ArticleBMC bioinformatics2010
A pairwise residue contact area-based mean force potential for discrimination of native protein structure.
Article in BMC bioinformatics, 2010. 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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Who cites it
7 citing papers in PubMed.
- Aminomethylmorpholino Nucleosides as Novel Inhibitors of PARP1 and PARP2: Experimental and Molecular Modeling Analyses of Their Selectivity and Mechanism of Action.International journal of molecular sciences · 2024Article
- Structure-conditioned amino-acid couplings: How contact geometry affects pairwise sequence preferences.Protein science : a publication of the Protein Society · 2022Article
- Identification of native protein structures captured by principal interactions.BMC bioinformatics · 2019Article
- Binding Direction-Based Two-Dimensional Flattened Contact Area Computing Algorithm for Protein-Protein Interactions.Molecules (Basel, Switzerland) · 2017Article
- Using the unfolded state as the reference state improves the performance of statistical potentials.Biophysical journal · 2012Article
- Self-complementarity within proteins: bridging the gap between binding and folding.Biophysical journal · 2012Article
- NCACO-score: an effective main-chain dependent scoring function for structure modeling.BMC bioinformatics · 2011Article
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Authors and funding
5 authors.
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Abstract
backgroundConsidering energy function to detect a correct protein fold from incorrect ones is very important for protein structure prediction and protein folding. Knowledge-based mean force potentials are certainly the most popular type of interaction function for protein threading. They are derived from statistical analyses of interacting groups in experimentally determined protein structures. These potentials are developed at the atom or the amino acid level. Based on orientation dependent contact area, a new type of knowledge-based mean force potential has been developed.
resultsWe developed a new approach to calculate a knowledge-based potential of mean-force, using pairwise residue contact area. To test the performance of our approach, we performed it on several decoy sets to measure its ability to discriminate native structure from decoys. This potential has been able to distinguish native structures from the decoys in the most cases. Further, the calculated Z-scores were quite high for all protein datasets.
conclusionsThis knowledge-based potential of mean force can be used in protein structure prediction, fold recognition, comparative modelling and molecular recognition. The program is available at http://www.bioinf.cs.ipm.ac.ir/softwares/surfield.
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