Quantitative Structure-Activity Relationship Study Of Volitinib And Its Derivatives As A Highly Potent And Selective Mesenchymal-Epithelial Transition Factor (c-Met) Inhibitor

Cancer is the one of the incurable diseases which causing the tragically death among the developing country. Many research and therapy have been uses for the treatment of this cancer disease. The main factor of the cause of cancer is the growth of cancer cells or the tumor which cannot be prevent....

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Bibliographic Details
Main Author: Rifdi Bin Mohamad Fuzi, Mohamad
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/44755
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:Cancer is the one of the incurable diseases which causing the tragically death among the developing country. Many research and therapy have been uses for the treatment of this cancer disease. The main factor of the cause of cancer is the growth of cancer cells or the tumor which cannot be prevent. Tumorigenesis is a multistep process in which oncogenes play a key role in tumor formation, growth, and maintenance. Met was discovered as an oncogene that is activated by its ligand, hepatocyte growth factor. Deregulated signaling in the c-Met pathway has been observed in multiple tumor types. Herein we report the discovery of potent and selective Volitinib derivatives that inhibit c-Met activity. Volitinib which is compound 28 has been proven to have exquisite pharmacokinetic profiles towards the cancer or tumor cells in vivo specifically, the c-Met kinase and the Receptor Tyrosine Kinase (RTK). The aim of the present research was to design the Volitinib derivatives as novel antitumor compounds based on the Quantitative Structure-Activity Relationship (QSAR) methods. Molecular structures were designed by the GaussView 5.0.8 and optimized using Gaussian 09W software. The physical chemistry properties were calculated using Molecular Operation Environment (MOE 2009.10) software and multilinear statistical analysis was done by using SPSS Statistics 21.0. The validation was conducted by Leave One Out (LOO) method while the designing of new compounds were done by using Topliss scheme based on the QSAR equation. The candidates of the antitumor compounds were docked into c-Met kinase using AutoDock 4.2 software to predict their interaction. The best QSAR equation obtained was IC50 = -3.449E-5 (± 4.835E-6) Am1_Eele - 0.973 (± 0.147) Am1_LUMO - 0.022 (± 0.005) ASA_H - 67.097 (± 9.044) Glob - 0.588 (± 0.123) Log S - 5.565 (± 0.717) Mr + 64.384 (± 8.437). Except compound z8 and z10 all other compounds are proven to have a better stability and energy affinity than the lead compound. The best compounds which have the highest hydrogen bond and highest number of amino acids residue are compound z6, z7 and z9.