MOTIVATION: 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.

MOTIVATION: Accurate alignments between entire genomes are crucial for comparative genomics. However, computing sensitive and accurate genome alignments is a challenging problem, complicated by genomic rearrangements. RESULTS: Here we present a fast approach, called chainCleaner, that improves the specificity in genome alignments by accurately detecting and removing local alignments that obscure the evolutionary history of genomic rearrangements. Systematic tests on alignments between the human and other vertebrate genomes show that chainCleaner (i) improves the alignment of numerous orthologous genes, (ii) exposes alignments between exons of orthologous genes that were masked before by alignments to pseudogenes, and (iii) recovers hundreds of kilobases in local alignments that otherwise would fall below a minimum score threshold. Our approach has broad applicability to improve the sensitivity and specificity of genome alignments. AVAILABILITY AND IMPLEMENTATION: http://bds.mpi-cbg.de/hillerlab/chainCleaner/ or https://github.com/ucscGenomeBrowser/kent. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.