Evaluating New Targets of Natural Anticancer Molecules through Bioinformatics Tools
Mehrdad Hashemi*, Newshan Behrangi, Hojat Borna and Alireza Akbarzadeh
Department of Genetics, Islamic Azad University, Tehran Medical Branch, Tehran, Iran
- *Corresponding Author:
- Dr. Mehrdad Hashemi
Department of Genetics, Islamic Azad University
Tehran Medical Branch, Tehran, Iran
E-mail: [email protected]
Received Date: December 30, 2011; Accepted Date: January 30, 2012; Published Date: February 29, 2012
Citation: Hashemi M, Behrangi N, Borna H, Akbarzadeh A, et al. (2012) Evaluating New Targets of Natural Anticancer Molecules through Bioinformatics Tools. J Proteomics Bioinform 5:050-053. doi: 10.4172/jpb.1000212
Copyright: © 2012 Hashemi M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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 A and 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.