Ebselen suitably interacts with the potential SARS-CoV-2 targets: an in-silico approach

Abstract

Ebselen (SPI-1005) is an active selenoorganic compound that can be found potential inhibitory activity against different types of viral infections such as zika virus, influenza A virus, HCV, and HIV-1; and also be found to exhibit promising antiviral activity against SARS-CoV-2 in cell-based assays but its particular target action against specific non-structural and structural proteins of SARS-CoV-2 is unclear to date. The purpose of this study is to evaluate the anti-SARS-CoV-2 efficacy of Ebselen along with the determination of the specific target among the 12 most common target proteins of SARS-CoV-2. AutoDock Vina in PyRx platform was used for docking analysis against the 12 selected SARS-CoV-2 encoded drug targets. ADME profiling was examined by using SwissADME online server. The stability of binding mode in the target active sites was evaluated using molecular dynamics (MD) simulation studies through NAMD and Desmond package software application. In this docking study, we recognized that Ebselen possesses the highest affinity to N protein (C domain) (PDB ID: 6YUN) and PLpro (PDB ID: 6WUU) among the selected SARS-CoV-2 targets showing −7.4 kcal/mol binding energy. The stability of Ebselen-6YUN and Ebselen-6WUU was determined by a 100 ns trajectory of all-atom molecular dynamics simulation. Structural conformation of these two complexes displayed stable root mean square deviation (RMSD), while root mean square fluctuations (RMSF) were also found to be consistent. This molecular docking study may propose the efficiency of Ebselen against SARS-CoV-2 to a significant extent which makes it a candidature of COVID-19 treatment.

Graphical Abstract

Communicated by Ramaswamy H. Sarma

Keywords:

• Ebselen (SPI-1005)
• SARS-CoV-2
• COVID-19
• molecular docking
• binding affinity
• ADME profiling
• molecular dynamics

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Shandong University postdoctoral fellowship to Mohnad abdalla and by the Evergreen Scientific Research Center in Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj (Dhaka)-8100, Bangladesh for providing the computational facilities.