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Add screen functionality #56

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Add screen functionality #56

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18 changes: 11 additions & 7 deletions docs/prediction.md
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,10 @@ Once you have installed `boltz`, you can start making predictions by simply runn

where `<INPUT_PATH>` is a path to the input file or a directory. The input file can either be in fasta (enough for most use cases) or YAML format (for more complex inputs). If you specify a directory, `boltz` will run predictions on each `.yaml` or `.fasta` file in the directory.

The `screen` function allows you to predict interactions for multiple ligands, accepting a single `.sdf` file, a directory of `.sdf` files, or a `.smi` file with ligand IDs and SMILES strings separated by spaces or tabs. Proteins can be provided as `.pdb` or `.fasta` files (recommended). The `screen` function supports all arguments from `predict` and additionally allows specifying a precomputed MSA file (`.m3a`) with `--msa_path`. If no MSA is available, the `--use_msa_server` flag can generate it automatically. **Note**: Using `--use_msa_server` sends data to an external server, and confidentiality cannot be guaranteed.

`boltz screen --protein <PROTEIN_PATH> --ligands <LIGANDS_PATH>`

Before diving into more details about the input formats, here are the key differences in what they each support:

| Feature | Fasta | YAML |
Expand Down Expand Up @@ -131,14 +135,14 @@ The following options are available for the `predict` command:
After running the model, the generated outputs are organized into the output directory following the structure below:
```
out_dir/
├── lightning_logs/ # Logs generated during training or evaluation
├── predictions/ # Contains the model's predictions
├── [input_file1]/
├── [input_file1]_model_0.cif # The predicted structure in CIF format
��������� lightning_logs/ # Logs generated during training or evaluation
��������� predictions/ # Contains the model's predictions
��������� [input_file1]/
��������� [input_file1]_model_0.cif # The predicted structure in CIF format
...
└── [input_file1]_model_[diffusion_samples-1].cif # The predicted structure in CIF format
└── [input_file2]/
��������� [input_file1]_model_[diffusion_samples-1].cif # The predicted structure in CIF format
��������� [input_file2]/
...
└── processed/ # Processed data used during execution
��������� processed/ # Processed data used during execution
```
The `predictions` folder contains a unique folder for each input file. The input folders contain diffusion_samples predictions saved in the output_format. The `processed` folder contains the processed input files that are used by the model during inference.
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