GPU-accelerated homology search with MMseqs2.

Kallenborn, Felix; Chacon, Alejandro; Hundt, Christian; Sirelkhatim, Hassan; Didi, Kieran; Cha, Sooyoung; Dallago, Christian; Mirdita, Milot et al. · Nat Methods · 2025

basic_science · Level V

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Abstract

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/ .

Medical subject headings