ASMC

ASMC combines (i) homology modeling of family members (MODELLER), (ii) ligand-binding pocket search (P2RANK), (iii) structural alignment of modeled active sites (USalign) and (iv) density-based spatial clustering of obtained alignments (DBSCAN) in a single command line. Clustering step can be carried out on either structural or sequence alignment.

Requirements

Requires Python>=3.8

Python dependencies:

• numpy
• scikit-learn
• pyyaml
• pillow
• biopython>=1.81
• weblogo

External dependencies:

• p2rank - for ligand-binding pocket detection (https://github.com/rdk/p2rank)
• modeller - for homology modeling (https://salilab.org/modeller/)
• USalign - for structural alignment (https://zhanggroup.org/US-align/)

Installation

Download

Download the latest GitHub release to obtain the code: https://github.com/labgem/ASMC/releases

Python requirements

• Python ≥ 3.8
• numpy
• scikit-learn
• pyyaml
• pillow
• biopython ≥ 1.81
• weblogo

You can install the python dependencies with pip, conda or mamba with the following commands and the files given in the releases:

pip

pip install -r requirements.txt

conda

conda env create -n env_name -f env.yml

mamba

mamba env create -n env_name -f env.yml

Installation via conda and mamba includes the MODELLER installation, but you still need to request the license key.

External Software dependencies

• P2RANK - for ligand-binding pocket detection (https://github.com/rdk/p2rank)
• MODELLER - for homology modeling (https://salilab.org/modeller/)
• USalign - for structural alignment (https://zhanggroup.org/US-align/)

Please follow the links above and the instructions given by their authors.

Configuration

In ASMC/resources, add a file exactly named config_asmc.yml. This file should contain 3 information:

• the path to the ASMC/resources/AA_distances.tsv
• the path or alias of P2RANK executable (or binary name if it's in your PATH)
• the path or alias of USalign executable (or binary name if it's in your PATH)

Example:

distances: "/home/User/ASMC/resources/AA_distances.tsv"
usalign: "USalign"
p2rank: "prank"

The keys should be identical to this example.

Quick Usage

python ASMC/run_asmc.py --threads 6 -r reference_file -s multi_fasta_file

the reference_file should contains the path to the reference(s) structure(s), e.g:

<path>/RefA.pdb
<path>/RefB.pdb

Recommanded Usage

It is advisable to define the positions of interest manually, based on the literature or your own expertise.

It is possible to run only the pocket detection and then refine the selection yourself:

python ASMC/run_asmc.py --threads 6 -r reference_file -s multi_fasta_file --end pocket

Then you should modified (or created) the pocket.csv file returned.

Finally you can run the pipeline with this command :

python ASMC/run_asmc.py --threads 6 -r reference_file -p pocket.csv -s multi_fasta_file

For more details, see the wiki