Covalent and Non-Covalent Binding Free Energy Calculations for Peptidomimetic Inhibitors of SARS-CoV-2 Main Protease
Bibliographic record
Abstract
COVID-19, the disease caused by the newly discovered coronavirus — SARS-CoV-2, has created global health, social, and economic crisis. At the time of writing (November 12, 2020), there are over 50 million confirmed cases and more than 1 million reported deaths due to COVID-19. Currently, there are no approved vaccines, and recently Veklury (remdesivir) was approved for the treatment of COVID-19 requiring hospitalization. The main protease (M<sup>pro</sup>) of the virus is an attractive target for the development of effective antiviral therapeutics because it is required for proteolytic cleavage of viral polyproteins. Furthermore, the M<sup>pro</sup> has no human homologues, so drugs designed to bind to this target directly have less risk for off-target reactivity. Recently, several high-resolution crystallographic structures of the M<sup>pro</sup> in complex with inhibitors have been determined — to guide drug development and to spur efforts in structure-based drug design. One of the primary objectives of modern structure-based drug design is the accurate prediction of receptor-ligand binding affinities for rational drug design and discovery. Here, we perform rigorous alchemical absolute binding free energy calculations and QM/MM calculations to give insight into the total binding energy of two recently crystallized inhibitors of SARS-CoV-2 M<sup>pro</sup>, namely, N3 and α-ketoamide 13b. The total binding energy consists of both covalent and non-covalent binding components since both compounds are covalent inhibitors of the M<sup>pro</sup>. Our results indicate that the covalent and non-covalent binding free energy contributions of both inhibitors to the M<sup>pro</sup> target differ significantly. The N3 inhibitor has more favourable non-covalent interactions, particularly hydrogen bonding, in the binding site of the M<sup>pro</sup> than the α-ketoamide inhibitor. But the Gibbs energy of reaction for the M<sup>pro</sup>–α-ketoamide covalent adduct is greater than the Gibbs reaction energy for the M<sup>pro</sup>–N3 covalent adduct. These differences in the covalent and non-covalent binding free energy contributions for both inhibitors could be a plausible explanation for their in vitro differences in antiviral activity. Our findings highlight the importance of both covalent and non-covalent binding free energy contributions to the absolute binding affinity of a covalent inhibitor towards its target.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| 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".