Integrated Web Interface for PPR Motif Discovery and Target Prediction in Plants

Pentatricopeptide repeat (PPR) proteins are pivotal regulators of organellar RNA metabolism. The PPR family comprises two major subfamilies, i.e., the P-type, involved in RNA stabilization and processing, and the PLS-type, primarily functioning as RNA editing factors. While PLS-type-predictive tools have already been well-established, specifically tailored software tools remain absent for P-type proteins, often forcing researchers to apply PLS-type models, being suboptimal when studying this group. I have developed the P-type PPR Prediction Program (PPPRPP), a cross-platform web application that integrates PPR motif discovery, RNA target-site scoring, and interactive visualization into a single user-friendly workflow. PPPRPP employs a scoring algorithm based on biophysical affinity data () and implements a gap-tolerant scanning mechanism to accommodate flexible binding modes characteristic of P-type proteins. Both P-type and PLS-type scoring schemes are available, allowing researchers to select the appropriate model for their target protein. By connecting motif identification, target prediction, and result visualization in a user-friendly graphical interface, PPPRPP facilitates candidate-site prioritization and functional characterization of the extensive PPR protein family.