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Keyword: homology detection ×Clear all

2 claims from 1 paper

1. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

   DeepFold-PLM: accelerating protein structure prediction via efficient homology search using protein language models

   Kim, Bae, Jo et al. · Bioinformatics · 2025

   The authors present DeepFold-PLM, a framework combining protein language models with vector embedding databases to speed up sequence alignment, detect remote homologs and predict protein structures.

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   1. UncheckedDeepFold-PLM, which uses language-model embeddings and contrastive learning, builds MSAs 47 times faster than standard methods with accuracy comparable to AlphaFold.“DeepFold-PLM utilizes high-dimensional embeddings and contrastive learning, significantly accelerate MSA generation, achieving 47 times faster than standard methods, while maintaining prediction accuracy comparable to AlphaFold.”
   2. UncheckedDeepFold-PLM's alignments are reported to be more sequence-diverse than JackHMMER's (Neff 8.65 versus 4.83), adding coevolutionary information for structure prediction.“Our method also effectively increases sequence diversity (Neff = 8.65 versus 4.83 with JackHMMER) enriching coevolutionary information critical for accurate structure prediction.”