ArticleScientific reports2016
Network measures for protein folding state discrimination.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- The protein folding rate and the geometry and topology of the native state.Scientific reports · 2022Article
- Network theory reveals principles of spliceosome structure and dynamics.Structure (London, England : 1993) · 2022Article
- Validation and quality assessment of macromolecular structures using complex network analysis.Scientific reports · 2019Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Proteins fold using a two-state or multi-state kinetic mechanisms, but up to now there is not a first-principle model to explain this different behavior. We exploit the network properties of protein structures by introducing novel observables to address the problem of classifying the different types of folding kinetics. These observables display a plain physical meaning, in terms of vibrational modes, possible configurations compatible with the native protein structure, and folding cooperativity. The relevance of these observables is supported by a classification performance up to 90%, even with simple classifiers such as discriminant analysis.
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Registered trials
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