Alphafold3<\/a> is a program developed by Google DeepMind and Isomorphic Labs to efficiently predict protein structures.<\/p>\n Only tagged releases are installed on the CSF as indicated by the module version number.<\/p>\n Alphafold3 is licensed for non commercial use only.<\/strong><\/p>\n To use Alphafold3: 2. Obtain the model Parameters from Google DeepMind<\/a><\/p>\n Any publication that discloses findings arising from using Alphafold3, the model parameters or outputs produced by those should cite the “Accurate structure prediction of biomolecular interactions with AlphaFold 3” paper.<\/a><\/p>\n Specific licenses and terms: It is good practice to load module files within your jobscript so that you have a full record of how the job was run.<\/p>\n Module load:<\/p>\n Please do not run on the login node, jobs should be submitted via batch to a GPU partition<\/strong>.<\/p>\n This installation uses a Singularity\/Apptainer container, which is launched with the command:<\/p>\n All Alphafold3 options are provided as arguments to this command. If you have previously used Alphafold2, there are differences in how jobs are configured and run.<\/p>\n You can view Alphafold3 help information with:<\/p>\n Alphafold3 uses a set of reference databases. We have downloaded these for the specific version of Alphafold3 and the path can be found in the example sbatch script(s) below.<\/p>\n Alphafold3 requires an input file in JSON format, an example JSON can be found on the Aphafold3 github.<\/a> The docker run instructions on the github will not work on the CSF, use the batch job script format provided below.<\/p>\n Create a batch submission script, in this example it will be a file called alphafold3.sbatch:<\/p>\n Submit the jobscript using:<\/p>\n Github Deepmind\/alphafold3<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" Overview Alphafold3 is a program developed by Google DeepMind and Isomorphic Labs to efficiently predict protein structures. Only tagged releases are installed on the CSF as indicated by the module version number. Restrictions on use Alphafold3 is licensed for non commercial use only. To use Alphafold3: 1. Read and understand the information below and then contact us to request access stating you agree to abide by the terms. 2. Obtain the model Parameters from Google.. Read more »<\/a><\/p>\n","protected":false},"author":25,"featured_media":0,"parent":86,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-11182","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/ri.itservices.manchester.ac.uk\/csf3\/wp-json\/wp\/v2\/pages\/11182","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ri.itservices.manchester.ac.uk\/csf3\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ri.itservices.manchester.ac.uk\/csf3\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ri.itservices.manchester.ac.uk\/csf3\/wp-json\/wp\/v2\/users\/25"}],"replies":[{"embeddable":true,"href":"https:\/\/ri.itservices.manchester.ac.uk\/csf3\/wp-json\/wp\/v2\/comments?post=11182"}],"version-history":[{"count":13,"href":"https:\/\/ri.itservices.manchester.ac.uk\/csf3\/wp-json\/wp\/v2\/pages\/11182\/revisions"}],"predecessor-version":[{"id":11197,"href":"https:\/\/ri.itservices.manchester.ac.uk\/csf3\/wp-json\/wp\/v2\/pages\/11182\/revisions\/11197"}],"up":[{"embeddable":true,"href":"https:\/\/ri.itservices.manchester.ac.uk\/csf3\/wp-json\/wp\/v2\/pages\/86"}],"wp:attachment":[{"href":"https:\/\/ri.itservices.manchester.ac.uk\/csf3\/wp-json\/wp\/v2\/media?parent=11182"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Restrictions on use<\/h2>\n
\n1. Read and understand the information below and then contact us to request access stating you agree to abide by the terms.<\/a><\/p>\nInformation on specific terms<\/h3>\n
\nAlphafold3 license<\/a>
\nAlphafold3 model weights terms of use policy<\/a>
\nList of Alphafold3 reference data licenses<\/a><\/p>\nSet up procedure<\/h2>\n
module load apps\/singularity\/alphafold3\/3.0.1<\/pre>\n
Running the application<\/h2>\n
run_alphafold<\/pre>\n
run_alphafold --helpfull<\/pre>\n
Databases<\/h3>\n
Batch job submission<\/h3>\n
#!\/bin\/sh\r\n#\r\n#SBATCH -p gpuL ## Options: gpuA, gpuL\r\n#SBATCH -G 1 ## Alphafold3 can only use 1 GPU\r\n#SBATCH -n 1 ## One task\r\n#SBATCH -c 12 ## 12 cpu cores\r\n#SBATCH -t 4-00:00:00 ## wallclock limit Days-HH:MM:SS\r\n\r\nmodule purge\r\n\r\nmodule load apps\/singularity\/alphafold3\/3.0.1\r\n\r\n\r\n## run-specific input and output locations (scratch used as example, modify paths as needed)\r\nINPUT=\/scratch\/${USER}\/alphafold3-test\/fold-input.json\r\nOUTPUT=\/scratch\/${USER}\/alphafold3-test\/fold-output\r\n\r\n## Model weights - obtained individually and saved in your own user space \r\nWEIGHTS=${HOME}\/af3-weights\/\r\n\r\n## Databases we have pre-downloaded - you should not need to change this\r\nDATABASES=\/mnt\/data-sets\/alphafold3\/3.0.1\r\n\r\n\r\n## execute alphafold3\r\nrun_alphafold \\\r\n --json_path=${INPUT} \\\r\n --model_dir=${WEIGHTS} \\\r\n --db_dir=${DATABASES} \\\r\n --output_dir=${OUTPUT} \\\r\n --run_inference=true \\\r\n --run_data_pipeline=true\r\n\r\n<\/pre>\nsbatch alphafold3.sbatch<\/pre>\n
Further info<\/h2>\n