Obtaining extremely large and accurate protein multiple sequence alignments from curated hierarchical alignments.

ABSTRACT: For optimal performance, machine learning methods for protein sequence/structural analysis typically require as input a large multiple sequence alignment (MSA), which is often created using query-based iterative programs, such as PSI-BLAST or JackHMMER. However, because these programs align database sequences using a query sequence as a template, they may fail to detect or may tend to misalign sequences distantly related to the query. More generally, automated MSA programs often fail to align sequences correctly due to the unpredictable nature of protein evolution. Addressing this problem typically requires manual curation in the light of structural data. However, curated MSAs tend to contain too few sequences to serve as input for statistically based methods. We address these shortcomings

SUBMITTER: Neuwald AF 

PROVIDER: S-EPMC7297217 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature