In-silico investigations on the anticancer activity of selected 2-aryloxazoline derivatives against breast cancer

Abstract

As the in-silico study has become an important tool to search for new drugs in the concurrent era with towering acceptance and accuracy, it has been employed in our research to unearth effective cancer drugs. Breast cancer has accounted for the most serious diseases for both men and women. Although few research outputs have been obtained on breast cancer, these are not an adequate amount to ascertain new drugs. Due to this gap, virtual screening, in-silico study, and computational techniques have been used to provide the ability to design and select anticancer compounds with desirable drug-like properties of breast cancer protein, which is commonly known as fatty acid synthase. A total of nine derivatives of 2-aryloxazoline compounds were chosen, and In-silico was studied to evaluate as a potential anticancer agent with the comparison of seven Food and Drug Administration(FDA) approved breast cancer drugs. These compounds were subjected to computational studies for quantum calculations, ADME and Lipinski analysis, as well as molecular docking and MD simulations against a variety of therapeutic targets involved in cell proliferation of fatty acid synthase (PDB ID:3TJM, 3ERT, 4OAR, 2J6M). An in-silico docking study reveals that ligands Hit-4, Hit-6, and Hit-8 had the highest docking scores at −10.3 kcal/mol, −10.3 kcal/mol, and −10.2 kcal/mol towards the protein of fatty acid synthase. The ligands had docking scores better than the standard anti-breast cancer drug gefitinib (−5.3 kcal/mole). Our findings demonstrate how crucial it is for pharmaceutical researchers to develop novel drugs for the treatment of breast cancer.

Communicated by Ramaswamy H. Sarma

Keywords:

• 2-Aryloxazoline
• breast cancer
• fatty acid synthase (FASN)
• molecular docking
• molecular dynamics

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

The author(s) reported there is no funding associated with the work featured in this article.

Authors’ contributions

Moly Rani: Conceptualization, software, visualization, validation, writing – original manuscript. Ashutosh Nath: Supervision, conceptualization, methodology, software, visualization, writing – review & editing, investigation, validation. Ajoy Kumer: Review & editing, investigation, validation. All authors reviewed the paper.

Data and software availability

AutoDock Vina, PyRx, Discover Studio, PyMOL software and web server used in this analysis is free for academic use. And licensed software’s are Gaussian16, Yet Another Scientific Artificial Reality Application (YASARA) used for Molecular Dynamics simulation.