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Using AlphaFold via SBGrid

The current version installed on our server is Alphafold2 2.1.1

SBGrid is a software infrastructure that includes a library of over 400 structural biology applications, including AlphaFold. The SBGrid software collection is already installed on the bioinformatics infrastructure of the structural biology platform and can be accessed either remotely via SSH or physically by logging into one of the computers in room C-305 (Roger-Gaudry building). More details are given on the SBGrid Wiki page for AlphaFold.

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Content of the run_alphafold_template.sh wrapper:

# Alphafold2, version 2.1.1
# wrapper script to run Alphafold for a monomer
#
# usage:
# ./run_alphafold_tempate.sh sequence.fasta
#
# adjust parameters as required

DATA_DIR="/home/sbio/afdb/"
OUTPUT_DIR=$(pwd)
MAX_TEMPLATE_DATE=$(date -I)
DB_PRESET="full_dbs"
BFD_DB="${DATA_DIR}/bfd/bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt"
UNICLUST30_DB="${DATA_DIR}/uniclust30/uniclust30_2018_08/uniclust30_2018_08"
UNIREF90_DB="${DATA_DIR}/uniref90/uniref90.fasta"
MGNIFY_DB="${DATA_DIR}/mgnify/mgy_clusters_2018_12.fa"
TEMPLATE_MMCIF_DIR="${DATA_DIR}/pdb_mmcif/mmcif_files"
PDB70_DB="${DATA_DIR}/pdb70/pdb70"
OBSOLETE_PATH="${DATA_DIR}/pdb_mmcif/obsolete.dat"

run_alphafold.py \
--data_dir=$DATA_DIR \
--output_dir=$OUTPUT_DIR \
--max_template_date=$MAX_TEMPLATE_DATE \
--db_preset=$DB_PRESET \
--bfd_database_path=$BFD_DB \
--uniclust30_database_path=$UNICLUST30_DB \
--uniref90_database_path=$UNIREF90_DB \
--mgnify_database_path=$MGNIFY_DB \
--template_mmcif_dir=$TEMPLATE_MMCIF_DIR \
--pdb70_database_path=$PDB70_DB \
--obsolete_pdbs_path=$OBSOLETE_PATH \
--fasta_paths=test_monomer.fasta${1} \

Make sure to replace Replace the --fasta_paths= value to point to your FASTA file in the run_alphafold_template.sh wrapper, and make the wrapper script executable.

chmod +x run_alphafold_template.sh

Then, to run AlphaFold, enter the following command in the terminal prompt:

./run_alphafold_template.sh [FASTA file location]

As a reference, it took about 60 minutes for the calculation to predict 5 models for RVFV NSs (the sequence given as example above) to take place on mazuelo. Once it is done, you can go to the results folder and analyze your results. A description of the various files produced by the program is provided on the GitHub page of AlphaFold.

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export ALPHAFOLD_PTM=true

Using the multimer option

It is now possible to run predictions with multimers. A wrapper script can be downloaded here. Content of the run_alphafold_template_multimer.sh wrapper:

# Alphafold2, version 2.1.1
# wrapper script to run Alphafold for a multimer
#
# usage:
# ./run_alphafold_tempate_multimer.sh multiple_sequences.fasta
#
# adjust parameters as required

DATA_DIR="/home/sbio/afdb/"
OUTPUT_DIR=$(pwd)
MAX_TEMPLATE_DATE=$(date -I)
DB_PRESET="full_dbs"
BFD_DB="${DATA_DIR}/bfd/bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt"
UNICLUST30_DB="${DATA_DIR}/uniclust30/uniclust30_2018_08/uniclust30_2018_08"
UNIREF90_DB="${DATA_DIR}/uniref90/uniref90.fasta"
MGNIFY_DB="${DATA_DIR}/mgnify/mgy_clusters_2018_12.fa"
TEMPLATE_MMCIF_DIR="${DATA_DIR}/pdb_mmcif/mmcif_files"
PDB70_DB="${DATA_DIR}/pdb70/pdb70"
OBSOLETE_PATH="${DATA_DIR}/pdb_mmcif/obsolete.dat"

run_alphafold.py \
--data_dir=$DATA_DIR \
--output_dir=$OUTPUT_DIR \
--max_template_date=$MAX_TEMPLATE_DATE \
--db_preset=$DB_PRESET \
--bfd_database_path=$BFD_DB \
--uniclust30_database_path=$UNICLUST30_DB \
--uniref90_database_path=$UNIREF90_DB \
--mgnify_database_path=$MGNIFY_DB \
--template_mmcif_dir=$TEMPLATE_MMCIF_DIR \
--pdb70_database_path=$PDB70_DB \
--obsolete_pdbs_path=$OBSOLETE_PATH \
--model_preset=multimer \
--fasta_paths=${1}

All protein sequences have to be in the same FASTA file.

Using AlphaFold via a web interface

DeepMind, in collaboration with Google, has provided users with a Colab notebook to run AlphaFoldAlphaFold2 (currently version 2.1.0). The notebook can be opened at the address below, and Instructions are provided in the notebook as to how to proceed:

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