In silico and in vitro assays reveal potential inhibitors against 3CL^pro main protease of SARS-CoV-2

Abstract

The COVID-19 pandemic, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is not showing any sign of slowing down even after the ongoing efforts of vaccination. The threats of new strains are concerning, as some of them are more infectious than the original one. A therapeutic against the disease is, therefore, of urgent need. Here, we use the DrugBank database to screen for potential inhibitors against the 3CL^pro main protease of SARS-CoV-2. Instead of using the traditional approach of computational screening by docking, we developed a kernel ridge regressor (using a part of the docking data) to predict the binding energy of ligands. We used this model to screen the DrugBank database and shortlist two lead candidates (bromocriptine and avoralstat) for in vitro enzymatic study. Our results show that the 3CL^pro enzyme activity in presence of 100 μM concentration of bromocriptine and avoralstat is 9.9% and 15.9%, respectively. Remarkably, bromocriptine exhibited submicromolar IC₅₀ of 130 nM (0.13 μM). Avoralstat showed an IC₅₀ of 2.16 μM. Further, the interactions of both drugs with 3CL^pro were analyzed using molecular dynamics simulations of 100 ns. Results indicate that both ligands are stable in the binding pocket of the 3CL^pro receptor. In addition, the MM-PBSA analysis revealed that bromocriptine (-29.37 kcal/mol) has a lower binding free energy compared to avoralstat (-6.91 kcal/mol). Further, hydrogen bond analysis also showed that bromocriptine interacts with the two catalytic residues, His⁴¹ and Cys¹⁴⁵, more frequently than avoralstat.

Communicated by Ramaswamy H. Sarma

Keywords:

• Drug discovery: SARS-CoV-2
• COVID-19
• kernel regression
• high throughput screening
• molecular docking
• molecular dynamics
• machine learning
• bromocriptine
• avoralstat

Disclosure statement

No potential conflict of interest was reported by the authors.