VenomFlow
VenomFlow identifies and characterizes disulfide-rich, cysteine-rich peptide toxins from raw RNAseq reads of venom glands to enable study of venom components that manipulate molecular targets such as ion channels and receptors.
Key Features:
- Automated pipeline: Automates identification and characterization of disulfide-rich peptides from sequencing data.
- De novo identification: Enables de novo discovery of previously uncharacterized cysteine-rich peptides directly from raw RNAseq reads.
- Integration of transcriptomic, proteomic and bioinformatic methods: Leverages transcriptomic analysis, proteomic methods, and bioinformatic techniques to detect and characterize venom peptides.
- Versatility: Applicable to venomous terebrid snails and adaptable to identify secreted disulfide-rich peptide toxins from other venomous organisms.
Scientific Applications:
- Toxinology: Identification and characterization of venom arsenals and cysteine-rich peptide toxins that target ion channels and receptors.
- Pharmacology and drug discovery: Discovery of bioactive peptides as potential therapeutic agents and leads for drug development.
Methodology:
Processes raw RNAseq reads from venom glands using transcriptomic and bioinformatic analyses and integrates proteomic methods to identify and characterize cysteine-rich, disulfide-rich peptides.
Topics
Details
- License:
- Not licensed
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- Python
- Added:
- 8/29/2022
- Last Updated:
- 11/24/2024
Operations
Publications
Achrak E, Ferd J, Schulman J, Dang T, Krampis K, Holford M. VenomFlow: An Automated Bioinformatic Pipeline for Identification of Disulfide-Rich Peptides from Venom Arsenals. Methods in Molecular Biology. 2022. doi:10.1007/978-1-0716-2313-8_6. PMID:35727542.
PMID: 35727542