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Plants-derive compounds play crucial role in development of several anti-cancer drugs and they target proteins having significant regulatory effects on tumor cell cycle progress. Bioinformatics and cancer research overlap in many different areas in order to solve some problems in the field of treatment. In this study, the target and drug likeness of natural anticancer molecules are predicted by PASS software. Consequently, some new mechanisms of anticancer molecules have been introduced. They include Pseudobaptigenin with 0.702 PASS thresholds which revealed protein tyrosine kinase inhibitory. In addition, Kabophenol Aand Carasinol B with score 0.652 and 0.669 respectively exhibited topoisomerase I inhibitory effects. Moreover, Docetaxel, 7-xylosyl-10-deacetyl paclitaxel and Artemether by exhibiting the highest PASS score are the strongest anticancer agents in our research. It is notice worthy all of studied agents exhibited high drug-likeness score and it means that they can be applied as drug.
Dr. Mehrdad Hashemi: Evaluating New Targets of Natural Anticancer Molecules through Bioinformatics Tools
Last date updated on June, 2014