Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD

Abstract Sequence alignments are the foundation of life science research, but most innovation focused on optimal alignments, while ignoring information derived from suboptimal solutions. We argue that one optimal alignment per pairwise sequence comparison was a reasonable approximation when dealing with very similar sequences, but is insufficient when exploring the biodiversity of the protein universe at tree-of-life scale. To overcome this limitation, we introduce pairwise alignment-safety to uncover the amino acid positions robustly shared across all suboptimal solutions. We implemented this approach into EMERALD, a dedicated software solution for alignment-safety inference and apply it to 400k sequences from the SwissProt database.