Computational insights into pediatric adenovirus inhibitors: in silico strategies for drug repurposing

Abstract

Human adenovirus (HADV) infection can pose a serious threat to children, leading to a variety of respiratory illnesses and other complications. Particularly, children with weak immune systems are vulnerable to severe adenovirus infections with high mortality. The main focus of this study is to propose new antiviral agents as lead HADV inhibitors for children. So, several antiviral agents used in children were subjected to finding new HADV inhibitors using important computational methods of molecular docking, molecular dynamics (MD) simulation, Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) binding free energy calculations, density functional theory (DFT), and pharmacokinetic analysis. Molecular docking of standard cidofovir along with other ligands, suggested that sofosbuvir has the highest binding energy (−10.8 kcal/mol), followed by baloxavir marboxil (−10.36 kcal/mol). Further, the analysis of molecular interactions using MD simulation (100 ns) and MM-PBSA indicated that baloxavir marboxil has formed the most stable protein–ligand complex with HADV, followed by sofosbuvir. The binding free energies of baloxavir marboxil and sofosbuvir were found to be −61.724 kJ/mol and −48.123 kJ/mol, respectively. The DFT and drug-likeness properties of these compounds were also investigated. Overall, two antiviral agents, such as baloxavir marboxil, and sofosbuvir are suggested as lead repurposed candidates against HADV.

Communicated by Ramaswamy H. Sarma

Keywords:

• Adenovirus
• drug repurposing
• molecular docking
• molecular dynamics simulation
• MM-PBSA
• ADMET
• DFT

Acknowledgments

All authors are thankful to the High Performance Computing (HPC) cluster of University of North Bengal for computational facility, Department of Chemistry for various support.

Disclosure statement

The authors declare no conflict of interest.

Additional information

Funding

KS is thankful to UGC, New Delhi for NET-JRF fellowship and RKD is grateful to University Grants Commission, New Delhi for the project F.30-515/2020(BSR), 12.02.2020, F.D. Diary No. 9719, 23.01.2020.