ArticleProteins2012
Structural features that predict real-value fluctuations of globular proteins.
Article in Proteins, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 35 citations in OpenAlex.
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- Unveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approach.Scientific reports · 2025Article
- Modeling protein-nucleic acid complexes with extremely large conformational changes using Flex-LZerD.Proteomics · 2023Article
- Classification of protein-protein association rates based on biophysical informatics.BMC bioinformatics · 2021Article
- Computationally identifying hot spots in protein-DNA binding interfaces using an ensemble approach.BMC bioinformatics · 2020Article
- Analysis of protein missense alterations by combining sequence- and structure-based methods.Molecular genetics & genomic medicine · 2020Article
- Investigation of the Relationship between the S1 Domain and Its Molecular Functions Derived from Studies of the Tertiary Structure.Molecules (Basel, Switzerland) · 2019Article
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- Ensemble-based evaluation for protein structure models.Bioinformatics (Oxford, England) · 2016Article
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- Structure and stability of recombinant bovine odorant-binding protein: II. Unfolding of the monomeric forms.PeerJ · 2016Article
- CABS-flex predictions of protein flexibility compared with NMR ensembles.Bioinformatics (Oxford, England) · 2014Article
- CABS-flex: Server for fast simulation of protein structure fluctuations.Nucleic acids research · 2013Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics (MD) trajectories of nonhomologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real value of residue fluctuations using the support vector regression (SVR). It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in MD trajectories. Moreover, SVR that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson's correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed in predictions by the Gaussian network model (GNM). An advantage of the developed method over the GNMs is that the former predicts the real value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.