Lan, C.-Y. | bioRxiv Science

bioRxiv2024

MOLECULAR CHARACTERIZATION AND PROMOTER ELEMENT ANALYSIS OF GROWTH REGULATOR BRAGRF5 IN BRASSICA CAMPESTRIS L. SSP. CHINENSIS

The transcriptional regulation of eukaryotic gene expression is a critical aspect, with transcription factors playing a key role by combining with cis-acting elements in the promoter regions. Growth regulating factors (GRFs) are plant-specific transcriptional factors. The Arabidopsis thaliana growth-regulating factor gene (AtGRF5), when ectopically expressed in crops such as Beta vulgaris (sugar beet) and Brassica napus (canola), has an effect of accelerating shoot organogenesis and enhancing the efficiency of genetic transformation. However, an efficient plant regeneration and genetic transformation system in Brassica campestris L. ssp. chinensis, a major vegetable crop in China, remains to be established. In this work, we identified and characterized the AtGRF5 ortholog in B. campestris, named as BraGRF5, from BRAD database. Molecular analysis of BraGRF5 gene and exploration of its protein interaction network were further conducted. Therefore, the promoter region of BraGRF5 was thoroughly examined to determine cis-acting elements of various kinds and quantities. It is expected to provide a foundation for regulation of BraGRF5, and a informative reference for the improvement of B. campestris transformation efficiency and molecular breeding.

plant biology↗

bioRxiv2019

Data-Driven Design of Diagnostic Kits and Therapeutic Peptides

To ensure a physicochemically desired sequence motif to adapt a specific type of secondary structures, we compile an -helix database allowing complicate search patterns to facilitate a data-driven design of therapeutic peptides. Nearly 1.7 million helical peptides in >130 thousand proteins are extracted along with their interacting partners from the protein data bank (PDB). The sequences of the peptides are indexed with patterns and gaps and deposited in our Therapeutic Peptide Design dataBase (TP-DB). We here demonstrate its utility in three medicinal design cases. By our pattern-based search engine but not PHI-BLAST, we can identify a pathogenic protein, Helicobacter pylori neutrophil-activating protein (HP-NAP), a virulence factor of H. pylori, which contains a motif DYKYLE that belongs to the affinity determinant motif DYKXX[DE] of the FLAG-tag and can be recognized by the anti-FLAG M2 antibody. By doing so, the known purification-tag-specific antibody is repurposed into a diagnostic kit for H. pylori. Also by leveraging TP-DB, we discovered a stretch of helical peptide matching the potent membrane-insertion pattern WXXWXXW, elucidated by MD simulations. The newly synthesized peptide has a better minimal inhibitory concentration (MIC) and much lower cytotoxicity against Candida albicans (fungus) than that of previously characterized homologous antimicrobial peptides. In a similar vein, taking the discontinued anchoring residues in the helix-helix interaction interface as the search pattern, TP-DB returns several helical peptides as potential tumor suppressors of hepatocellular carcinoma (HCC) whose helicity and binding affinity were examined by MD simulations. Taken together, we believe that TP-DB and its pattern-based search engine provide a new opportunity for a (secondary-)structure-based design of peptide drugs and diagnostic kits for pathogens without inferring evolutionary homology between sequences sharing the same pattern. TP-DB is made available at http://dyn.life.nthu.edu.tw/design/.

bioinformatics↗