Virtual screening and repurposing of FDA-approved drugs from ZINC database to identify potential autophagy inhibitors exploiting autophagy related 4A cysteine peptidase as a target: potential as novel anti-cancer molecule.

Abstract

Cancer cells utilize extensive autophagy in effort to adapt to high metabolic stress. This indicates that impairing the high autophagic flux might be an attractive target for cancer therapy. Autophagy related gene 4A (ATG4A) is a key player for autophagy and its inhibition may help in tumor clearance. The present study aims to screen candidate drugs from FDA-approved drugs, a subset of Zinc database, to identify potential ATG4A inhibitors that may have anti-cancer activity. Computer aided drug design approach was applied for the study using the virtual screening tools Raccoon and MGLTools-1.5.6. We have identified the drug Lumacaftor as a potent inhibitor of ATG4A on the basis of computational approaches viz. molecular docking, molecular dynamics simulation and MM/PBSA method. The drug is likely to be a potent regimen candidate to be used as an anti-cancer molecule. However, this potent inhibitor against ATG4A as anti-cancer molecule needs further investigation and validation.

Communicated by Ramaswamy H. Sarma

Keywords:

• Bioinformatics
• ATG4A
• molecular docking
• ADME
• MD simulation
• MM/PBSA
• cancer

Acknowledgements

The infrastructure facilities by IIT (BHU) Varanasi are acknowledged. Further, the support and the resources provided by PARAM Shivay Facility under the National Supercomputing Mission, Government of India at the Indian Institute of Technology, Varanasi are gratefully acknowledged.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The work is supported by CSIR project [27(344)/19-EMR-II] to V.K.D.