Computational evaluation of bioactive compounds from Viscum album (mistletoe) as inhibitors of p63 for pancreatic cancer treatment

Abstract

Pancreatic ductal adenocarcinoma is an aggressive malignancy usually detectable at the advanced stage, with a 5-year survival rate of less than 8%. It has been reported that a gene called tumor-protein 63 (TP63) is expressed in an aggressive form of pancreatic cancer with a squamous signature. Thus, inhibiting the activity of p63 can be a means of treating and managing PDA. Different studies have shown that plant constituents are rich and can be a promising source for discovering drug candidates. The extract from mistletoe (Viscum album) is known to contain anticancer compounds; however, the specific molecular mechanism of the bioactive compounds is unknown. This study examines the pancreatic cancer therapeutic potential of the bioactive compounds in the flavonoid and phenolic acid constituents of mistletoe by adopting structural bioinformatics and advanced theoretical chemistry techniques via molecular docking, molecular dynamics simulation, molecular mechanics/generalized Born surface area (MM/GBSA) calculations, pharmacokinetic analysis, and density functional theory analysis. The six best compounds from the flavonoid constituent with the highest binding affinity ranging from −6.8 kcal/mol to −6.7 kcal/mol were selected with the control gemcitabine (−5.5 kcal/mol) for further computational analysis after molecular docking. Furthermore, MM/GBSA calculation showed the highest binding energy for the selected docked compounds, which validates their inhibitory potential. Hence, the molecular dynamics simulation, post-simulation analysis, pharmacokinetics model, and DFT results showed that mistletoe compounds are reliable due to their stable interaction with the target protein and drug-likeness properties.

Communicated by Ramaswamy H. Sarma

Keywords:

• Pancreatic ductal adenocarcinoma
• tumor-protein63
• molecular docking
• density functional theory
• molecular dynamic simulation

Disclosure statement

The authors declare no conflict of interest

Data availability statement

Data available upon request

Author contributions

GD designed the study. GD, AI, and TB performed high-throughput virtual screening and chemical library curation. GD, AI, and TB performed molecular docking, pharmacokinetic analysis, molecular dynamics simulation, and post-simulation analysis. GD, MNW, and JJD performed density functional theory calculations. GD drafted the manuscript. JJD and MS critically revised the manuscript. All authors read and approved the final manuscript.

Informed consent statement

Not applicable

Additional information

Funding

This work used Expanse at the San Diego Supercomputer Center through allocation CHE220065 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296.