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MULTICOM_ligand 0.4.0
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MULTICOM_ligand 0.4.0

Contents:

  • Installation
  • DynamicBind checkpoint (~0.25 GB)
  • Tutorials
  • RoseTTAFold-All-Atom checkpoint (~1.5 GB)
  • How to prepare MULTICOM_ligand data
  • Available inference methods
  • How to run inference with individual methods
  • How to run inference with a method ensemble
  • NOTE: the suffixes for both output_dir and ensemble_benchmarking_repeat_index should be modified to e.g., 2, 3, …
  • benchmark using the PoseBusters Benchmark dataset e.g., after generating 40 complexes per target with each method
  • benchmark using the Astex Diverse dataset e.g., after generating 40 complexes per target with each method
  • benchmark using the DockGen dataset e.g., after generating 40 complexes per target with each method
  • benchmark using the CASP15 dataset e.g., after generating 40 complexes per target with each method
  • analyze benchmarking results for the PoseBusters Benchmark dataset
  • How to create comparative plots of inference results
  • analyze benchmarking results for the CASP15 dataset
  • For developers
  • Acknowledgements
  • Citing this work
  • Bonus

Default Configs

  • Analysis
  • Data
  • Model

API Reference

  • Binding site crop preparation
  • Complex alignment
  • Inference relaxation
  • Minimize energy
  • Ensemble generation
  • Data utilities
  • Model utilities
  • General utilities
  • OmegaConf resolvers
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Python Module Index

m
 
m
- multicom_ligand
    multicom_ligand.__init__
    multicom_ligand.analysis.complex_alignment
    multicom_ligand.data.binding_site_crop_preparation
    multicom_ligand.models.ensemble_generation
    multicom_ligand.models.inference_relaxation
    multicom_ligand.models.minimize_energy
    multicom_ligand.utils.data_utils
    multicom_ligand.utils.model_utils
    multicom_ligand.utils.utils
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