Scientists develop new method to generate protein datasets for training AI

For decades, the existence of the hydrophobic core, a region in the 3D structure of proteins where hydrophobic amino acids reside together, has been considered a general property in proteins. What we have found now may extend that model. In particular, the rest of amino acids also seem to cluster together according to their chemical type (polar, acidic, basic, special), specifically in groups of ~8 units. This is what we have come to call the Mosaic Q model. Here is how we found it, along with tools for its quantification and visualization. The post Proteins: A Mosaic Pattern to Rule Them All? appeared first on Towards Data Science.

Using AI tools, the team reworked part of the ribosome to need one less amino acid.

Founded by Tristan Bepler PhD ’20 and former MIT professor Tim Lu PhD ’07, OpenProtein.AI offers researchers open-source models and other tools for protein engineering.