ArticleBMC bioinformatics2013
MICAN: a protein structure alignment algorithm that can handle Multiple-chains, Inverse alignments, C(α) only models, Alternative alignments, and Non-sequential alignments.
Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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29 citing papers in PubMed.
- A graphic and command line protocol for quick and accurate comparisons of protein and nucleic acid structures with US-align.Nature protocols · 2026Review
- epLSAP-Align: a non-sequential protein structural alignment solver with entropy-regularized partial linear sum assignment problem formulation.Bioinformatics (Oxford, England) · 2025Article
- Design of complicated all-α protein structures.Nature structural & molecular biology · 2024Article
- Isolation and Characterization of Neutralizing Monoclonal Antibodies from a Large Panel of Murine Antibodies against RBD of the SARS-CoV-2 Spike Protein.Antibodies (Basel, Switzerland) · 2024Article
- Design of allosteric sites into rotary motor VNature chemistry · 2023Article
- BeEM: fast and faithful conversion of mmCIF format structure files to PDB format.BMC bioinformatics · 2023Article
- PDC: a highly compact file format to store protein 3D coordinates.Database : the journal of biological databases and curation · 2023Article
- Prediction of chaperonin GroE substrates using small structural patterns of proteins.FEBS open bio · 2023Article
- MeDBA: the Metalloenzyme Data Bank and Analysis platform.Nucleic acids research · 2023Article
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- Distinct mutations in importin-β family nucleocytoplasmic transport receptors transportin-SR and importin-13 affect specific cargo binding.Scientific reports · 2021Article
- AncPhore: A versatile tool for anchor pharmacophore steered drug discovery with applications in discovery of new inhibitors targeting metallo-Acta pharmaceutica Sinica. B · 2021Article
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- De novo design of potent and resilient hACE2 decoys to neutralize SARS-CoV-2.Science (New York, N.Y.) · 2020Article
- An ancient evolutionary connection between Ribonuclease A and EndoU families.RNA (New York, N.Y.) · 2020Article
- Article
- Non-sequential protein structure alignment by conformational space annealing and local refinement.PloS one · 2019Article
- Rules for connectivity of secondary structure elements in protein: Two-layer αβ sandwiches.Protein science : a publication of the Protein Society · 2017Article
- An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes.Scientific reports · 2017Article
- Landscape of protein-small ligand binding modes.Protein science : a publication of the Protein Society · 2016Article
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3 authors.
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Abstract
backgroundProtein pairs that have the same secondary structure packing arrangement but have different topologies have attracted much attention in terms of both evolution and physical chemistry of protein structures. Further investigation of such protein relationships would give us a hint as to how proteins can change their fold in the course of evolution, as well as a insight into physico-chemical properties of secondary structure packing. For this purpose, highly accurate sequence order independent structure comparison methods are needed.
resultsWe have developed a novel protein structure alignment algorithm, MICAN (a structure alignment algorithm that can handle Multiple-chain complexes, Inverse direction of secondary structures, Cα only models, Alternative alignments, and Non-sequential alignments). The algorithm was designed so as to identify the best structural alignment between protein pairs by disregarding the connectivity between secondary structure elements (SSE). One of the key feature of the algorithm is utilizing the multiple vector representation for each SSE, which enables us to correctly treat bent or twisted nature of long SSE. We compared MICAN with other 9 publicly available structure alignment programs, using both reference-dependent and reference-independent evaluation methods on a variety of benchmark test sets which include both sequential and non-sequential alignments. We show that MICAN outperforms the other existing methods for reproducing reference alignments of non-sequential test sets. Further, although MICAN does not specialize in sequential structure alignment, it showed the top level performance on the sequential test sets. We also show that MICAN program is the fastest non-sequential structure alignment program among all the programs we examined here.
conclusionsMICAN is the fastest and the most accurate program among non-sequential alignment programs we examined here. These results suggest that MICAN is a highly effective tool for automatically detecting non-trivial structural relationships of proteins, such as circular permutations and segment-swapping, many of which have been identified manually by human experts so far. The source code of MICAN is freely download-able at http://www.tbp.cse.nagoya-u.ac.jp/MICAN.
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