ArticleBMC bioinformatics2010
The LabelHash algorithm for substructure matching.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed.
- VirtuousPocketome: a computational tool for screening protein-ligand complexes to identify similar binding sites.Scientific reports · 2024Article
- pyScoMotif: discovery of similar 3D structural motifs across proteins.Bioinformatics advances · 2023Article
- A Conical Representation of Hydrogen Bond Geometry for Quantifying Bond Interactions.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2021Article
- Real-time structural motif searching in proteins using an inverted index strategy.PLoS computational biology · 2020Article
- Precise parallel volumetric comparison of molecular surfaces and electrostatic isopotentials.Algorithms for molecular biology : AMB · 2020Article
- Design and engineering of artificial oxygen-activating metalloenzymes.Chemical Society reviews · 2016Review
- Structure-guided selection of specificity determining positions in the human Kinome.BMC genomics · 2016Article
- Ensemble-based evaluation for protein structure models.Bioinformatics (Oxford, England) · 2016Article
- Artificial Diiron Enzymes with a De Novo Designed Four-Helix Bundle Structure.European journal of inorganic chemistry · 2015Article
- Rapid search for tertiary fragments reveals protein sequence-structure relationships.Protein science : a publication of the Protein Society · 2015Article
- Proteins comparison through probabilistic optimal structure local alignment.Frontiers in genetics · 2014Article
- Ballast: a ball-based algorithm for structural motifs.Journal of computational biology : a journal of computational molecular cell biology · 2013Article
- An aggregate analysis of many predicted structures to reduce errors in protein structure comparison caused by conformational flexibility.BMC structural biology · 2013Article
- Combinatorial clustering of residue position subsets predicts inhibitor affinity across the human kinome.PLoS computational biology · 2013Article
- Article
- BetaSearch: a new method for querying β-residue motifs.BMC research notes · 2012Article
- Modeling regionalized volumetric differences in protein-ligand binding cavities.Proteome science · 2012Article
- GIRAF: a method for fast search and flexible alignment of ligand binding interfaces in proteins at atomic resolution.Biophysics (Nagoya-shi, Japan) · 2012Article
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3 authors.
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Abstract
backgroundThere is an increasing number of proteins with known structure but unknown function. Determining their function would have a significant impact on understanding diseases and designing new therapeutics. However, experimental protein function determination is expensive and very time-consuming. Computational methods can facilitate function determination by identifying proteins that have high structural and chemical similarity.
resultsWe present LabelHash, a novel algorithm for matching substructural motifs to large collections of protein structures. The algorithm consists of two phases. In the first phase the proteins are preprocessed in a fashion that allows for instant lookup of partial matches to any motif. In the second phase, partial matches for a given motif are expanded to complete matches. The general applicability of the algorithm is demonstrated with three different case studies. First, we show that we can accurately identify members of the enolase superfamily with a single motif. Next, we demonstrate how LabelHash can complement SOIPPA, an algorithm for motif identification and pairwise substructure alignment. Finally, a large collection of Catalytic Site Atlas motifs is used to benchmark the performance of the algorithm. LabelHash runs very efficiently in parallel; matching a motif against all proteins in the 95% sequence identity filtered non-redundant Protein Data Bank typically takes no more than a few minutes. The LabelHash algorithm is available through a web server and as a suite of standalone programs at http://labelhash.kavrakilab.org. The output of the LabelHash algorithm can be further analyzed with Chimera through a plugin that we developed for this purpose.
conclusionsLabelHash is an efficient, versatile algorithm for large-scale substructure matching. When LabelHash is running in parallel, motifs can typically be matched against the entire PDB on the order of minutes. The algorithm is able to identify functional homologs beyond the twilight zone of sequence identity and even beyond fold similarity. The three case studies presented in this paper illustrate the versatility of the algorithm.
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