YouTube video by Research Institute of Molecular Pathology

By combining structural biology and evolutionary genomics analyses, the evolution of enzymes over 400 million years is shown to be governed by catalytic function, metabolic network architecture, cost ...

Proteins are constructed from a limited alphabet of ~20 amino acids, yet the origins and selection of this specific alphabet are unresolved. One largely overlooked aspect is whether elemental composit...

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Traditional protein engineering methods, such as directed evolution, while effective, are often slow and labor-intensive. Advances in machine learning and automated biofoundry present new opportunities for optimizing these processes. This study devises a protein language model-enabled automatic evolution platform, a closed-loop system for automated protein engineering within the Design-Build-Test-Learn cycle. The protein language model ESM-2 makes zero-shot prediction of 96 variants to initiate the cycle. The biofoundry constructs and evaluates these variants, and feeds the results back to a multi-layer perceptron to train a fitness predictor, which then makes prediction of second round of 96 variants with improved fitness. With the tRNA synthetase as a model enzyme, four-rounds of evolution carried out within 10 days lead to mutants with enzyme activity improved by up to 2.4-fold. Our system significantly enhances the speed and accuracy of protein evolution, driving faster advancement

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The intrinsic conformational flexibility of proteins creates structural heterogeneity, giving rise to conformational ensembles within the energy lands…