Shikimate Kinase of Yersinia pestis: A Sequence, Structural and Functional Analysis
- *Corresponding Author:
- Dr. Neelima Arora
Centre for Biotechnology
Institute of Science and Technology
Jawaharlal Nehru Technological University, Kukatpally
Hyderabad-500085, Telangana State, India
Tel: +91-040 2315-8661
E-mail: [email protected]
Received date: January 29, 2016; Accepted date: February 22, 2016; Published date: March 15, 2016
Citation: Arora N, Narasu ML, Banerjee AK (2016) Shikimate Kinase of Yersinia pestis: A Sequence, Structural and Functional Analysis. Int J Biomed Data Min 5:119. doi:10.4172/2090-4924.1000119
Copyright: ©2016 Arora N, 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.
Yersinia pestis, the causative organism of Plague, is widely recognized as a potential bioterrorism threat. Due to the absence of homologs in human, Shikimate Kinase (SK) is considered as an excellent drug target in several bacterial and protozoan parasites. Ample literature evidences confirm the suitability of this protein as a good target. Therefore, Shikimate Kinase of Shikimate pathway in Yersinia pestis represents an attractive drug target. In the present study, a clustering approach was undertaken to select the proper representative for Shikimate Kinase sequences belonging to Yersinia pestis for structure determination. Three-dimensional models of the enzyme for KFB61218.1 (SK1), EFA47400.1 (SK2) and WP_016255950.1 (SK3) were generated using a comparative molecular modeling approach where structures were developed using the single specific template as well as multiple closely associated templates. The structures of Shikimate Kinase developed using comparative modeling were evaluated for stereochemical quality using various structural validation tools. Results from structural assessment tools indicated the reasonably good quality of models.