Comparative Modeling and Molecular Docking Study of P53 and AKT1, Genes of Lung Cancer Pathways
International Journal of Clinical Oncology and Cancer Research
Volume 1, Issue 1, December 2016, Pages: 6-14
Received: Oct. 15, 2016;
Accepted: Dec. 3, 2016;
Published: Jan. 9, 2017
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Asif Mir, Department of Bioinformatics and Biotechnology, International Islamic University, Islamabad, Pakistan
Syeda Naqsh e Zahra, Department of Bioinformatics and Biotechnology, International Islamic University, Islamabad, Pakistan
Sobiah Rauf, Department of Bioinformatics and Biotechnology, International Islamic University, Islamabad, Pakistan
The fundamentals of structure-based drug designing rely on protein-ligand interactions, which play a significant role to open a gateway from identification of active residues and development of potential drugs. The endeavor behind this work is to select most susceptible genes p53 and AKT1 which plays a vital role in lung cancer pathogencity. In a queue to deliberate the crucial role of these genes in-silico experimental strategy was adopted. 3-D structure of p53 generated by YASARA showed 50.9% sequence identity with 2PCX-A and Z-score of -0.276 while AKT1 showed 66.3% sequence identity with 3QKL-A and Z-score of 0.036. Mutational analysis revealed that R273L and C275Y mutations of p53 destabilize the DNA binding domain, while E17K mutation of AKT1directly affect the binding of the ligand as this residues lines the pocket. Molecular docking was performed using ligands Staurosporine and Nutlin-3 retrieved form ZINC database. Blind docking experiment revealed that p53 involve non polar (Leu206, Leu188, Pro190), acidic (Glu204, Tyr 205) and basic (Arg202) as most interacting residues. AKT1 interactions with ligand Staurosporine revealed nonpolar (Val164, Phe438, Phe442, Phe 236, Phe 237, Phe 161), polar (Gly159, Gly157, Gly234, Gly 278), basic (Lys163, Lys158, Lys 276, Lys 179), acidic (Asp439, Glu278) as most interacting residues. It is assumed that current study will play a significant contribution to design potential drug inhibitors by utilizing most interactive residue information with Nutlin-3 and Staurosporine ligands to restrain the interaction between p53 pathways and epidermal growth pathways. Structural based receptor-ligand interactions likely to be used against anti-cancer therapy.
Syeda Naqsh e Zahra,
Comparative Modeling and Molecular Docking Study of P53 and AKT1, Genes of Lung Cancer Pathways, International Journal of Clinical Oncology and Cancer Research.
Vol. 1, No. 1,
2016, pp. 6-14.
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