The systematic design of functional peptides has technological and therapeutic applications. However, there is a need for pattern-based search engines that help locate desired functional motifs in primary sequences regardless of their evolutionary conservation. Existing databases such as The Protein Secondary Structure database (PSS) no longer serves the community, while the Dictionary of Protein Secondary Structure (DSSP) annotates the secondary structures when tertiary structures of proteins are provided. Here, we extract 1.7 million helices from the PDB and compile them into a database (Therapeutic Peptide Design database; TP-DB) that allows queries of compounded patterns to facilitate the identification of sequence motifs of helical structures. We show how TP-DB helps us identify a known purification-tag-specific antibody that can be repurposed into a diagnostic kit for
Helicobacter pylori
. We also show how the database can be used to design a new antimicrobial peptide that shows better
Candida albicans
clearance and lower hemolysis than its template homologs. Finally, we demonstrate how TP-DB can suggest point mutations in helical peptide blockers to prevent a targeted tumorigenic protein-protein interaction. TP-DB is made available at
http://dyn.life.nthu.edu.tw/design/
.
Here, we present TP-DB; a pattern-based search engine based on 1.67 million helices from the Protein Database (PDB). We demonstrate the utility of TP-DB in identifying microbe-specific antigens, as well as the design of antimicrobial peptides and Protein-protein interaction blockers....

Helical structure motifs made searchable for functional peptide design

10.1038/s41467-021-27655-0