alphafold3_tools

Toolkit for alphafold3 input generation and output analysis.

Installation

Requirements:

• Python 3.10 or later

brew install [email protected] with Homebrew is useful to install python3.12 on macOS.

Note

If you are using python3.12, create and activate venv at first. /path/to/workingdirectory is your working directory.

mkdir -p /path/to/workingdirectory ; cd /path/to/workingdirectory
python3.12 -m venv .venv
source .venv/bin/activate

# Ubuntu 22.04 uses python3.10 by default. Use python3.12 if you have it instead of python3.10.
# install from GitHub
python3 -m pip install git+https://github.com/cddlab/alphafold3_tools.git
# upgrade
python3 -m pip uninstall alphafold3_tools -y && python3 -m pip install --upgrade git+https://github.com/cddlab/alphafold3_tools.git

On Ubuntu, the commands will be installed in ~/.local/bin or in the .venv directory (e.g. /path/to/workingdirectory/.venv/bin). You may need to add this directory to your PATH environment variable.

export PATH=$PATH:~/.local/bin

Usage

More detailed usage information can be found by running the commands with the -h option.

msatojson

msatojson is a command to convert an a3m-formatted multiple sequence alignment (MSA) file to JSON format. The input name can be specified with the -n option.

msatojson -i input.a3m -o input.json -n inputname

The input a3m MSA file can be generated by MMSeqs2 webserver (or ColabFold). colabfold_batch --msa-only option is useful to generate a3m MSA files only.

msatojson can accept a directory containing multiple a3m files. In this case, the output JSON files will be saved in the specified output directory.

msatojson -i /path/to/a3m_containing/directory -o /path/to/output/directory

Warning

Currently including templates is not supported. I am working on it.

paeplot

paeplot is a command to plot the predicted aligned error (PAE). The color map can be specified with the -c option. The default color map is bwr (ColabFold-like), but Greens_r is also available for AlphaFold Structure Database (AFDB)-like coloring.

paeplot -i /path/to/alphafold3_output/directory -c Greens_r --dpi 300 [-n foo] [-a]

superpose_ciffiles

superpose_ciffiles is a command to superpose the output mmCIF files. The command creates a multi-model mmCIF file containing all the predicted model.cif subdirectories. The output file name can be specified with the -o option. By default, the output file will be saved as foo_superposed.cif in the input directory. -c option can be used to specify the chain ID to be superposed.

superpose_ciffiles -i /path/to/alphafold3_output/directory [-o /path/to/output/directory/foo_superposed.cif] [-c A]

In PyMOL, the following command will be useful to visualize the plDDT values.

color 0x0053D6, b < 100
color 0x65CBF3, b < 90
color 0xFFDB13, b < 70
color 0xFF7D45, b < 50
util.cnc

Note

To visualize only an object of seed-1_sample-0 with plddt values, type the following command in PyMOL.

color 0x0053D6, seed-1_sample-0 and b < 100
color 0x65CBF3, seed-1_sample-0 and b < 90
color 0xFFDB13, seed-1_sample-0 and b < 70
color 0xFF7D45, seed-1_sample-0 and b < 50

sdf2ccd

sdf2ccd is a command to convert sdf file to ccd format.

sdf2ccd -i input.sdf -o output.ccd -n STR

Other tools are being developed and will be added.

Acknowledgements

This tool uses the following libraries:

• RDKit
• matplotlib
• numpy
• gemmi
• loguru

PDBeurope/ccdutils is used for the conversion of sdf to ccd.