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The optimization of enzyme properties for specific reaction conditions enables their tailored use in biotechnology. Predictions using established computer-based methods, however, remain challenging, especially regarding physical parameters such as thermostability without concurrent loss of activity. Employing established computational methods such as energy calculations using FoldX can lead to the identification of beneficial single amino acid substitutions for the thermostabilization of enzymes. However, these methods require a three-dimensional (3D)-structure of the enzyme. In contrast, coevolutionary analysis is a computational method, which is solely based on sequence data. To enable a comparison, we employed coevolutionary analysis together with structure-based approaches to identify mutations, which stabilize an enzyme while retaining its activity. As an example, we used the delicate dimeric, thiamine pyrophosphate dependent enzyme ketoisovalerate decarboxylase (Kivd) and experimentally determined its stability represented by a T 50  value indicating the temperature where 50% of enzymatic activity remained after incubation for 10 min. Coevolutionary analysis suggested 12 beneficial mutations, which were not identified by previously established methods, out of which four mutations led to a functional Kivd with an increased T 50  value of up to 3.9°C.

biological chemistry

Direct coupling analysis improves the identification of beneficial amino acid mutations for the functional thermostabilization of a delicate decarboxylase