CPPsite

CPPsite catalogs experimentally validated cell-penetrating peptides (CPPs) and their structural and functional annotations to support CPP prediction, design, and the study of cargo delivery across cellular membranes.

Key Features:

• Dataset size: 1855 experimentally validated CPP entries with detailed annotations.
• Peptide types: Includes linear and cyclic CPPs and peptides containing modified and non-natural residues.
• Cargo types: Records CPP-mediated delivery of nucleic acids, proteins, nanoparticles, and peptide nucleic acids (PNA).
• Structural annotations: Contains secondary and tertiary structure information for entries to support structure–function analysis.
• Molecular and physicochemical annotations: Provides amino acid composition, hydrophobicity, and other physicochemical properties for each peptide.
• Biological annotations: Captures chirality, origin, natural versus synthetic status, sub-cellular localization, uptake mechanism, and uptake efficiency.
• Computational integration: Integrates with prediction/design tools including CellPPD and CPPpred to support in silico CPP prediction and design.
• Method development support: Supplies curated datasets suitable for development and benchmarking of new CPP prediction methods.

Scientific Applications:

• Cargo delivery studies: Enables analysis of CPP-mediated delivery mechanisms for nucleic acids, proteins, nanoparticles, and PNA.
• CPP design and prediction: Supports in silico prediction and rational design of novel CPPs prior to experimental testing.
• Structure–function analysis: Facilitates investigation of relationships between peptide structure (secondary/tertiary) and cellular uptake or efficacy.
• Algorithm development and benchmarking: Provides curated data for training, testing, and benchmarking CPP prediction algorithms such as CellPPD and CPPpred.

Methodology:

Curation of experimentally validated CPP entries annotated with sequence, chirality, origin, natural/synthetic status, amino acid composition, hydrophobicity, physicochemical properties, sub-cellular localization, uptake mechanism and efficiency, and secondary/tertiary structure annotations, with integration of datasets into computational prediction/design tools CellPPD and CPPpred.