2026/01/01 by Ashar J. Malik, Siying Mao, Philip Hugenholtz +1 · 2 voices
Biochemistry, Genetics and Molecular Biology · Materials Science · #Protein Structure and Dynamics #Enzyme Structure and Function #Machine Learning in Materials Science
paper · doi:10.1093/gbe/evag004
Protein structure-based comparison provides a framework for uncovering deep evolutionary relationships that can escape conventional sequence-based approaches. Encoding three-dimensional protein structures using a simplified structure-aware alphabet can lead to compact, comparable strings that retain key spatial relationships. Although this enables comparison, structure-aware alignments can experience misaligned regions, particularly when comparing proteins with substantial divergence in fold architecture. To address this, a web-based resource, Structome-AlignViewer, is introduced in this work for evaluating the quality of structure-aware alignments through both spatial mapping of alignment columns to protein structures and quantitative confidence scoring. Confidence is computed from pairwise structural substitutions between adjacent inputs and normalized within each alignment to highlight relatively well-supported columns. To provide broader context, thousands of alignments from established structural classification systems were analyzed, allowing for an empirical comparative statistic to be derived to assess alignment quality. The option to exclude gap-rich regions enables users to refine alignments and focus on conserved structural cores. This approach provides an interpretable method for assessing structural alignment quality and supports more robust comparative and evolutionary analyses. Structome-AlignViewer is freely available at https://biosig.lab.uq.edu.au/structomealignviewer/.