> ## Documentation Index
> Fetch the complete documentation index at: https://docs.ospribrain.com/llms.txt
> Use this file to discover all available pages before exploring further.

# De Novo Drug Design

> Structure-based molecule generation from protein binding pockets.

## Overview

The De Novo Drug Design tool generates novel small molecules that fit a target protein's binding pocket. It uses state-of-the-art generative models to create drug candidates for hit discovery.

## Workflow

<Steps>
  <Step title="Upload protein structure">
    Provide a PDB file by uploading, pasting, or using the example structure. The 3D structure is visualized in the viewer.
  </Step>

  <Step title="Define binding pocket">
    Either:

    * **AI detection** — The AI automatically identifies the binding pocket
    * **Manual coordinates** — Specify pocket center coordinates (x, y, z) and radius
  </Step>

  <Step title="Configure generation">
    Select a model and parameters:

    * **Model:** Pocket2Mol, TargetDiff, DiffSBDD, or DecompDiff
    * **Count:** Number of molecules to generate
    * **Temperature:** Creativity parameter (higher = more diverse)
  </Step>

  <Step title="Generate">
    Click Generate. The job runs and produces candidate molecules.
  </Step>
</Steps>

<Note>
  **Alex's screenshot note:** Take a screenshot of the De Novo setup wizard showing the protein structure viewer with the binding pocket highlighted.
</Note>

## Results

Generated molecules are displayed in a sortable table:

| Column           | Description                                    |
| ---------------- | ---------------------------------------------- |
| **2D Depiction** | Molecular structure drawing                    |
| **SMILES**       | SMILES string                                  |
| **QED**          | Drug-likeness score (0-1)                      |
| **SA**           | Synthetic accessibility (1-10, lower = easier) |
| **Vina Score**   | Predicted binding affinity                     |
| **MW**           | Molecular weight                               |
| **LogP**         | Lipophilicity                                  |

### Molecule Detail

Click any molecule to see:

* Enlarged 2D depiction
* All properties
* SMILES string (copyable)
* **Edit & Re-score** — Modify the SMILES and recalculate properties
* **Fragment Growing** — Extend the molecule from specific attachment points

## Export

| Format     | Description                    |
| ---------- | ------------------------------ |
| **SDF**    | Standard molecular data format |
| **SMILES** | Plain text SMILES strings      |

## Jobs History

View past generation jobs with:

* Job ID and date
* Model used
* Number of molecules generated
* Status (running, complete, failed)

Click any job to reload its results.

## Guided Demo

Click **Guided Demo** for a step-by-step walkthrough using an example protein that demonstrates the full workflow.

<Note>
  **Alex's screenshot note:** Take a screenshot of the results table showing 5-6 generated molecules with their 2D depictions and property scores.
</Note>