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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).

Table of Contents

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  • --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) (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) (See Notes for more detail)

    • default = t4

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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

References

AlphaFold Github

OpenFold Github

ESMFold Github