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> **⚠️ Notice:** We have discovered a bug in version `1.0.0` affecting the ligand scoring results of each primary-ligand dataset (Astex Diverse, DockGen-E, and PoseBusters Benchmark). We have addressed this bug in version `1.1.0`, which reports (~15% on average) reduced performance for each method currently in the benchmark. Please rerun your analyses if you have developed code on top of `PoseBench`. Thank you for your understanding!
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## Contents
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-[Installation](#installation)
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```bash
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# fetch, extract, and clean-up preprocessed Astex Diverse, PoseBusters Benchmark, DockGen, and CASP15 data (~3 GB) #
**NOTE:** The preprocessed Astex Diverse, PoseBusters Benchmark, DockGen, and CASP15 data available via [Zenodo](https://doi.org/10.5281/zenodo.17536252) provide pre-holo-aligned protein structures predicted by AlphaFold 3 (and alternatively MIT-licensed ESMFold) for these respective datasets. Accordingly, users must ensure their usage of such predicted protein structures from AlphaFold 3 aligns with AlphaFold 3's [Terms of Use](https://github.com/google-deepmind/alphafold3/blob/main/WEIGHTS_TERMS_OF_USE.md).
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**NOTE:** The preprocessed Astex Diverse, PoseBusters Benchmark, DockGen, and CASP15 data available via [Zenodo](https://doi.org/10.5281/zenodo.19138652) provide pre-holo-aligned protein structures predicted by AlphaFold 3 (and alternatively MIT-licensed ESMFold) for these respective datasets. Accordingly, users must ensure their usage of such predicted protein structures from AlphaFold 3 aligns with AlphaFold 3's [Terms of Use](https://github.com/google-deepmind/alphafold3/blob/main/WEIGHTS_TERMS_OF_USE.md).
method: diffdock # the method for which to score predictions - NOTE: must be one of (`diffdock`, `fabind`, `dynamicbind`, `neuralplexer`, `flowdock`, `rfaa`, `chai-lab`, `boltz`, `vina`, `ensemble`)
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vina_binding_site_method: p2rank # the method to use for Vina binding site prediction - NOTE: must be one of (`diffdock`, `fabind`, `dynamicbind`, `neuralplexer`, `flowdock`, `rfaa`, `chai-lab`, `boltz`, `p2rank`)
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method: diffdock # the method for which to score predictions - NOTE: must be one of (`diffdock`, `fabind`, `dynamicbind`, `neuralplexer`, `flowdock`, `rfaa`, `chai-lab`, `boltz`, `alphafold3`, `vina`, `ensemble`)
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vina_binding_site_method: p2rank # the method to use for Vina binding site prediction - NOTE: must be one of (`diffdock`, `fabind`, `dynamicbind`, `neuralplexer`, `flowdock`, `rfaa`, `chai-lab`, `boltz`, `alphafold3`, `p2rank`)
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ensemble_ranking_method: consensus # the method to use for ensemble ranking - NOTE: must be one of (`consensus`, `ff`)
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dataset: astex_diverse # the dataset to use - NOTE: must be one of (`posebusters_benchmark`, `astex_diverse`, `dockgen`, `casp15`)
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repeat_index: 1# the repeat index which was used for inference
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cuda_device_index: 0# the CUDA device index to use for inference (for all methods except AutoDock-Vina)
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output_script_dir: ${oc.env:PROJECT_ROOT}/scripts/inference # the directory in which to save the output script
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pocket_only_baseline: null# whether to perform a pocket-only baseline for the PoseBusters Benchmark set - NOTE: not applicable only to `tulip`
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pocket_only_baseline: false# whether to perform a pocket-only baseline for the PoseBusters Benchmark set - NOTE: not applicable only to `tulip`
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v1_baseline: false # whether to perform the V1 baseline for DiffDock
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no_ilcl: null# whether to use model weights trained with an inter-ligand clash loss (ILCL) for the CASP15 set - NOTE: only applicable to `neuralplexer`
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relax_protein: null# whether to relax the protein structure before scoring - NOTE: currently in an experimental state
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no_ilcl: false# whether to use model weights trained with an inter-ligand clash loss (ILCL) for the CASP15 set - NOTE: only applicable to `neuralplexer`
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relax_protein: false# whether to relax the protein structure before scoring - NOTE: currently in an experimental state
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export_hpc_headers: true # whether to insert high-performance computing (by default, SLURM) headers into the output script
Copy file name to clipboardExpand all lines: docs/source/available_methods.rst
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================
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.. mdinclude:: ../../README.md
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.. note::
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Have a new method to add? Please let us know by creating a pull request. We would be happy to work with you to integrate new methodology into this benchmark!
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