Literature DB >> 23424251

Modifying the catalytic preference of tributyrin in Bacillus thermocatenulatus lipase through in-silico modeling of enzyme-substrate complex.

Emel Durmaz1, Serdar Kuyucak, Ugur O Sezerman.   

Abstract

In this study, rational design for Bacillus thermocatenulatus lipase (BTL2) was carried out to lower the activation barrier for hydrolysis of short-chain substrates. In this design, we used computational models for the enzyme-substrate (ES) complexes of tributyrin (C4) and tricaprylin (C8), which were generated through docking and molecular dynamics (MD) simulations. These ES complexes were employed in steered MD (SMD) simulations with Jarzynski's equality to estimate their relative binding free energies. Potential mutation sites for modifying the chain-length selectivity of BTL2 were found by inspecting the SMD trajectories and fine-tuning the volume and hydrophobicity of the cleft. Seven mutations (F17A, L57F, V175A, V175F, I320A, I320F and L360F) were performed to cover three binding pockets for sn-1, sn-2 and sn-3 acyl chains. The relative binding free energies of the mutant ES complexes formed by C4 and C8 ligands were calculated similarly. The experimental routines of protein engineering including site-directed mutagenesis, heterologous protein expression and purification were performed for all lipases. Steady-state specific activities towards C4 and C8 were determined for wild-type and mutant lipases, which gave an estimate of the relative change in the binding free energy of transition state complex (ES(‡)). The chain-length selectivity of mutants was determined from the relative changes in the activation barrier of hydrolysis of C4 and C8 triacylglycerol with respect to wild-type using computational and experimental findings. The most promising mutant for C4 over C8 preference was found to be L360F. We suggest that L360F may be at a critical position to lower the activation barrier for C4 and elevate it for C8 hydrolysis.

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Year:  2013        PMID: 23424251     DOI: 10.1093/protein/gzt004

Source DB:  PubMed          Journal:  Protein Eng Des Sel        ISSN: 1741-0126            Impact factor:   1.650


  7 in total

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Review 6.  A review of metabolic and enzymatic engineering strategies for designing and optimizing performance of microbial cell factories.

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  7 in total

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