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Title

The RAS subfamily Evolution tracing evolution for its utmost exploitation

 

Authors

Ismail IF Saad1, Saurav B Saha2* & George Thomas3

 

Affiliation

1Department of Zoology, Faculty of Science, Omar Al Mukhtar University, Al Bayda, Libya; 2Department of Computational Biology and Bioinformatics, JSBB, SHIATS, Allahabad - 211007, India; 3Department of Molecular and Cellular Engineering, JSBB, SHIATS, Allahabad - 211007, India

 

Email

saurav.saha@shiats.edu.in; *Corresponding author

 

Article Type

Hypothesis

Date

Received May 03, 2014; Accepted May 04, 2014; Published May 20, 2014

 

Abstract

In the development of multicellularity, signaling proteins has played a very important role. Among them, RAS family is one of the most widely studied protein family. However, evolutionary analysis has been carried out mainly on super family level leaving sub family information in scanty. Thus, a subfamily evolutionary study on RAS evolutionary expansion is imperative as it will aid in better drug designing against dreadful diseases like Cancer and other developmental diseases. The present study was aimed to understand RAS evolution on both holistic as well as reductive level. All human RAS family genes and protein were subjected to BLAST tools to find orthologs and paralogs with different parameters followed by phylogenetic tree generation. Our results clearly showed that H-RAS is the most primitive RAS in higher eukaryotes and then diverged into other RAS family members due to different gene modification events. Furthermore, a site specific selection pressure analysis was carried out using SELECTON server which showed that H-RAS, M-RAS and N-RAS are evolving faster than K-RAS and R-RAS. Thus, the results ascertain a new ground to cancer biologists to exploit negatively selected K-RAS and R-RAS as potent drug targets in cancer therapeutics.

 

Keywords

RAS, evolution, cancer, evolutionary tree, selection pressure

 

Citation

Saad  et al. Bioinformation 10(5): 293-298 (2014)
 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.