ConoDictor

A fast and accurate prediction and classification tool for conopeptides

🗺️ Overview

Unlocking the Potential of Cone Snail Venom

Cone snails are a treasure trove of natural peptides with immense pharmacological and therapeutic potential. The advent of affordable RNA sequencing (RNAseq) has revolutionized the mining of novel bioactive conopeptides from venom gland transcriptomes. However, the complexity of bioinformatic analyses often impedes the discovery process.

Introducing ConoDictor 2

ConoDictor 2 is a standalone, user-friendly command-line tool designed to streamline the discovery of conopeptides. Building on a decade-old web server, we have significantly upgraded ConoDictor with modern tools and algorithms, and enhanced our classification models using new, high-quality sequences. The result is a program that is more accurate, faster, and compatible across multiple platforms.

Key Features

• Enhanced Accuracy and Speed: ConoDictor 2 processes entire venom gland transcriptomes, whether from raw reads or assembled contigs, in record time.
• Ease of Use: The program requires only the assembled transcriptome or raw reads file, in either DNA or amino acid format. ConoDictor 2 automatically recognizes the alphabet used.
• Advanced Prediction Capabilities: It runs predictions directly on the submitted or dynamically generated proteins file, aiming to identify the longest conopeptide precursor-like sequences.

Simplified Bioinformatics for Breakthrough Discoveries

With ConoDictor 2, researchers can bypass the intricate bioinformatic challenges and focus on uncovering the next generation of bioactive peptides from cone snail venom. Its robust performance and user-centric design make it an indispensable tool in venom research and drug discovery.

Installing

Install from Pip

You will first have to install HMMER 3 and Pftools to be able to run conodictor (as of version 2.4, conodictor does not need hmmer anymore as it use the wonderful pyhmmer library).

pip install conodictor

Using containers

Docker

Accessible at https://hub.docker.com/u/ebedthan or on BioContainers.

docker pull ebedthan/conodictor:latest
docker run ebedthan/conodictor:latest conodictor -h

Example of a run

docker run --rm=True -v $PWD:/data -u $(id -u):$(id -g) ebedthan/conodictor:latest conodictor --out /data/outdir /data/input.fa.gz

See https://staph-b.github.io/docker-builds/run_containers/ for more informations on how to properly run a docker container.

Singularity

The singularity container does not need admin privileges making it suitable for university clusters and HPC.

singularity build conodictor.sif docker://ebedthan/conodictor:latest
singularity exec conodictor.sif conodictor -h

Install from source

# Download ConoDictor development version
git clone https://github.com/koualab/conodictor.git conodictor

# Navigate to directory
cd conodictor

# Install with poetry: see https://python-poetry.org
poetry install --no-dev

# Enter the Python virtual environment with
poetry shell

# Test conodictor is correctly installed
conodictor -h

If you do not want to go into the virtual environment just do:

poetry run conodictor -h

💡 Example

conodictor file.fa.gz
conodictor --out outfolder --cpus 4 --mlen 51 file.fa

Output files

The comma separeted-values file summary.csv can be easily viewed with any office suite, or text editor.

sequence,hmm_pred,pssm_pred definitive_pred
SEQ_ID_1,A,A,A
SEQ_ID_2,B,D,CONFLICT B and D
SEQ_ID_3,O1,O1,O1
...

💭 Feedback

Issue tracker

Found a bug ? Have an enhancement request ? Head over to the GitHub issue tracker if you need to report or ask something. If you are filing in on a bug, please include as much information as you can about the issue, and try to recreate the same bug in a simple, easily reproducible situation.

⚖️ License

GPL v3.

For commercial uses please contact Dominique Koua at [email protected].

🔖 Citation

ConoDictor is a scientifc software, with a published paper in the Bioinformatics Advances journal. Please cite this article if you are using it in an academic work, for instance as: Koua, D., Ebou, A., & Dutertre, S. (2021). Improved prediction of conopeptide superfamilies with ConoDictor 2.0. Bioinformatics Advances, 1(1), vbab011. https://doi.org/10.1093/bioadv/vbab011

Dependencies

• Pftools
  Used for PSSM prediction.
  Schuepbach P et al. pfsearchV3: a code acceleration and heuristic to search PROSITE profiles. Bioinformatics 2013, 10.1093/bioinformatics/btt129

📚 References

• HMMER 3
  Used for HMM profile prediction.
  Eddy SR, Accelerated Profile HMM Searches. PLOS Computational Biology 2011, 10.1371/journal.pcbi.1002195

• Pftools
  Used for PSSM prediction.
  Schuepbach P et al. pfsearchV3: a code acceleration and heuristic to search PROSITE profiles. Bioinformatics 2013, 10.1093/bioinformatics/btt129

Authors

• Anicet Ebou
• Dominique Koua