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PLMSearch and PLMAlign: Protein Language Model (PLM)-Based Homologous Protein Sequence Search and Alignment
Wei Liu1,2, Ziye Wang1, Ronghui You1
1Institute of Science and Technology for Brain-Inspired Intelligence and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
Methods in Molecular Biology (Clifton, N.J.)
|July 2, 2025
Summary
We developed PLMSearch and PLMAlign, novel tools using protein language models (PLMs) for identifying and aligning distantly related protein sequences. These methods enhance evolutionary relationship inference beyond traditional sequence and structure searches.
Area of Science:
- Computational biology
- Bioinformatics
- Structural biology
Background:
- Homologous protein search and sequence alignment are crucial in computational biology.
- Inferring distant evolutionary relationships solely from sequences is challenging.
- Existing structure search methods offer insights but have limitations for sequence-only analysis.
Purpose of the Study:
- Introduce PLMSearch and PLMAlign, novel protein language model (PLM)-based tools.
- Enable accurate identification and alignment of remote homologous protein sequences.
- Advance the detection of evolutionary relationships using sequence data.
Main Methods:
- PLMSearch utilizes deep representations from pretrained PLMs for sequence-based homologous search.
- PLMAlign provides accurate sequence alignment for identified homologous pairs.
- Both tools leverage large datasets of real structure similarities for training and validation.
Main Results:
- PLMSearch effectively detects remote homologies from sequence data alone.
- PLMAlign accurately aligns homologous protein sequences.
- Web servers and open-source resources are provided for accessibility and further research.
Conclusions:
- PLMSearch and PLMAlign represent a significant advancement in protein sequence analysis.
- These PLM-based tools improve the detection of distant evolutionary relationships.
- The freely available resources facilitate broader adoption and scientific discovery.
