ArticlePloS one2011
Incorporation of local structural preference potential improves fold recognition.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Identification of novel salt tolerance-associated proteins from the secretome of Enterococcus faecalis.World journal of microbiology & biotechnology · 2022Article
- Heteromerization of μ-opioid receptor and cholecystokinin B receptor through the third transmembrane domain of the μ-opioid receptor contributes to the anti-opioid effects of cholecystokinin octapeptide.Experimental & molecular medicine · 2018Article
- Integrating computational modeling and functional assays to decipher the structure-function relationship of influenza virus PB1 protein.Scientific reports · 2014Article
- From local structure to a global framework: recognition of protein folds.Journal of the Royal Society, Interface · 2014Review
- Improvement in low-homology template-based modeling by employing a model evaluation method with focus on topology.PloS one · 2014Article
- Assessing protein conformational sampling methods based on bivariate lag-distributions of backbone angles.Briefings in bioinformatics · 2013Article
- Structure analysis of the extracellular domain reveals disulfide bond forming-protein properties of Mycobacterium tuberculosis Rv2969c.Protein & cell · 2013Article
- Article
- A position-specific distance-dependent statistical potential for protein structure and functional study.Structure (London, England : 1993) · 2012Article
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Authors and funding
6 authors.
Funding
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Abstract
Fold recognition, or threading, is a popular protein structure modeling approach that uses known structure templates to build structures for those of unknown. The key to the success of fold recognition methods lies in the proper integration of sequence, physiochemical and structural information. Here we introduce another type of information, local structural preference potentials of 3-residue and 9-residue fragments, for fold recognition. By combining the two local structural preference potentials with the widely used sequence profile, secondary structure information and hydrophobic score, we have developed a new threading method called FR-t5 (fold recognition by use of 5 terms). In benchmark testings, we have found the consideration of local structural preference potentials in FR-t5 not only greatly enhances the alignment accuracy and recognition sensitivity, but also significantly improves the quality of prediction models.
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