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.
Download the latest GitHub release to obtain the code: https://github.com/labgem/ASMC/releases
- Python ≥ 3.8
- biopython ≥ 1.81
- numpy
- scikit-learn
- pyyaml
- pillow
- 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.
- 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.
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 of P2RANK executable
- the path of USalign executable
Example:
distances: "/home/User/ASMC/resources/AA_distances.tsv"
usalign: "/home/User/bin/USALIGN/USalign"
p2rank: "/home/User/bin/p2rank_2.4.1/prank"
The keys should be identical to this example.
Run ASMC in a blind way (unknown active site) using a multi fasta file that should contain at least 100 sequences for clustering to be sufficiently relevant.
python ASMC/run_asmc.py --log run_asmc.log --threads 6 -r reference_file -s sequences.fasta
reference_file
should contains the path to the reference(s) structure(s), e.g:
<path>/RefA.pdb
<path>/RefB.pdb
NB: For more details, see the wiki