Enzymes are essential biological macromolecules, which catalyse chemical reactions and have impacted the human civilization tremendously. The importance of enzymes as biocatalyst was realized more than a century ago by eminent scientists like Kuhne, Buchner, Payen, Sumner, and the last three decades has seen exponential growth in enzyme industry, mainly due to the revolution in tools and techniques in molecular biology, biochemistry and production. This has resulted in high demand of enzymes in various applications like food, agriculture, chemicals, pharmaceuticals, cosmetics, environment and research sector. The cut-throat competition also pushes the enzyme industry to constantly discover newer and better enzymes regularly. The conventional methods to discover enzymes are generally costly, time consuming and have low success rate. Exploring the exponentially growing biological databases with the help of various computational tools can increase the discovering process, with less resource consumption and higher success rate. Present review discusses this approach, known as in-silico bioprospecting, which broadly involves computational searching of gene/protein databases to find novel enzymes.
Keywords: Bioprospecting; Enzyme; In-silico.