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.