Conformational sampling and interpolation using language-based protein folding neural networks
Diego del Alamo,
Jeliazko R. Jeliazkov,
Daphné Truan
et al.
Abstract:Protein language models (PLMs), such ESM2, learn a rich semantic grammar of the protein sequence space. When coupled to protein folding neural networks (e.g., ESMFold), they can facilitate the prediction of tertiary and quaternary protein structures at high accuracy. However, they are limited to modeling protein structures in single states. This manuscript demonstrates that ESMFold can predict alternate conformations of some proteins, includingde novodesigned proteins. Randomly masking the sequence prior to PL… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.