SkinPP: In Silico Prediction and Design of Skin Penetrating Peptides

SkinPP: In Silico Prediction and Design of Skin Penetrating Peptides SkinPP is a computational web server developed for predicting and designing efficient skin penetrating peptides, also known as SPPs. Skin penetrating peptides are short peptide sequences that can cross the skin barrier and may be useful as therapeutic agents or as delivery vehicles for drugs, peptides, proteins, and other bioactive molecules. SkinPP helps researchers identify, design, mutate, and analyze peptides with potential skin penetration ability. Web Server: https://webs.iiitd.edu.in/raghava/skinpp/ About the Research Skin is one of the most important barriers for drug delivery. Although topical and transdermal delivery are attractive because they are non-invasive and patient-friendly, many therapeutic molecules cannot efficiently penetrate the skin barrier. Skin penetrating peptides are useful because they can help transport therapeutic agents across the skin. These peptides may improve the delivery of drugs, peptides, proteins, and other therapeutic molecules. SkinPP was developed as an in silico method to predict and design skin penetrating peptides. The tool allows users to analyze peptide sequences, generate mutant analogues, scan full-length proteins, identify skin penetrating peptide motifs, and calculate physicochemical properties. Data Compilation: The dataset section of the server states that the dataset will be made available after publication. Methodology: SkinPP uses computational prediction approaches to classify peptides as skin penetrating or non-skin penetrating. The server also supports peptide design, mutation-based analogue generation, protein scanning, motif scanning, and physicochemical property calculation.