Computer aided design of efficient phytases

• Main Authors: Noorbatcha, Ibrahim Ali, Samsudin, Nurhusna, Hamzah, Mohd. Salleh, Syed Osman Idid, Syed Zahir Idid
• 格式: Conference or Workshop Item
• 語言: English; English; English
• 出版: 2009
• 主題: TP248.13 Biotechnology
• 在線閱讀: http://irep.iium.edu.my/13864/1/KERIE2009_Phytase_poster.pdf; http://irep.iium.edu.my/13864/2/KERIE2009_Programme_Book_BTE.pdf; http://irep.iium.edu.my/13864/3/LIst_of_WinnersKERIE09.pdf; http://irep.iium.edu.my/13864/

Phytases catalyze the hydrolysis of inorganic phosphate (InsP6) from phytic acid and are able to improve the nutritional quality of phytate rich diet. However, phosphorous in this form (phytate) is largely unavailable to monogastric animals such as poultry and fish, because monogastric animal is lacking intestinal phytase. In addition to the unavailability of precious nutrients, phytate not assimilated by animal is excreted in manure and contribute to the phosphorous related environmental pollution problem. Availability of efficient phytases can solve this problem by completely degrading phyates. In this work we have successfully designed a new improved phytase using computed aided protein design (CAPD). We started from a native phytase, identified it’s active site and analyzed the factors that are responsible for phytase binding and hence it’s activity. Armed with this understanding, we have mutated the enzyme and have designed a best mutated enzyme with enhanced binding character. We have identified the active site in Eschericia coli phytase and further validated by docking the known ligands in to the active site using well known Genetic Algorithm (GA) techniques. Transition state of the reaction is determined to calculate the activation energy barrier of the enzyme. Map reaction methods used to determine the transition state and numerical vibrational analysis is carried out to verify transition states. After characterizing the active site, selected amino acid residues are mutated to investigate their effects on the binding strength of this phytase. After a careful manual docking procedure, automated docking is carried out to calculate the strength of the binding before and after mutation. It is found that mutation at position M216R and E219R leads to improvement in the binding strength while mutation at position H17A shows decrease in binding and mutation at A116T have no effect in the binding strength.