Assignment of Protein Secondary Structure Elements from Cα Backbone Trace: An Ensemble of Machine Learning Approaches

Secondary structure elements in protein molecules refer to local sub-conformational regions stabilized by hydrogen bonding. Assigning Secondary Structure Elements is crucial in protein structure determination and function analysis. This work represents a recast of a previously developed classifier using ensemble of machine learning models. In this paper, we introduce new geometrical features to improve the accuracy, reduce training data set and process, and we develop and apply a post-processing step. The classifier is trained with 150K amino acids. We tested our classifier on a set of 20 protein structures and compared with previously developed classifier. The information from Protein Data Bank was used as a reference. The comparison shows that new method can produce assignments that are more aligned with PDB at 95.31% accuracy after applying a simple postprocessing step compared to 92.75% for the previous classifier.