Evidence map›Paper›PMID 26072475›Full record

ArticleBioinformatics (Oxford, England)2015

Finding optimal interaction interface alignments between biological complexes.

Xuefeng Cui, Hammad Naveed, Xin Gao

Abstract read
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Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xuefeng CuiComputer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.
Hammad NaveedComputer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.
Xin GaoComputer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationBiological molecules perform their functions through interactions with other molecules. Structure alignment of interaction interfaces between biological complexes is an indispensable step in detecting their structural similarities, which are key S: to understanding their evolutionary histories and functions. Although various structure alignment methods have been developed to successfully access the similarities of protein structures or certain types of interaction interfaces, existing alignment tools cannot directly align arbitrary types of interfaces formed by protein, DNA or RNA molecules. Specifically, they require a ': blackbox preprocessing ': to standardize interface types and chain identifiers. Yet their performance is limited and sometimes unsatisfactory.

resultsHere we introduce a novel method, PROSTA-inter, that automatically determines and aligns interaction interfaces between two arbitrary types of complex structures. Our method uses sequentially remote fragments to search for the optimal superimposition. The optimal residue matching problem is then formulated as a maximum weighted bipartite matching problem to detect the optimal sequence order-independent alignment. Benchmark evaluation on all non-redundant protein -: DNA complexes in PDB shows significant performance improvement of our method over TM-align and iAlign (with the ': blackbox preprocessing ': ). Two case studies where our method discovers, for the first time, structural similarities between two pairs of functionally related protein -: DNA complexes are presented. We further demonstrate the power of our method on detecting structural similarities between a protein -: protein complex and a protein -: RNA complex, which is biologically known as a protein -: RNA mimicry case. AVAILABILITY AND IMPLEMENTATION: The PROSTA-inter web-server is publicly available at http://www.cbrc.kaust.edu.sa/prosta/.

Indexed as

AlgorithmsBinding SitesDNADNA-Binding ProteinsModels, MolecularMolecular MimicryMultiprotein ComplexesNucleic Acid ConformationProtein ConformationRNARNA-Binding ProteinsSequence AlignmentSoftwareDNADNA-Binding ProteinsMultiprotein ComplexesRNARNA-Binding Proteins

Identifiers

PMID26072475
PMCPMC4765866

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LicenceCC BY-NC
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.