The AI Folding
API provides a common interface to AI based protein structure prediction tools. The API currently supports OpenFold, AlphaFold, and ESMFold. The API runs a post-processing protocol on the results to minimize the output structure into the Rosetta energy function and correct any atomic level errors in sidechain positioning (See Notes for more detail).
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Code Block |
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cyrus engine submit ai-folding input.fasta --mode=monomer --ai-tool=alphafold```alphafold |
Model multiple monomers in parallel using OpenFold
...
--ai-tool
AI folding tool to run (
openfold
,alphafold
,esmfold
),default =
alphafold
--mode
Mode to run with AI tool (
monomer
,multimer
,singleseq
),default =
monomer
--model-sets
The set of model weights to use with OpenFold (
alphafold
,openfold
) , default =openfold
(See Notes for more detail)default =
openfold
--existing-model-data
Location of existing model data in GCS,
default =
null
--precomputed-alignments
Directory path to precomputed alignments that will be upload and used for AlphaFold jobs,
default =
null
--run-relax
Enable or disable the Rosetta relax phase of post-processing,
default =
true
false
--gpu-type
Select the GPU type to use (
t4
,a100
) , default =t4
(See Notes for more detail)default =
t4
Outputs
alignments
(directory)Alignment data relevant to AI tool predictions
predictions
(directory)AI tool model predictions
initial_molprobity_reports
(directory)Molprobity report for models output by AI tool
rosetta_relaxed_models
(directory)Rosetta relaxed AI tool models
final_molprobity_reports
(directory)Molprobity report for relaxed models
...
The amount of GPU memory required increases quadratically with the number of amino acids in the system being modeled. If you are modeling a protein longer than 1500 residues or so, add the following options to the ai-folding submit command: --gpu-type=a100 --run-relax=false