the first review on PCIs as potential antiviral drugs and on CDKs, and cellular proteins in general, as potential targets for antiviral drugs. We also highlight the major issues that still need to be addressed before PCIs or other drugs targeting cellular proteins can be developed as clinical antivirals.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".