Helical structure motifs made searchable for functional peptide design

Abstract

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/.

Phosphate-binding protein-loaded iron oxide particles: adsorption performance for phosphorus removal and recovery from water

“…While the hinge motion is thus important, several studies provide substantial evidence supporting the feasibility of designing and synthesizing peptide sequences that leverage functional amino acid sequences derived from proteins. 64–66 For example, Fowler et al (2021) 67 demonstrated selective P i adsorption and controlled desorption using a protein-derived P i -binding peptide sequence approximately 37× smaller than the PBP tested in our study. Immobilization of such peptide sequences and testing their P i binding potential in a range of conditions relative to water/wastewater is important moving forward to further evaluate the adsorbent's abilities relative to other adsorbents.…”

Synthetic extracellular matrices with function-encoding peptides

“…Moreover, artificial intelligence and machine learning may offer an inverse (but complementary) approach, through which full-length protein structures can be analysed to identify new peptides. For example, secondary structures of nearly 2 million protein helices have been compared by a pattern-based search engine to identify and locate antimicrobial motifs and to provide design rules to control protein-protein interactions 221 . Similarly, a combination of machine learning and multivariate outlier detection models has helped to discover new non-haemolytic peptides and provide de novo design guidelines 222 .…”

Design of Protein Segments and Peptides for Binding to Protein Targets

“…The process of motif identification and extraction is slow and can be highly accelerated through the use of computational methods. For example, Tsai et al [29] recently created TP-DB (therapeutic peptide design database) that allows the users to search helical motifs that match a given sequence pattern. Their pattern-specific search engine is based on features derived from nearly 1.7 million helical structures extracted from PDB.…”