Ankh‐Score Produces Better Sequence Alignments Than <scp>AlphaFold3</scp>

ABSTRACT Protein sequence alignment is one of the most fundamental procedures in bioinformatics. Due to its many downstream applications, improvements to this procedure are of great importance. We consider two revolutionary concepts that emerged recently as candidates for improving the state‐of‐the‐art alignment methods: AlphaFold and protein language models such as Ankh, ProtT5, or ESM‐C. Alignment improvements can come from the structural alignment of AlphaFold‐predicted structures or the scoring based on the similarity of protein embeddings produced by the protein language models. Thorough comparison on many domains from BAliBASE and CDD demonstrates that the Ankh‐score method produces much better sequence alignments than the structural alignments using US‐align of AlphaFold3‐predicted structures. Both are better than the traditional method using BLOSUM matrices. This suggests that Ankh embeddings may possess certain information that is not available in the AlphaFold3‐predicted structures. The alignment software is freely available as a web server at e‐score.csd.uwo.ca and as source code at github.com/lucian‐ilie/E‐score .