Protein Engineering Design and Selection · 2016 · 48 citations · 70 references
Life SciencesBiochemistryChemistryBiocatalysisComputational ChemistryEnzymologyCatalytic MechanismsComputational Enzyme DesignDisulfide Bond FormationEnzyme DiscoveryEnzyme StabilityStructural EnzymologyDe Novo Enzyme DesignEnzyme Stabilization MechanismsMutant IdentificationMutant LibrariesOptimum TemperaturePoint MutationsProtein Structural ChangesTemperature Optimum
To improve the applicability of halohydrin dehalogenase as a catalyst for reactions in the presence of organic cosolvents, we explored a computational library design strategy (Framework for Rapid Enzyme Stabilization by Computational libraries) that involves discovery and in silico evaluation of stabilizing mutations. Energy calculations, disulfide bond predictions and molecular dynamics simulations identified 218 point mutations and 35 disulfide bonds with predicted stabilizing effects. Experiments confirmed 29 stabilizing point mutations, most of which were located in two distinct regions, whereas introduction of disulfide bonds was not effective. Combining the best mutations resulted in a 12-fold mutant (HheC-H12) with a 28°C higher apparent melting temperature and a remarkable increase in resistance to cosolvents. This variant also showed a higher optimum temperature for catalysis while activity at low temperature was preserved. Mutant H12 was used as a template for the introduction of mutations that enhance enantioselectivity or activity. Crystal structures showed that the structural changes in the H12 mutant mostly agreed with the computational predictions and that the enhanced stability was mainly due to mutations that redistributed surface charges and improved interactions between subunits, the latter including better interactions of water molecules at the subunit interfaces.
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<i>Phaser</i>crystallographic software
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Inference of Macromolecular Assemblies from Crystalline State
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