Baltzis, AthanasiosMansouri, LeilaJin, SuzanneLanger, Björn E.Erb, IonasNotredame, Cedric2023-01-202023-01-202022Baltzis A, Mansouri L, Jin S, Langer BE, Erb I, Notredame C. Highly significant improvement of protein sequence alignments with AlphaFold2. Bioinformatics. 2022 Nov 15;38(22):5007-11. DOI: 10.1093/bioinformatics/btac6251367-4803http://hdl.handle.net/10230/55346Motivation: Protein sequence alignments are essential to structural, evolutionary and functional analysis, but their accuracy is often limited by sequence similarity unless molecular structures are available. Protein structures predicted at experimental grade accuracy, as achieved by AlphaFold2, could therefore have a major impact on sequence analysis. Results: Here, we find that multiple sequence alignments estimated on AlphaFold2 predictions are almost as accurate as alignments estimated on experimental structures and significantly closer to the structural reference than sequence-based alignments. We also show that AlphaFold2 structural models of relatively low quality can be used to obtain highly accurate alignments. These results suggest that, besides structure modeling, AlphaFold2 encodes higher-order dependencies that can be exploited for sequence analysis. Availability and implementation: All data, analyses and results are available on Zenodo (https://doi.org/10.5281/zenodo.7031286). The code and scripts have been deposited in GitHub (https://github.com/cbcrg/msa-af2-nf) and the various containers in (https://cloud.sylabs.io/library/athbaltzis/af2/alphafold, https://hub.docker.com/r/athbaltzis/pred). Supplementary information: Supplementary data are available at Bioinformatics online.application/pdfeng© The Author(s) 2022. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.cominfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1093/bioinformatics/btac625info:eu-repo/semantics/openAccess