In the field of drug discovery, many methods of molecular modeling have been employed to study complex biological and chemical systems. Experimental strategies are integrated with computational approaches for the identification, characterization, and development of novel drugs and compounds. In modern drug designing, molecular docking is an approach that explores the confirmation of a ligand within the binding site of a macromolecule. To date, many software and tools for docking have been employed. AutoDock Vina (in UCSF [University of California, San Francisco] Chimera) is one of the computationally fastest and most accurate software employed in docking. In this paper, a sequential demonstration of molecular docking of the ligand fisetin with the target protein Akt has been provided, using AutoDock Vina in UCSF Chimera 1.12. The first step involves target protein ID retrieval from the protein database, the second step involves visualization of the protein structure in UCSF Chimera, the third step involves preparation of the target protein for docking, the fourth step involves preparation of the ligand for docking, the fifth step involves docking of the ligand and the target protein as Mol.2 files in Chimera by using AutoDock Vina, and the final step involves interpretation and analysis of the docking results. By following the guidelines and steps outlined in this paper, researchers with no previous background in bioinformatics research can perform computational docking in an easier and more user-friendly manner.

Liver cancer is the second most common cause of cancer-induced deaths worldwide. Liver cirrhosis and cancer are a consequence of the abnormal angio-architecture formation of liver and formation of new blood vessels. This angiogenesis is driven by overexpression of hypoxia-inducible factor 1-alpha (Hif1-α) and vascular endothelial growth factor (VEGF). Apart from this, protein kinase B (Akt) is also impaired in liver cancer. Despite the advancement in conventional treatments, liver cancer remains largely incurable. Nowadays, the use of naturally occurring anticancer agents particularly flavonoids is subject to more attention due to their enhanced physicochemical properties. Therefore, this study underlines the use of a natural anticancer agent taxifolin in the treatment of liver cancer using hepatocellular carcinoma cell line HepG2 and Huh7. The aim of our study is to devise a natural and efficient solution for the disease prevalent in Pakistan. The study involved the assessment of binding of ligand taxifolin using molecular docking. The binding of taxifolin with the proteins (Hif1-α, VEGF and Akt) was calculated by docking using Vina and Chimera. Further evaluation was performed by cell viability assay (MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) Assay), colony formation assay, cell migration assay, DNA ladder assay and flow cytometry. To see whether taxifolin directly affected expression levels, analysis of gene expression of Hif1-α, VEGF and Akt was performed using real-time polymerase chain reaction (qPCR) and western blotting. In silico docking experiments revealed that these proteins showed favorable docking scores with taxifolin. Treatment with taxifolin resulted in the inhibition of the liver cancer growth and migration, and induced apoptosis in HepG2 and Huh7 cell lines at an inhibitory concentration (IC50) value of 0.15 µM and 0.22 µM, respectively. The expression of HIF1-α, VEGF and Akt was significantly reduced in a dose- dependent manner. The inhibitory effect of taxifolin on hepatic cells suggested its chemopreventive and therapeutic potential. The studied compound taxifolin exhibited pronounced pro-apoptotic and hepatoprotective potential. Our study has confirmed the pro-apoptotic potential of taxifolin in liver cancer cell lines and will pave a way to the use of taxifolin as a chemotherapeutic agent after its further validation on the animal models and humans based epidemiological studies.

UNSTRUCTURED In the field of drug discovery, many methods of molecular modeling have been employed to study complex biological and chemical systems. Experimental strategies are integrated with computational approaches for the identification, characterization, and development of novel drugs and compounds. In modern drug designing, molecular docking is an approach that explores the confirmation of a ligand within the binding site of a macromolecule. To date, many software and tools for docking have been employed. AutoDock Vina (in UCSF [University of California, San Francisco] Chimera) is one of the computationally fastest and most accurate software employed in docking. In this paper, a sequential demonstration of molecular docking of the ligand fisetin with the target protein Akt has been provided, using AutoDock Vina in UCSF Chimera 1.12. The first step involves target protein ID retrieval from the protein database, the second step involves visualization of the protein structure in UCSF Chimera, the third step involves preparation of the target protein for docking, the fourth step involves preparation of the ligand for docking, the fifth step involves docking of the ligand and the target protein as Mol.2 files in Chimera by using AutoDock Vina, and the final step involves interpretation and analysis of the docking results. By following the guidelines and steps outlined in this paper, researchers with no previous background in bioinformatics research can perform computational docking in an easier and more user-friendly manner.