Enzymes are in high demand for very diverse biotechnological applications. However, natural biocatalysts often need to be engineered for fine-tuning their properties towards the end applications, such as the activity, selectivity, stability to temperature or co-solvents, and solubility. Computational methods are increasingly used in this task, providing predictions that narrow down the space of possible mutations significantly and can enormously reduce the experimental burden. Many computational tools are available as web-based platforms, making them accessible to non-expert users. These platforms are typically user-friendly, contain walk-throughs, and do not require deep expertise and installations. Here we describe some of the most recent outstanding web-tools for enzyme engineering and formulate future perspectives in this field.

Loschmidt Laboratories Department of Experimental Biology and RECETOX Faculty of Science Masaryk University Kamenice 5 C13 625 00 Brno Czech Republic; International Centre for Clinical Research St Anne's University Hospital Brno Pekarska 53 656 91 Brno Czech Republic

References provided by Crossref.org

Engineering Dehalogenase Enzymes Using Variational Autoencoder-Generated Latent Spaces and Microfluidics

Machine Learning-Guided Protein Engineering

CalFitter 2.0: Leveraging the power of singular value decomposition to analyse protein thermostability

LoopGrafter: a web tool for transplanting dynamical loops for protein engineering