ArticleProteins2012
A new size-independent score for pairwise protein structure alignment and its application to structure classification and nucleic-acid binding prediction.
Article in Proteins, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 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
- Exploring the protein universe with distant similarity detection methods.Protein science : a publication of the Protein Society · 2026Review
- epLSAP-Align: a non-sequential protein structural alignment solver with entropy-regularized partial linear sum assignment problem formulation.Bioinformatics (Oxford, England) · 2025Article
- DRBP-EDP: classification of DNA-binding proteins and RNA-binding proteins using ESM-2 and dual-path neural network.NAR genomics and bioinformatics · 2025Article
- RBProkCNN: Deep learning on appropriate contextual evolutionary information for RNA binding protein discovery in prokaryotes.Computational and structural biotechnology journal · 2024Article
- DeepProSite: structure-aware protein binding site prediction using ESMFold and pretrained language model.Bioinformatics (Oxford, England) · 2023Article
- Identifying B-cell epitopes using AlphaFold2 predicted structures and pretrained language model.Bioinformatics (Oxford, England) · 2023Article
- A unified approach to sequential and non-sequential structure alignment of proteins, RNAs, and DNAs.iScience · 2022Article
- US-align: universal structure alignments of proteins, nucleic acids, and macromolecular complexes.Nature methods · 2022Article
- RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins.Briefings in bioinformatics · 2022Article
- Ribonomics Approaches to Identify RBPome in Plants and Other Eukaryotes: Current Progress and Future Prospects.International journal of molecular sciences · 2022Review
- Evidence for the emergence of β-trefoils by 'Peptide Budding' from an IgG-like β-sandwich.PLoS computational biology · 2022Article
- GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteins.BioImpacts : BI · 2021Article
- Non-sequential protein structure alignment by conformational space annealing and local refinement.PloS one · 2019Article
- Deep-RBPPred: Predicting RNA binding proteins in the proteome scale based on deep learning.Scientific reports · 2018Article
- YesU from Bacillus subtilis preferentially binds fucosylated glycans.Scientific reports · 2018Article
- Glycointeractions in bacterial pathogenesis.Nature reviews. Microbiology · 2018Review
- Grid-based prediction of torsion angle probabilities of protein backbone and its application to discrimination of protein intrinsic disorder regions and selection of model structures.BMC bioinformatics · 2018Article
- Systems-level understanding of ethanol-induced stresses and adaptation in E. coli.Scientific reports · 2017Article
- Correlation of fitness landscapes from three orthologous TIM barrels originates from sequence and structure constraints.Nature communications · 2017Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
A structure alignment program aligns two structures by optimizing a scoring function that measures structural similarity. It is highly desirable that such scoring function is independent of the sizes of proteins in comparison so that the significance of alignment across different sizes of the protein regions aligned is comparable. Here, we developed a new score called SP-score that fixes the cutoff distance at 4 Å and removed the size dependence using a normalization prefactor. We further built a program called SPalign that optimizes SP-score for structure alignment. SPalign was applied to recognize proteins within the same structure fold and having the same function of DNA or RNA binding. For fold discrimination, SPalign improves sensitivity over TMalign for the chain-level comparison by 12% and over DALI for the domain-level comparison by 13% at the same specificity of 99.6%. The difference between TMalign and SPalign at the chain level is due to the inability of TMalign to detect single domain similarity between multidomain proteins. For recognizing nucleic acid binding proteins, SPalign consistently improves over TMalign by 12% and DALI by 31% in average value of Mathews correlation coefficients for four datasets. SPalign with default setting is 14% faster than TMalign. SPalign is expected to be useful for function prediction and comparing structures with or without domains defined. The source code for SPalign and the server are available at http://sparks.informatics.iupui.edu.
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Registered trials
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.