Old Drug for New Use： Searching for MEK1 （Mitogen- Activated Protein Kinase Kinase 1） Inhibitor by the Computer Aided Drug Design
Old Drug for New Use： Searching for MEK1 （Mitogen- Activated Protein Kinase Kinase 1） Inhibitor by the Computer Aided Drug Design作者机构：Department of Biological Science and Technology China Medical University Taichung 404 Taiwan School of Chinese Medicine College of Chinese Medicine China Medical University Taichung 404 Taiwan Department of Biomedical Imaging and Radiological Science China Medical University Taichung 404 Taiwan
出 版 物：《Journal of Life Sciences》 (生命科学（英文版）)
年 卷 期：2013年第7卷第5期
页 面：453-458页
学科分类：0710[理学-生物学] 07[理学] 09[农学]
主 题：MEK (Mitogen-activated protein kinase kinase) MAPK (mitogen-activated protein kinase) pharmacophore QSAR(quantitative structure-activity relationship) PHP (hypertext preprocessor).
摘 要：An old drug with a new use can significantly reduce the cost and time for new drug research and development. MAPK （Mitogen-activated protein kinase） plays a very important key role in signal transduction pathways of cell proliferation and differentiation. According to the statistics, there are about 30% persons who suffered from cancers related to the MAPK signal transduction pathways. Therefore, many researchers are focused on blocking these pathways in cancers therapies. Ras/Raf/MEK/ERK, however, is one of very important pathways among MAPK message transduction pathways. More and more information about MEK protein inhibitors are unveiled in several recent years. In the present study, the authors utilized MEK inhibitors which were already published and their activities were available to construct 2D-QSAR model by using CADD （multiple linear regression）. Then, the authors searched certified FDA drugs （Drugs@FDA 6184 drugs） making preliminary screening. The secondary screening on 3D structures were followed by using Docking, Scoring and Pharmacophore analysis to find out most suitable MEK inhibitors to become a fundamental database in drug discovery. The results are shown the ALogP, number of aromatic rings, number of hydrogen bond acceptors and number of hydrogen bond donors are all in positive correlation. According to the equation from 2D-QSAR model, the results conform to the previous description.
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