Protein Engineering Design and Selection · 2008 · 87 citations · 20 references
Life SciencesBiochemistryMolecular BiologyEnzymologyProtein BiochemistryProtein EngineeringProtein DesignProtein Sequence AnalysisProtein StructureProteolytic EnzymesProteolytic ProcessingGluten ProteinsGluten StructureImmunotoxic EffectsMachine Learning-guided Protein EngineeringPeptidase ActivityPh OptimaSimulated Gastric FluidSimulated Gastric Media
Due to their unique ability to cleave immunotoxic gluten peptides endoproteolytically, prolyl endopeptidases (PEPs) are attractive oral therapeutic candidates for protecting celiac sprue patients from the toxic effects of dietary gluten. Enhancing the activity and stability of PEPs under gastric conditions (low pH, high pepsin concentration) is a challenge for protein engineers. Using a combination of sequence- and structure-based approaches together with machine learning algorithms, we have identified improved variants of the Sphingomonas capsulata PEP, a target of clinical relevance. Through two rounds of iterative mutagenesis and analysis, variants with as much as 20% enhanced specific activity at pH 4.5 and 200-fold greater resistance to pepsin were identified. Our results vividly reinforce the concept that conservative changes in proteins, especially in hydrophobic residues within tightly packed regions, can profoundly influence protein structure and function in ways that are difficult to predict entirely from first principles and must therefore be optimized through iterative design and analytical cycles. Incubation with whole wheat bread under simulated gastric conditions also suggests that some variants have pharmacologically significant improvements in gluten detoxification activity.
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