Structure-based drug design targeting the SARS-CoV-2 virus has been greatly facilitated by available virus-related protein structures. However, there is an urgent need for effective, safe small-molecule drugs to control the spread of the virus and variants. While many efforts are devoted to searching for compounds that selectively target individual proteins, we investigated the potential interactions between eight proteins related to SARS-CoV-2 and more than 600 compounds from a traditional Chinese medicine which has proven effective at treating the viral infection. Our original ensemble docking and cooperative docking approaches, followed by a total of over 16-micorsecond molecular simulations, have identified at least 9 compounds that may generally bind to key SARS-CoV-2 proteins. Further, we found evidence that some of these compounds can simultaneously bind to the same target, potentially leading to cooperative inhibition to SARS-CoV-2 proteins like the Spike protein and the RNA-dependent RNA polymerase. These results not only present a useful computational methodology to systematically assess the anti-viral potential of small molecules, but also point out a new avenue to seek cooperative compounds toward cocktail therapeutics to target more SARS-CoV-2-related proteins.
- Award ID(s):
- 1912191
- NSF-PAR ID:
- 10412268
- Date Published:
- Journal Name:
- Molecules
- Volume:
- 27
- Issue:
- 21
- ISSN:
- 1420-3049
- Page Range / eLocation ID:
- 7336
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Objective: This study aimed to investigate natural compounds that could unitedly inhibit spikeglycoproteins 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 thatwould inhibit the viral entry disregard of occurred mutations.
Methods: An extensive analysis of relevant literature was conducted to compile a libraryof chemical compounds sourced from citrus essential oils. Ten homology models representingmutants of the Omicron variant were generated, including the latest 23F clade (EG.5.1),and the compound library was screened against them. Subsequently, employing comprehensivemolecular docking and molecular dynamics simulations, we successfully identifiedpromising compounds that exhibited sufficient binding efficacy towards the receptorbinding domains (RBDs) of the mutant viral strains. The scoring of ligands was based ontheir average potency against all models generated herein, in addition to a reference OmicronRBD structure. Furthermore, the toxicity profile of the highest-scoring compounds waspredicted.
Results: Out of ten built homology models, seven were successfully validated and showed to bereliable for In Silico studies. Three models of clades 22C, 22D, and 22E had major deviations intheir secondary structure and needed further refinement. Notably, through a 100 nanosecondmolecular dynamics simulation, terpinen-4-ol emerged as a potent inhibitor of the OmicronSARS-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 ahomology 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 opportunitiesfor further advancing the drug discovery process, offering novel avenues for the development ofmultifunctional, non-toxic natural medications.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/molecules27217336
