Welcome to the AdenylPred github repo!
AdenylPred is a substrate and function prediction tool for class I adenylate-forming enzymes. Class I adenylate-forming enzymes have diverse functions including the acyl-CoA synthetases, NRPS A-domains, firefly luciferases, fatty acyl-AMP ligases, and β-lactone synthetases. These enzymes play critical roles in primary and secondary metabolism in all branches of the tree of life.
The number of adenylate-forming enzymes in sequence databases (>700,000) far outnumber our capacity to experimentally characterize them. Since these enzymes activate a variety of fatty, aryl, and amino acid precursors in biosynthetic pathways, prediction of substrate can help inform the chemical structure of downstream metabolites. To meet this challenge, AdenylPred was developed using a random forest machine learning approach to predict substrate specificity from amino acid sequence.
For running small queries (<50 sequences), an AdenylPred web app is available at z.umn.edu/adenylpred. For computationally-intensive queries we request use of the command-line version here.
Prerequisite software and packages:
- python (version 3.7.3 tested, any version >= 3.5.0 should work)
- python-virtualenv (not needed, but highly recommended)
- muscle (version 3.8.1551 tested) or if you have conda installed you can use
conda install -c bioconda muscle - hmmer2 (HMMER 2.3.2 tested) or if you have conda installed you can use
conda install -c bioconda hmmer2
Create a python virtual environment for installing AdenylPred dependencies. If conda is not installed, see venv documentation for more information. If conda is install you can use the following commands:
conda create --name adenylpred_env
Then activate your environment using:
source activate adenylpred_env
Next navigate to a location on your local drive where you would like AdenylPred installed. To obtain a copy of the AdenylPred source code you will need to clone the AdenylPred git repository:
git clone https://github.com/serina-robinson/adenylpred_minimal.git
cd adenylpred
Or, from github.com, click the "clone or download" button and "Download ZIP"
All python dependencies are specified in the requirements.txt file. To load all the requirements simply run:
conda install -c bioconda hmmer2
conda install -c bioconda muscle
pip3 install -r requirements.txt
You should then be able to run adenylpred as follows:
usage: adenylpred.py [-h] -i INPUT -o OUTPUT [-v] [-n] [-g]
Prediction tool for adenylate-forming enzyme substrate specificity
optional arguments:
-h, --help show this help message and exit
-i INPUT, --input INPUT
Input file (FASTA or GenBank format).
-o OUTPUT, --output OUTPUT
Output file directory. Default is stdout
-v, --verbose Verbose. Prints progress to stdout
-n, --nucleotide Nucleotide sequence
-g, --genbank_input Input is in GenBank format
Common issues include not having hmmer2 or muscle installed, so please check the dependencies before using AdenylPred.
Predict substrates of A domains from a complete biosynthetic gene cluster FASTA file
python3 adenylpred.py -i examples/lipstatin.fasta -o lipstatin_predictions.txt
Predict substrates for AMP-binding enzymes in a nucleotide FASTA file
python3 adenylpred.py -i examples/lipstatin_nucleotide.fasta -n
Predict substrates from a GenBank file
python3 adenylpred.py -i examples/daptomycin.gbk -g
This tool is the product of a collaboration between Dr. Larry Wackett’s lab at the University of Minnesota and Dr. Marnix Medema’s lab at Wageningen University and Research, the Netherlands. It is supported a National Science Foundation Graduate Research Fellowship under Grant No. 00039202. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
- Serina Robinson (robi0916@umn.edu)
- Barbara Terlouw
- Marnix Medema
- Larry Wackett
AdenylPred is an open source tool available under the GNU Affero General Public
License version 3.0 or greater. See the LICENSE.txt file for
details.