ArticleComputational and mathematical methods in medicine2017
NSiteMatch: Prediction of Binding Sites of Nucleotides by Identifying the Structure Similarity of Local Surface Patches.
Article in Computational and mathematical methods in medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 9 citations in OpenAlex.
- An Updated Review of Computer-Aided Drug Design and Its Application to COVID-19.BioMed research international · 2021Review
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2 authors at 1 institution in 1 country.
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Abstract
Nucleotides play a central role in life-form metabolism, by interacting with proteins and mediating the function of proteins. It is estimated that nucleotides constitute about 15% of the biologically relevant ligands included in PDB. Prediction of binding sites of nucleotides is useful in understanding the function of proteins and can facilitate the in silico design of drugs. In this study, we propose a nucleotide-binding site predictor, namely, NSiteMatch. The NSiteMatch algorithm integrates three different strategies: geometrical analysis, energy calculation, and template comparison. Unlike a traditional template-based predictor, which identifies global similarity between target structure and template, NSiteMatch concerns the local similarity between a surface patch of the target protein and the binding sites of template. To this end, NSiteMatch identifies more templates than traditional template-based predictors. The NSiteMatch predictor is compared with three representative methods, Findsite, Q-SiteFinder, and MetaPocket. An extensive evaluation demonstrates that NSiteMatch achieves higher success rates than Findsite, Q-SiteFinder, and MetaPocket, in prediction of binding sites of ATP, ADP, and AMP.
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