Discovery and Characterization of 7,8-Dihydropyrido[4,3-d]pyrimidines as SARS-CoV-2 Entry Inhibitors
Bibliographic record
Abstract
Background/Objectives: We have established a robust, cell-based high-throughput screening platform capable of identifying SARS-CoV-2 entry inhibitors within a BSL-2 facility. Methods: Using a curated compound library, we conducted a screening campaign that led to the discovery of potent viral entry inhibitors active in both pseudoviral and infectious SARS-CoV-2 inhibition assays. Results: Among those, Hit-1 exhibited submicromolar antiviral activity across all tested SARS-CoV-2 strains, including the highly transmissible Omicron subvariants. Biophysical binding assays confirmed that Hit-1 and related compounds directly engage the prefusion-stabilized SARS-CoV-2 spike proteins of both authentic WA1/2020 and Omicron viral strains. To elucidate potential binding orientations and interactions of the hit compounds with the SARS-CoV-2 spike protein, molecular docking studies were performed targeting two putative binding sites. Conclusions: Preliminary structure–activity relationship studies identified a promising subset of drug-like 7,8-dihydropyrido[4,3-d]pyrimidine-based inhibitors with potential for further development as novel therapeutic agents aimed at blocking viral entry and thereby preventing or mitigating SARS-CoV-2 infection. Among these, compound 13 stands out due to its superior in vitro potency and favorable pharmacokinetic properties, positioning it as a strong candidate for in vivo efficacy evaluation.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".