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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).

Contents

Quickstart

Inputs

Options

Outputs

Notes

References

Release Notes

Table of Contents

Quickstart

Model a monomer using AlphaFold

Code Block
cyrus engine submit ai-folding input.fasta --mode=monomer --ai-tool=alphafold```alphafold

Model multiple monomers in parallel using OpenFold

Code Block
cyrus engine submit ai-folding input.fasta input2.fasta --mode=monomer --ai-tool=openfold

Model a monomer using OpenFold with weights trained by DeepMind (AlphaFold)

Default = OpenFold weights

Code Block
cyrus engine submit ai-folding input.fasta --mode=monomer --ai-tool=openfold --model-sets=alphafold

Create a model using AlphaFold's SingleSeq mode with 2 recycles

Code Block
cyrus engine submit ai-folding input.fasta --mode=singleseq --ai-tool=alphafold --af-n-recycles=2

Model a multimer (AlphaFold only)

Code Block
cyrus engine submit ai-folding input.fasta --mode=multimer --ai-tool=alphafold

...

FASTA file containing sequence(s) of interest to model.

Options

  • --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

Notes

Model weight sets

  • alphafold - weights trained by DeepMind

  • openfold - weights trained by the AlQuarashi Lab for OpenFold

...

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