New out: Deep learning-based enzyme engineering toolkit “ALDELE”
Jiahui Zhou
Mar 11, 2024
1 min read
Updated: Apr 14, 2024
We are excited to present “ALDELE” (paper link), a comprehensive Deep Learning toolkit for guiding enzyme engineering. ALDELE is a milestone of our INSIGHT@ project in collaboration with Almac. It can be used to predict enzyme activities from sequences, identify the hot-spot regions of enzymes for engineering and predict substrate spectrum. For more details please refer to our ADELE paper published in Journal of Chemical Information and Modelling.
This sounds like a genuinely useful step for enzyme engineering, especially predicting activity directly from sequence rather than relying only on structural data. I have been working with directed evolution libraries and always wondered how much deep learning could reduce screening effort. By the way, when I need to label variants or annotate figures with symbols, I often use a greek letters copy and paste tool to keep notation consistent.
Really enjoyed reading "New out: Deep learning-based enzyme engineering toolkit “ALDELE”", and I liked how clear and grounded the writing felt. Appreciate you publishing this. check microphone