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skills/datamol/references/conformers_module.md

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+# Datamol Conformers Module Reference
+
+The `datamol.conformers` module provides tools for generating and analyzing 3D molecular conformations.
+
+## Conformer Generation
+
+### `dm.conformers.generate(mol, n_confs=None, rms_cutoff=None, minimize_energy=True, method='ETKDGv3', add_hs=True, ...)`
+Generate 3D molecular conformers.
+- **Parameters**:
+  - `mol`: Input molecule
+  - `n_confs`: Number of conformers to generate (auto-determined based on rotatable bonds if None)
+  - `rms_cutoff`: RMS threshold in Ångströms for filtering similar conformers (removes duplicates)
+  - `minimize_energy`: Apply UFF energy minimization (default: True)
+  - `method`: Embedding method - options:
+    - `'ETDG'` - Experimental Torsion Distance Geometry
+    - `'ETKDG'` - ETDG with additional basic knowledge
+    - `'ETKDGv2'` - Enhanced version 2
+    - `'ETKDGv3'` - Enhanced version 3 (default, recommended)
+  - `add_hs`: Add hydrogens before embedding (default: True, critical for quality)
+  - `random_seed`: Set for reproducibility
+- **Returns**: Molecule with embedded conformers
+- **Example**:
+  ```python
+  mol = dm.to_mol("CCO")
+  mol_3d = dm.conformers.generate(mol, n_confs=10, rms_cutoff=0.5)
+  conformers = mol_3d.GetConformers()  # Access all conformers
+  ```
+
+## Conformer Clustering
+
+### `dm.conformers.cluster(mol, rms_cutoff=1.0, already_aligned=False, centroids=False)`
+Group conformers by RMS distance.
+- **Parameters**:
+  - `rms_cutoff`: Clustering threshold in Ångströms (default: 1.0)
+  - `already_aligned`: Whether conformers are pre-aligned
+  - `centroids`: Return centroid conformers (True) or cluster groups (False)
+- **Returns**: Cluster information or centroid conformers
+- **Use case**: Identify distinct conformational families
+
+### `dm.conformers.return_centroids(mol, conf_clusters, centroids=True)`
+Extract representative conformers from clusters.
+- **Parameters**:
+  - `conf_clusters`: Sequence of cluster indices from `cluster()`
+  - `centroids`: Return single molecule (True) or list of molecules (False)
+- **Returns**: Centroid conformer(s)
+
+## Conformer Analysis
+
+### `dm.conformers.rmsd(mol)`
+Calculate pairwise RMSD matrix across all conformers.
+- **Requirements**: Minimum 2 conformers
+- **Returns**: NxN matrix of RMSD values
+- **Use case**: Quantify conformer diversity
+
+### `dm.conformers.sasa(mol, n_jobs=1, ...)`
+Calculate Solvent Accessible Surface Area (SASA) using FreeSASA.
+- **Parameters**:
+  - `n_jobs`: Parallelization for multiple conformers
+- **Returns**: Array of SASA values (one per conformer)
+- **Storage**: Values stored in each conformer as property `'rdkit_free_sasa'`
+- **Example**:
+  ```python
+  sasa_values = dm.conformers.sasa(mol_3d)
+  # Or access from conformer properties
+  conf = mol_3d.GetConformer(0)
+  sasa = conf.GetDoubleProp('rdkit_free_sasa')
+  ```
+
+## Low-Level Conformer Manipulation
+
+### `dm.conformers.center_of_mass(mol, conf_id=-1, use_atoms=True, round_coord=None)`
+Calculate molecular center.
+- **Parameters**:
+  - `conf_id`: Conformer index (-1 for first conformer)
+  - `use_atoms`: Use atomic masses (True) or geometric center (False)
+  - `round_coord`: Decimal precision for rounding
+- **Returns**: 3D coordinates of center
+- **Use case**: Centering molecules for visualization or alignment
+
+### `dm.conformers.get_coords(mol, conf_id=-1)`
+Retrieve atomic coordinates from a conformer.
+- **Returns**: Nx3 numpy array of atomic positions
+- **Example**:
+  ```python
+  positions = dm.conformers.get_coords(mol_3d, conf_id=0)
+  # positions.shape: (num_atoms, 3)
+  ```
+
+### `dm.conformers.translate(mol, conf_id=-1, transform_matrix=None)`
+Reposition conformer using transformation matrix.
+- **Modification**: Operates in-place
+- **Use case**: Aligning or repositioning molecules
+
+## Workflow Example
+
+```python
+import datamol as dm
+
+# 1. Create molecule and generate conformers
+mol = dm.to_mol("CC(C)CCO")  # Isopentanol
+mol_3d = dm.conformers.generate(
+    mol,
+    n_confs=50,           # Generate 50 initial conformers
+    rms_cutoff=0.5,       # Filter similar conformers
+    minimize_energy=True   # Minimize energy
+)
+
+# 2. Analyze conformers
+n_conformers = mol_3d.GetNumConformers()
+print(f"Generated {n_conformers} unique conformers")
+
+# 3. Calculate SASA
+sasa_values = dm.conformers.sasa(mol_3d)
+
+# 4. Cluster conformers
+clusters = dm.conformers.cluster(mol_3d, rms_cutoff=1.0, centroids=False)
+
+# 5. Get representative conformers
+centroids = dm.conformers.return_centroids(mol_3d, clusters)
+
+# 6. Access 3D coordinates
+coords = dm.conformers.get_coords(mol_3d, conf_id=0)
+```
+
+## Key Concepts
+
+- **Distance Geometry**: Method for generating 3D structures from connectivity information
+- **ETKDG**: Uses experimental torsion angle preferences and additional chemical knowledge
+- **RMS Cutoff**: Lower values = more unique conformers; higher values = fewer, more distinct conformers
+- **Energy Minimization**: Relaxes structures to nearest local energy minimum
+- **Hydrogens**: Critical for accurate 3D geometry - always include during embedding