In silico study of SARS‐CoV‐2 spike protein RBD and human ACE‐2 affinity dynamics across variants and Omicron subvariants
Bibliographic record
Abstract
The coronavirus disease 2019 virus outbreak continues worldwide, with many variants emerging, some of which are considered variants of concern (VOCs). The WHO designated Omicron as a VOC and assigned it under variant B.1.1.529. Here, we used computational studies to examine the VOCs, including Omicron subvariants, and one variant of interest. Here we found that the binding affinity of human receptor angiotensin-converting enzyme 2 (hACE2) and receptor-binding domain (RBDs) increased in the order of wild type (Wuhan-strain) < Beta < Alpha < OmicronBA.5 < Gamma < Delta < Omicron BA.2.75 < BA.1 < BA.3 < BA.2. Interactions between docked complexes revealed that the RBD residue positions like 452, 478, 493, 498, 501, and 505 are crucial in creating strong interactions with hACE2. Omicron BA.2 shows the highest binding capacity to the hACE2 receptor among all the mutant complexes. The BA.5's L452R, F486V, and T478K mutation significantly impact the interaction network in the BA.5 RBD-hACE2 interface. Here for the first time, we report the His505, an active residue on the RBD forming a salt bridge in the BA.2, leading to increased mutation stability. When the active RBD residues are mutated, binding affinity and intermolecular interactions increase across all mutant complexes. By examining the differences in different variants, this study may provide a solid foundation for structure-based drug design for newly emerging variants.
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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 | 0.005 | 0.001 |
| 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 | 0.001 | 0.002 |
| 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".