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 (Kd) 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 candidatesite prioritization and functional characterization of the extensive PPR protein family.
