Background:SARS-CoV-2's remarkable capacity for genetic mutation enables it to
swiftly adapt to environmental changes, influencing critical attributes, such as antigenicity and
transmissibility. Thus, multi-target inhibitors capable of effectively combating various viral mutants
concurrently are of great interest.Objective:This study aimed to investigate natural compounds that could unitedly inhibit spike
glycoproteins of various Omicron mutants. Implementation of various in silico approaches allows
us to scan a library of compounds against a variety of mutants in order to find the ones that
would inhibit the viral entry disregard of occurred mutations.Methods:An extensive analysis of relevant literature was conducted to compile a library
of chemical compounds sourced from citrus essential oils. Ten homology models representing
mutants of the Omicron variant were generated, including the latest 23F clade (EG.5.1),
and the compound library was screened against them. Subsequently, employing comprehensive
molecular docking and molecular dynamics simulations, we successfully identified
promising compounds that exhibited sufficient binding efficacy towards the receptor
binding domains (RBDs) of the mutant viral strains. The scoring of ligands was based on
their average potency against all models generated herein, in addition to a reference Omicron
RBD structure. Furthermore, the toxicity profile of the highest-scoring compounds was
predicted.Results:Out of ten built homology models, seven were successfully validated and showed to be
reliable for in silico studies. Three models of clades 22C, 22D, and 22E had major deviations in
their secondary structure and needed further refinement. Notably, through a 100 nanosecond
molecular dynamics simulation, terpinen-4-ol emerged as a potent inhibitor of the Omicron
SARS-CoV-2 RBD from the 21K clade (BA.1); however, it did not show high stability in complexes
with other mutants. This suggests the need for the utilization of a larger library of chemical
compounds as potential inhibitors.Conclusion:The outcomes of this investigation hold significant potential for the utilization of a
homology modeling approach for the prediction of RBD’s secondary structure based on its sequence
when the 3D structure of a mutated protein is not available. This opens the opportunities
for further advancing the drug discovery process, offering novel avenues for the development of
multifunctional, non-toxic natural medications.