Work

LoL-align: sensitive and fast probabilistic protein structure alignment

Year: 2026

Type: article

Abstract: The ubiquitous availability of protein structures permits replacing sequence alignment with more accurate and sensitive structure alignment algorithms. LoL-align maximizes a local log-odds score for proteins to be homologous, given their intra-protein C α − C α distances. Here we show that LoL-align is markedly more sensitive in detecting remote homologs than TM-align and Dali on single- and multidomain benchmarks and achieves better alignment quality at 5–20 × their speed. LoL-align is fully integrated into Foldseek.

Source: Nature Methods

DOI: 10.1038/s41592-026-03249-w

Authors: Lasse Reifenrath, Michel van Kempen, Gyuri Kim, Soo Hyun Kim, Mohammadreza Radnezhad, Cameron L. M. Gilchrist, Milot Mirdita, Martin Steinegger, Johannes Söding

Institutions: Max Planck Institute for Multidisciplinary Sciences, Seoul National University, Korea Basic Science Institute, Sungkyunkwan University, Campus-Institut Data Science (CIDAS)

Language: English

Topic: Protein Structure and Dynamics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: hybrid

Estimated APC paid: $12,690

Funders: Deutsche Forschungsgemeinschaft, Korea Basic Science Institute, National Research Foundation of Korea, Max-Planck-Gesellschaft, Novo Nordisk, Ministry of Science and ICT, South Korea

Awards: G1210678535, G1620819194, G230658605, G3432363212, G3812690899, G3987779410, G6096856274, G6520972873, G6556642110, G667447399, G6721392810, G7538056602, G762962293, G765433051, G8625565407, G9001177570, G9001291700

OpenAlex ID: W7221754960

FWCI:

Cites: 21

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