alexa In Silico Approach for the Bioremediation of Toxic Pollutants | OMICS International | Abstract
ISSN:2157-7463

Journal of Petroleum & Environmental Biotechnology
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Review Article

In Silico Approach for the Bioremediation of Toxic Pollutants

Fazlurrahman Khan, Mohammad Sajid and Swaranjit Singh Cameotra*
Environmental Biotechnology and Microbial Biochemistry Laboratory, Institute of Microbial Technology, Sector 39-A, Chandigarh-160036, India
Corresponding Author : Swaranjit Singh Cameotra
Environmental Biotechnology and Microbial Biochemistry Laboratory
Institute of Microbial Technology
Sector 39-A, Chandigarh-160036, India
Tel: +91-6665223/224
Fax: +91-172-2690632
E-mail: [email protected]
Received October 07, 2013; Accepted November 22, 2013; Published November 29, 2013
Citation: Khan F, Sajid M, Cameotra SS (2013) In Silico Approach for the Bioremediation of Toxic Pollutants. J Phylogenetics Evol Biol 4:161. doi:10.4172/2157-7463.1000161
Copyright: © 2013 Khan F, 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.

Abstract

Microbial degradation is considered as one of the environment friendly and cost-effective method for restoration of ecological niches contaminated with chemical pollutants. Thus before the application of microbial system for the degradation of any newly released pollutant in the environment, there is need to in silico study for predicting the possible degradation pathways by using various computational tools. There are large number of databases and computer programs available to perform the computational analysis for assisting the development and implementation of microbial bioremediation. The present review provides a comprehensive account of these databases, software, their respective work methodologies and potential application for the bioremediation. The information collected for the above study from different in silico resources for assisting the environmental degradation studies is discussed.

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