gh-k-dense-ai-claude-scientific-skills-scientific-skills/skills/diffdock/references/parameters_reference.md

DiffDock Configuration Parameters Reference

This document provides comprehensive details on all DiffDock configuration parameters and command-line options.

Model & Checkpoint Settings

Model Paths

• --model_dir: Directory containing the score model checkpoint

  • Default: ./workdir/v1.1/score_model
  • DiffDock-L model (current default)

• --confidence_model_dir: Directory containing the confidence model checkpoint

  • Default: ./workdir/v1.1/confidence_model

• --ckpt: Name of the score model checkpoint file

  • Default: best_ema_inference_epoch_model.pt

• --confidence_ckpt: Name of the confidence model checkpoint file

  • Default: best_model_epoch75.pt

Model Version Flags

• --old_score_model: Use original DiffDock model instead of DiffDock-L

  • Default: false (uses DiffDock-L)

• --old_filtering_model: Use legacy confidence filtering approach

  • Default: true

Input/Output Options

Input Specification

• --protein_path: Path to protein PDB file

  • Example: --protein_path protein.pdb
  • Alternative to --protein_sequence

• --protein_sequence: Amino acid sequence for ESMFold folding

  • Automatically generates protein structure from sequence
  • Alternative to --protein_path

• --ligand: Ligand specification (SMILES string or file path)

  • SMILES string: --ligand "COc(cc1)ccc1C#N"
  • File path: --ligand ligand.sdf or .mol2

• --protein_ligand_csv: CSV file for batch processing

  • Required columns: complex_name, protein_path, ligand_description, protein_sequence
  • Example: --protein_ligand_csv data/protein_ligand_example.csv

Output Control

• --out_dir: Output directory for predictions

  • Example: --out_dir results/user_predictions/

• --save_visualisation: Export predicted molecules as SDF files

  • Enables visualization of results

Inference Parameters

Diffusion Steps

• --inference_steps: Number of planned inference iterations

  • Default: 20
  • Higher values may improve accuracy but increase runtime

• --actual_steps: Actual diffusion steps executed

  • Default: 19

• --no_final_step_noise: Omit noise at the final diffusion step

  • Default: true

Sampling Settings

• --samples_per_complex: Number of samples to generate per complex

  • Default: 10
  • More samples provide better coverage but increase computation

• --sigma_schedule: Noise schedule type

  • Default: expbeta (exponential-beta)

• --initial_noise_std_proportion: Initial noise standard deviation scaling

  • Default: 1.46

Temperature Parameters

Sampling Temperatures (Controls diversity of predictions)

• --temp_sampling_tr: Translation sampling temperature

  • Default: 1.17

• --temp_sampling_rot: Rotation sampling temperature

  • Default: 2.06

• --temp_sampling_tor: Torsion sampling temperature

  • Default: 7.04

Psi Angle Temperatures

• --temp_psi_tr: Translation psi temperature

  • Default: 0.73

• --temp_psi_rot: Rotation psi temperature

  • Default: 0.90

• --temp_psi_tor: Torsion psi temperature

  • Default: 0.59

Sigma Data Temperatures

• --temp_sigma_data_tr: Translation data distribution scaling

  • Default: 0.93

• --temp_sigma_data_rot: Rotation data distribution scaling

  • Default: 0.75

• --temp_sigma_data_tor: Torsion data distribution scaling

  • Default: 0.69

Processing Options

Performance

• --batch_size: Processing batch size

  • Default: 10
  • Larger values increase throughput but require more memory

• --tqdm: Enable progress bar visualization

  • Useful for monitoring long-running jobs

Protein Structure

• --chain_cutoff: Maximum number of protein chains to process

  • Example: --chain_cutoff 10
  • Useful for large multi-chain complexes

• --esm_embeddings_path: Path to pre-computed ESM2 protein embeddings

  • Speeds up inference by reusing embeddings
  • Optional optimization

Dataset Options

• --split: Dataset split to use (train/test/val)
  • Used for evaluation on standard benchmarks

Advanced Flags

Debugging & Testing

• --no_model: Disable model inference (debugging)

  • Default: false

• --no_random: Disable randomization

  • Default: false
  • Useful for reproducibility testing

Alternative Sampling

• --ode: Use ODE solver instead of SDE

  • Default: false
  • Alternative sampling approach

• --different_schedules: Use different noise schedules per component

  • Default: false

Error Handling

• --limit_failures: Maximum allowed failures before stopping
  • Default: 5

Configuration File

All parameters can be specified in a YAML configuration file (typically default_inference_args.yaml) or overridden via command line:

python -m inference --config default_inference_args.yaml --samples_per_complex 20

Command-line arguments take precedence over configuration file values.