The discovery of Zika virus NS2B-NS3 inhibitors with antiviral activity via an integrated virtual screening approach
Bibliographic record
Abstract
With expanding recent outbreaks and a lack of treatment options, the Zika virus (ZIKV) poses a severe health concern. The availability of ZIKV NS2B-NS3 co-crystallized structures paved the way for rational drug discovery. A computer-aided structure-based approach was used to screen a diverse library of compounds against ZIKV NS2B-NS3 protease. The top hits were selected based on various binding free energy calculations followed by per-residue decomposition analysis. The selected hits were then evaluated for their biological potential with ZIKV protease inhibition assay and antiviral activity. Among 26 selected compounds, 8 compounds showed promising activity against ZIKV protease with a percentage inhibition of greater than 25 and 3 compounds displayed ∼50% at 10 µM, which indicates an enrichment rate of approximately 36% (threshold IC50 < 10 µM) in the ZIKV-NS2B-NS3 protease inhibition assay. Of these, only one compound (23) produced whole-cell anti-ZIKV activity, and the binding mode of 23 was extensively analyzed through long-run molecular dynamics simulations. The current study provides a promising starting point for the further development of novel compounds against ZIKV.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".