Computational tools for the analysis of protein data and the prediction of biological properties are essential in life sciences and biomedical research. Here, we introduce ProtDCal-Suite, a web server comprising a set of machine learning-based methods for studying proteins. The main module of ProtDCal-Suite is the ProtDCal software. ProtDCal translates the structural information of proteins into numerical descriptors that serve as input to machine-learning techniques. The ProtDCal-Suite server also incorporates a post-processing optional stage that allows ranking and filtering the obtained descriptors by computing their Shannon entropy values across the input set of proteins. ProtDCal's codification was used in the development of models for the prediction of specific protein properties. Thus, the other modules of ProtDCal-Suite are protein analysis tools implemented using ProtDCal's descriptors. Among them are PPI-Detect, for predicting the interaction likelihood of protein–protein and protein–peptide pairs, Enzyme Identifier, for identifying enzymes from amino acid sequences or 3D structures, and Pred-NGlyco, for predicting N-glycosylation sites. ProtDCal-Suite is freely accessible at https://protdcal.zmb.uni-due.de.

Additional Metadata
Keywords descriptor, enzymes, machine-learning, N-glycosylation, protein–protein interactions, web server
Persistent URL dx.doi.org/10.1002/pro.3673
Journal Protein Science
Citation
Romero-Molina, S. (Sandra), Ruiz-Blanco, Y.B. (Yasser B.), Green, J, & Sanchez-Garcia, E. (Elsa). (2019). ProtDCal-Suite: A web server for the numerical codification and functional analysis of proteins. Protein Science, 28(9), 1734–1743. doi:10.1002/pro.3673