Benchmarking fold detection by DaliLite v.5 - PubMed (original) (raw)

Benchmarking fold detection by DaliLite v.5

Liisa Holm. Bioinformatics. 2019.

Abstract

Motivation: Protein structure comparison plays a fundamental role in understanding the evolutionary relationships between proteins. Here, we release a new version of the DaliLite standalone software. The novelties are hierarchical search of the structure database organized into sequence based clusters, and remote access to our knowledge base of structural neighbors. The detection of fold, superfamily and family level similarities by DaliLite and state-of-the-art competitors was benchmarked against a manually curated structural classification.

Results: Database search strategies were evaluated using Fmax with query-specific thresholds. DaliLite and DeepAlign outperformed TM-score based methods at all levels of the benchmark, and DaliLite outperformed DeepAlign at fold level. Hierarchical and knowledge-based searches got close to the performance of systematic pairwise comparison. The knowledge-based search was four times as efficient as the hierarchical search. The knowledge-based search dynamically adjusts the depth of the search, enabling a trade-off between speed and recall.

Availability and implementation: http://ekhidna2.biocenter.helsinki.fi/dali/README.v5.html.

Supplementary information: Supplementary data are available at Bioinformatics online.

© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

PubMed Disclaimer

Similar articles

Cited by

Publication types

MeSH terms

Substances

LinkOut - more resources