Abstract
BackgroundThe fluctuation of atoms around their average positions in protein structures provides important information regarding protein dynamics. This flexibility of protein structures is associated with various biological processes. Predicting flexibility of residues from protein sequences is significant for analyzing the dynamic properties of proteins which will be helpful in predicting their functions.ResultsIn this paper, an approach of improving the accuracy of protein flexibility prediction is introduced. A neural network method for predicting flexibility in 3 states is implemented. The method incorporates sequence and evolutionary information, context-based scores, predicted secondary structures and solvent accessibility, and amino acid properties. Context-based statistical scores are derived, using the mean-field potentials approach, for describing the different preferences of protein residues in flexibility states taking into consideration their amino acid context.The 7-fold cross validated accuracy reached 61 % when context-based scores and predicted structural states are incorporated in the training process of the flexibility predictor.ConclusionsIncorporating context-based statistical scores with predicted structural states are important features to improve the performance of predicting protein flexibility, as shown by our computational results. Our prediction method is implemented as web service called “FLEXc” and available online at: http://hpcr.cs.odu.edu/flexc.
Highlights
The fluctuation of atoms around their average positions in protein structures provides important information regarding protein dynamics
Conformational changes driven by protein flexibility and dynamics are considered the basis of misfolding
The evolutionary information of protein sequences combined with the context-based flexibility scores, predicted structural features that we found to be correlated with flexibility, and amino acid properties enhanced the accuracy of our method by 8.4 % over the prediction with evolutionary information only
Summary
The fluctuation of atoms around their average positions in protein structures provides important information regarding protein dynamics. This flexibility of protein structures is associated with various biological processes. B-factors ( referred to as B-values, Debye-Waller factors, or temperature factors) reported in experimentally determined protein structures are commonly used to represent protein flexibility and its local mobility [18, 19]. They indicate both the static mobility, related. The values of the B-factors are usually between 15 to 30 Å2, and sometimes higher than 30 for more flexible regions
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