Abstract

Plant growth-promoting bacteria are well known to produce various bacterial secondary metabolites (BSM) which are much diversified in their origin and structure. These metabolites provide beneficial effect to crops which lead to sustainable agriculture. Each BSM is produced inside the bacterial cell by the regulation of specific biochemical pathways. To increase the yield of crops, there is a need to understand the metabolic pathway for the synthesis of secondary metabolites. Experimental approach to study the metabolic pathway was found to be limiting in terms of time and money. Development in the genome sequencing technologies and computational methods shifts the focus of researchers toward in silico approaches to reconstruct the biochemical pathways of metabolite production in genome-scale metabolic level. There are varieties of computational databases and tools available for the analysis of biosynthetic gene clusters including the prediction of non-ribosomal peptide synthetases (NRPS) and polyketide synthase (PKS) enzymes which encode for bacterial metabolites. These tools are developed to analyze the biochemical pathways for metabolite production. The present chapter gives a comprehensive overview on the in silico approach for the reconstruction of biochemical pathway and different databases and computational tools associated with it.

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