首页|A learnable transition from low temperature to high temperature proteins with neural machine translation
A learnable transition from low temperature to high temperature proteins with neural machine translation
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2024 FEB 27 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – According to news reporting based on a preprint abstract, our journalists obtained the following quote sourced from biorxiv.org: “This work presents Neural Optimization for Melting-temperature Enabled by Leveraging Translation (NOMELT), a novel approach for designing and ranking high-temperature stable proteins using neural machine translation. The model, trained on over 4 million protein homologous pairs from organisms adapted to different temperatures, demonstrates promising capability in targeting thermal stability. “A designed variant of the Drosophila melanogaster Engrailed Homeodomain shows increased stability at high temperatures, as validated by estimators and molecular dynamics simulations.
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