GhostFold: Accurate protein structure prediction using structure-constrained synthetic coevolutionary signals.

ABSTRACT: The accuracy of protein structure prediction models such as AlphaFold2 is tightly coupled to the depth and quality of multiple sequence alignments (MSAs), posing a persistent challenge for proteins with few or no identifiable homologs. We present GhostFold, a method for conjuring structure-constrained synthetic MSAs from a single amino acid sequence, bypassing the need for traditional homology searches. Leveraging the ProstT5 protein language model and the 3Di structural alphabet, GhostFold projects a query sequence into a tokenized structural representation and iteratively back-translates to generate an ensemble of diverse, fold-consistent sequences. These synthetic alignments (pseudoMSAs) encode emergent coevolutionary constraints that are sufficient for high-accuracy struc

SUBMITTER: Mishra N 

PROVIDER: S-EPMC12633075 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature