Publications by authors named "Mojmir Mutny"

Darwinian evolution has given rise to all the enzymes that enable life on Earth. Mimicking natural selection, scientists have learned to tailor these biocatalysts through recursive cycles of mutation, selection and amplification, often relying on screening large protein libraries to productively modulate the complex interplay between protein structure, dynamics and function. Here we show that by removing destabilizing mutations at the library design stage and taking advantage of recent advances in gene synthesis, we can accelerate the evolution of a computationally designed enzyme.

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Article Synopsis
  • * To enhance the efficiency of this process, researchers developed a new method that combines large-scale screening and machine learning, successfully applied to create an artificial metalloenzyme for a unique reaction.
  • * This integrated approach significantly increased the success rate of enzyme variants while minimizing experimental costs and time, suggesting its widespread applicability in advancing enzyme engineering and biocatalyst development.
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Soft robots have applications in safe human-robot interactions, manipulation of fragile objects, and locomotion in challenging and unstructured environments. In this article, we present a computational method for augmenting soft robots with proprioceptive sensing capabilities. Our method automatically computes a stretch-receptive sensor network to user-provided soft robotic designs, which is optimized to perform well under a set of user-specified deformation-force pairs.

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