Computational Screening of Anti-Cancer Phytochemicals: Molecular Docking Simulations
Muhammad Ahmad Riaz, Sana Riaz, Samrah Khalid, Tariq Javed
Background: Cancers are caused by uncontrolled proliferations of malignant cells due to defective apoptosis mechanism therefore, most attractive drug target discovery strategy is to find ligands which have the ability to activate or regulate the apoptotic machinery.
Aim: To scrutinized anticancer attractive drug target ligands from Arnebia hispidissima, Terminalia arjuna, Digera arvensis forsk and Caesalpinia crista.
Methodology: In silico molecular modeling simulations were performed by interactions between active site of receptor residues and potential phytochemical ligand with least energy values and most efficient interactions.
Results: The most effective medicinal plant with significant number of phytochemicals with virtual potential anticancer phytochemical remain Arnebia hispidissima. Moreover, the potential phytochemicals from Terminalia arjuna possess significant binding affinity including are ursolic acid-2xyj, ursolic acid-5c3h and Ellagic acid-2xyj respectively. Moreover Bcl-2 regulator protein showed maximum amino acid interactions by all the phytochemicals.
Conclusion: This advanced computational drug designing modeling approach therefore, identifies the potential leads against over expressed tumours.
Keywords: Arnebia hispidissima, Terminalia arjuna, Digera arvensis forsk, Caesalpinia crista, antitumor, molecular modeling