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

ABSTRACT:

Motivation

Protein structure prediction has been revolutionized and generalized with the advent of cutting-edge AI methods such as AlphaFold, but reliance on computationally intensive multiple sequence alignments (MSA) remains a major limitation.

Results

We introduce DeepFold-PLM, a novel framework that integrates advanced protein language models with vector embedding databases to enhance ultra-fast MSA construction, remote homology detection, and protein structure prediction. 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. In addition, it enhances structure prediction by extending modeling capabi

SUBMITTER: Kim M 

PROVIDER: S-EPMC12598648 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature