HIF1 inhibition of the biflavonoids against pancreas cancer: drug-likeness, bioavailability, ADMET, PASS, molecular docking, molecular dynamics, and MM/GBSA calculations

Abstract

Pancreatic cancer is an aggressive disease with a high death rate and is difficult to treat. This disease, in the most cases, is asymptomatic until it progresses to an advanced stage. Therefore, the search for bioactive molecules is urgent to combat pancreatic cancer. Then, this work analyzed the interaction potential of agathisflavone and amentoflavone molecules against the HIF1 target using the ADMET, molecular docking, and molecular dynamics simulations. More recent drug-likeness filters that combine physicochemical and physiological parameters have shown that high polar surface area (TPSA > 75 Ų) drives biflavonoids out of the toxic drug space of Pfizer dataset. Regarding the pharmacokinetic descriptors, it was possible to notice that Amentoflavone showed a better order of passive cell permeability (P_app = 8 × 10⁻⁶cm/s) and better metabolic stability, biotransformed by aromatic hydroxylation reactions by the CYP3A4 isoenzyme on the human liver, that favor its hepatic clearance. The molecular docking and molecular dynamics simulations indicated the high interaction potential and stability between the ligands analyzed (highlighted the amentoflavone molecule), respectively. The MM/GBSA calculations showed that the amentoflavone ligand registered the highest ΔG binding value of −32.6957 kcal/mol with the HIF1 target. Then, this molecule may be used as a potential inhibitor of pancreatic cancer. In this perspective, the present work represents an initial step in the virtual bioprospecting a pharmacological tool for treating of pancreatic cancer.

Communicated by Ramaswamy H. Sarma

Keywords:

• Anticancer
• biflavonoids
• ADMET
• molecular docking
• molecular dynamics

Acknowledgments

Laboratory of Chemistry of Natural Products (LQPN) of the State University of Ceará (UECE), National Center for High Performance Processing of the Federal University of Ceará (CENAPADI – UFC) and Ceará Foundation of Support for Scientific and Technological Development (FUNCAP, Brazil) for the LF scholarship funding and research projects. We also thank Luiz Wilson Lima-Verde for the exsiccate deposit at Prisco Bezerra herbarium of Federal University of Ceará. The authors also thanks to National Center for High Performance Processing – UFC for the computational resources.

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.