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README
!header
AlphaFold
This package provides an implementation of the inference pipeline of AlphaFold
v2. For simplicity, we refer to this model as AlphaFold throughout the rest of
this document.
We also provide:
1. An implementation of AlphaFold-Multimer. This represents a work in progress
and AlphaFold-Multimer isn't expected to be as stable as our monomer
AlphaFold system. Read the guide for how
to upgrade and update code.
2. The technical note containing the models
and inference procedure for an updated AlphaFold v2.3.0.
3. A CASP15 baseline set of predictions along
with documentation of any manual interventions performed.
Any publication that discloses findings arising from using this source code or
the model parameters should cite the
AlphaFold paper and, if
applicable, the
AlphaFold-Multimer paper.
Please also refer to the
Supplementary Information
for a detailed description of the method.
You can use a slightly simplified version of AlphaFold with
community-supported versions (see below).
If you have any questions, please contact the AlphaFold team at
[email protected].
!CASP14 predictions
Installation and running your first prediction
You will need a machine running Linux, AlphaFold does not support other
operating systems. Full installation requires up to 3 TB of disk space to keep
genetic databases (SSD storage is recommended) and a modern NVIDIA GPU (GPUs
with more memory can predict larger protein structures).
Please follow these steps:
1. Install Docker.
Install
NVIDIA Container Toolkit
for GPU support.
Setup running
Docker as a non-root user.
1. Clone this repository and cd into it.
bash
git clone https://github.com/deepmind/alphafold.git
cd ./alphafold
1. Download genetic databases and model parameters:
Install aria2c. On most Linux distributions it is available via the
package manager as the aria2 package (on Debian-based distributions
this can be installed by running sudo apt install aria2).
Same for rsync.
Please use the script scripts/download_all_data.sh to download and set
up full databases. This may take substantial time (download size is 556
GB), so we recommend running this script in the background:
bash
scripts/download_all_data.sh download.log 2 download_all.log &
Note: The download directory should not be a
subdirectory in the AlphaFold repository directory. If it is, the
Docker build will be slow as the large databases will be copied into the
docker build context.
It is possible to run AlphaFold with reduced databases; please refer to
the complete documentation.
1. Check that AlphaFold will be able to use a GPU by running:
bash
docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi
The output of this command should show a list of your GPUs. If it doesn't,
check if you fol