Computational molecular docking studies on anticancer drugs

Journal Title: Asian Pacific Journal of Tropical Disease - Year 2012, Vol 2, Issue 0

Abstract

Objective: Cancer can be described as the uncontrolled growth of abnormal cells. Lung cancer is one of the commonest malignant neoplasms all over the world. Oncogenic fusion genes consisting of EML4 and anaplastic lymphoma kinase (ALK) are present in non-small-cell lung cancers, representing 2 to 7% of such tumors. ALK proteins play a vital role in deactivating the apoptosis process in cancer disease. Some of the most commonly used non-small-cell lung cancers drugs are Crizotinib, Sunitinibmalate, Tandutinib etc..., Non-small-cell lung cancer Cells need anaplastic lymphoma kinase (ALK) to cell growth and proliferation the role of ALK in malignant proliferation and as a valid drug target. These drugs mainly work against the effects of ALK on these cells. Methods: The Protein- Ligand interaction plays a significant role in structural based drug designing. In our research work we have taken the Human anaplastic lymphoma kinase (ALK) and the commercially available drugs against non-small-cell lung cancer. The ALK was docked to the above said drugs and the energy value obtained as follows Crizotinib(-9.86), Sunitinib malate(-8.26), Tandutinib(-8.05) using the Argus Lab docking software. Results: Depending on the energy values we have chosen the best two drugs they are Crizotinib(-9.86) and Sunitinib malate(-8.26). We tried to improve the binding efficiency and steric compatibility of the two drugs namely Crizotinib(-9.86) and Sunitinib malate(-8.26). Several modifications were made to the probable functional groups which were interacting with the receptor molecule. Analogs of this drug molecule were prepared using ACD ChemSketch and docked using Argus Lab docking software. Conclusions: Crizotinib Analog 2 and Sunitinib malate analog 1 were detected with significant energy values and probable lead molecules. The Modified drugs was sketched using Chemsketch were found to be better than the conventional drugs available. Further from this work we can improve the steric compatibility and then ADME/T properties of the Analogs can be analyzed using Inslico ADME/T tools available.

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  • EP ID EP234110
  • DOI 10.1016/S2222-1808(12)60254-0
  • Views 79
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How To Cite

(2012). Computational molecular docking studies on anticancer drugs. Asian Pacific Journal of Tropical Disease, 2(0), 734-738. https://europub.co.uk/articles/-A-234110