Mechanistic investigation of SARS-CoV-2 Omicron variant spike mutants via full quantum mechanical modeling

Ab initioquantum mechanical models can characterize and predict intermolecular binding, but only recently have models including more than a few hundred atoms gained traction. Here, we simulate ∼13,000 atoms to predict and characterize binding of SARS-CoV-2 spike variants to the human receptor ACE2 (hACE2). We compare four spike variants in our analysis: Wuhan, Omicron, and two Omicron-based variants. To assess binding, we mechanistically characterize the energetic contribution of each amino acid involved, and predict the effect of select single point mutations. We validate our computational predictions experimentally by comparing binding efficacy of spike variants to cells expressing hACE2. We argue that this computational model, QM-CR, can identify mutations critical for intermolecular interactions and inform the engineering of high-specificity interactors.