ArticleThe Journal of membrane biology2014
Automated procedure for contact-map-based protein structure reconstruction.
Article in The Journal of membrane biology, 2014. 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, 19 citations in OpenAlex.
- StructureDistiller: Structural relevance scoring identifies the most informative entries of a contact map.Scientific reports · 2019Article
- Automated method to differentiate between native and mirror protein models obtained from contact maps.PloS one · 2018Article
- Forecasting residue-residue contact prediction accuracy.Bioinformatics (Oxford, England) · 2017Article
- NeBcon: protein contact map prediction using neural network training coupled with naïve Bayes classifiers.Bioinformatics (Oxford, England) · 2017Article
- Applying PyRosetta molecular energies to separate properly oriented protein models from mirror models, obtained from contact maps.Journal of molecular modeling · 2016Article
- Article
- MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins.Bioinformatics (Oxford, England) · 2015Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Knowledge of the three-dimensional structures of ion channels allows for modeling their conductivity characteristics using biophysical models and can lead to discovering their cellular functionality. Recent studies show that quality of structure predictions can be significantly improved using protein contact site information. Therefore, a number of procedures for protein structure prediction based on their contact-map have been proposed. Their comparison is difficult due to different methodologies used for validation. In this work, a Contact Map-to-Structure pipeline (C2S_pipeline) for contact-based protein structure reconstruction is designed and validated. The C2S_pipeline can be used to reconstruct monomeric and multimeric proteins. The median RMSD of structures obtained during validation on a representative set of protein structures, equaled 5.27 Å, and the best structure was reconstructed with RMSD of 1.59 Å. The validation is followed by a detailed case study on the KcsA ion channel. Models of KcsA are reconstructed based on different portions of contact site information. Structural feature analysis of acquired KcsA models is supported by a thorough analysis of electrostatic potential distributions inside the channels. The study shows that electrostatic parameters are correlated with structural quality of models. Therefore, they can be used to discriminate between high and low quality structures. We show that 30 % of contact information is needed to obtain accurate structures of KcsA, if contacts are selected randomly. This number increases to 70 % in case of erroneous maps in which the remaining contacts or non-contacts are changed to the opposite. Furthermore, the study reveals that local reconstruction accuracy is correlated with the number of contacts in which amino acid are involved. This results in higher reconstruction accuracy in the structure core than peripheral regions.
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