tetano
Editor, Senior Moderator
J Mol Model
. 2021 Feb 28;27(3):97.
doi: 10.1007/s00894-021-04703-6.
Structure-activity relationship (SAR) and molecular dynamics study of withaferin-A fragment derivatives as potential therapeutic lead against main protease (M [SUP]pro[/SUP]) of SARS-CoV-2
Arabinda Ghosh[SUP] 1 [/SUP], Monoswi Chakraborty[SUP] 2 [/SUP], Anshuman Chandra[SUP] 3 [/SUP], Mohamad Parvez Alam[SUP] 4 [/SUP]
Affiliations
Abstract
The spread of novel coronavirus SARS-CoV-2 has directed to a state of an unprecedented global pandemic. Many synthetic compounds and FDA-approved drugs have been significantly inhibitory against the virus, but no SARS-CoV-2 solution has been identified. However, small molecule fragment-based derivatives of potent phytocompounds may serve as promising inhibitors against SARS-CoV-2. In the pursuit of exploring novel SARS-CoV-2 inhibitors, we generated small molecule fragment derivatives from potent phytocompounds using neural networking and machine learning-based tools, which can cover unexplored regions of the chemical space that still retain lead-like properties. Out of 300 derivative molecules from withaferin-A, hesperidin, and baicalin, 30 were screened out with synthetic accessibility scores > 4 having the best ADME properties. The withaferin-A derivative molecules 61 and 64 exhibited a significant binding affinity of - 7.84 kcal/mol and - 7.94 kcal/mol. The docking study reveals that withaferin-A mol 61 forms 5 polar H-bonds with the M[SUP]pro[/SUP] where amino acids involved are GLU166, THR190, CYS145, MET165, and GLN152 and upon QSAR analysis showed a minimal predicted IC50 value of 7762.47 nM. Furthermore, the in silico cytotoxicity predictions, pharmacophore modeling, and molecular dynamics simulation studies have resulted in predicting the highly potent small molecule derivative from withaferin-A (phytocompound from Withania somnifera) to be the potential inhibitor of SARS-CoV 2 protease (M[SUP]pro[/SUP]) and a promising future lead candidate against COVID-19. The rationale of choosing withaferin-A from Withania somnifera (Ashwagandha) was propelled by the innumerous applications of Ashwagandha for the treatment of various antiviral diseases, common cold, and fever since time immemorial. Graphical abstract.
Keywords: COVID-19; DNN; Machine learning; Mpro inhibitor; QSAR; SARS-CoV-2; Small molecule derivative; Withania somnifera.
. 2021 Feb 28;27(3):97.
doi: 10.1007/s00894-021-04703-6.
Structure-activity relationship (SAR) and molecular dynamics study of withaferin-A fragment derivatives as potential therapeutic lead against main protease (M [SUP]pro[/SUP]) of SARS-CoV-2
Arabinda Ghosh[SUP] 1 [/SUP], Monoswi Chakraborty[SUP] 2 [/SUP], Anshuman Chandra[SUP] 3 [/SUP], Mohamad Parvez Alam[SUP] 4 [/SUP]
Affiliations
- PMID: 33641023
- DOI: 10.1007/s00894-021-04703-6
Abstract
The spread of novel coronavirus SARS-CoV-2 has directed to a state of an unprecedented global pandemic. Many synthetic compounds and FDA-approved drugs have been significantly inhibitory against the virus, but no SARS-CoV-2 solution has been identified. However, small molecule fragment-based derivatives of potent phytocompounds may serve as promising inhibitors against SARS-CoV-2. In the pursuit of exploring novel SARS-CoV-2 inhibitors, we generated small molecule fragment derivatives from potent phytocompounds using neural networking and machine learning-based tools, which can cover unexplored regions of the chemical space that still retain lead-like properties. Out of 300 derivative molecules from withaferin-A, hesperidin, and baicalin, 30 were screened out with synthetic accessibility scores > 4 having the best ADME properties. The withaferin-A derivative molecules 61 and 64 exhibited a significant binding affinity of - 7.84 kcal/mol and - 7.94 kcal/mol. The docking study reveals that withaferin-A mol 61 forms 5 polar H-bonds with the M[SUP]pro[/SUP] where amino acids involved are GLU166, THR190, CYS145, MET165, and GLN152 and upon QSAR analysis showed a minimal predicted IC50 value of 7762.47 nM. Furthermore, the in silico cytotoxicity predictions, pharmacophore modeling, and molecular dynamics simulation studies have resulted in predicting the highly potent small molecule derivative from withaferin-A (phytocompound from Withania somnifera) to be the potential inhibitor of SARS-CoV 2 protease (M[SUP]pro[/SUP]) and a promising future lead candidate against COVID-19. The rationale of choosing withaferin-A from Withania somnifera (Ashwagandha) was propelled by the innumerous applications of Ashwagandha for the treatment of various antiviral diseases, common cold, and fever since time immemorial. Graphical abstract.
Keywords: COVID-19; DNN; Machine learning; Mpro inhibitor; QSAR; SARS-CoV-2; Small molecule derivative; Withania somnifera.