Litcius/Paper detail

A unified approach to sequential and non-sequential structure alignment of proteins, RNAs, and DNAs

Chengxin Zhang, Anna Marie Pyle

2022iScience15 citationsDOIOpen Access PDF

Abstract

Many distantly related structure pairs exhibit structural similarities that can only be fully captured by a non-sequential alignment program. We present US-align2, a unified protocol for both sequential and non-sequential alignment of proteins and nucleic acids. On manually curated reference alignments for protein structural pairs with non-sequential relations, US-align2 achieves ≥13% higher agreement with reference alignments than existing sequential and non-sequential alignment methods. Non-sequential alignments also enabled US-align2 to have higher sensitivities in detecting RNA pairs from the same family with sequence identities <40%, obtaining ≥9% higher area under the receiver operating characteristic curve than third-party programs. The unique ability of US-align2 to parse both proteins and nucleic acids allows the method to detect protein-RNA and protein-DNA mimicries. Additionally, US-align2 performs full and semi-non-sequential alignments with at least 48% and 14% faster speed than existing programs for the same tasks, making it particularly useful for large-scale structural similarity detection.

Topics & Concepts

Computer scienceComputational biologySequence (biology)Structural alignmentSequence alignmentNucleic acid structureNucleic acidMultiple sequence alignmentSimilarity (geometry)Protein structureAlgorithmRNAArtificial intelligenceBiologyGeneticsPeptide sequenceImage (mathematics)BiochemistryGeneRNA and protein synthesis mechanismsGenomics and Phylogenetic StudiesBacteriophages and microbial interactions