GPU-accelerated homology search with MMseqs2

Journal article

Rapidly growing protein databases demand faster sensitive search tools. Here the graphics processing unit (GPU)-accelerated MMseqs2 delivers 6× faster single-protein searches than CPU methods on 2 × 64 cores, speeds previously requiring large protein batches. For larger query batches, it is the most cost-effective solution, outperforming the fastest alternative method by 2.4-fold with eight GPUs. It accelerates protein structure prediction with ColabFold 31.8× over the standard AlphaFold2 pipeline and protein structure search with Foldseek by 4–27×. MMseqs2-GPU is available under an open-source license at https://mmseqs.com/.

Authors: Kallenborn, F; Chacon, A; Hundt, C; Sirelkhatim, H; Didi, K

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Nature Research
• Journal: Nature Methods
• Volume: 22
• Issue: 10
• Pages: 2024-2027
• Publication date: 2025-09-18
• Acceptance date: 2025-08-14
• DOI: 10.1038/s41592-025-02819-8
• EISSN: 1548-7105
• ISSN: 1548-7091
• Language: English