From 561626343ac995e5aef5c52326c34cde77d132f6 Mon Sep 17 00:00:00 2001
From: Vratin Srivastava <vratins@andrew.cmu.edu>
Date: Tue, 3 Mar 2026 16:58:01 -0600
Subject: [PATCH 01/10] README.md updated with instructions to run code,
 cleaning up toml file

---
 .gitignore     |   1 +
 README.md      | 299 ++++++++++++++-
 pyproject.toml | 197 +---------
 uv.lock        | 994 ++-----------------------------------------------
 4 files changed, 343 insertions(+), 1148 deletions(-)

diff --git a/.gitignore b/.gitignore
index 1aac477..fe8429a 100644
--- a/.gitignore
+++ b/.gitignore
@@ -16,3 +16,4 @@ build/
 .venv/
 venv/
 notebooks/
+figures/
diff --git a/README.md b/README.md
index cc882a8..0c7fc80 100644
--- a/README.md
+++ b/README.md
@@ -1,17 +1,99 @@
 # WaterFlow
-Predicting water moelcule placements on protein surfaces using flow matching conditioned on learned protein structure embeddings.
 
-This repo contains all the code required to process a dataset, load in features from a pre-trained model for protein structure embeddings, and run inference (and training) of the flow matching classes. 
+Predicting water molecule placements on protein surfaces using flow matching conditioned on learned protein structure embeddings.
 
-# Environment Setup
+## Project Structure
 
-We use `uv` for our environment and package management, with python 3.12.
+```
+WaterFlow/
+├── src/                    # Core library code
+│   ├── dataset.py          # ProteinWaterDataset and data loading
+│   ├── flow.py             # FlowMatcher and FlowWaterGVP model
+│   ├── gvp.py              # Geometric Vector Perceptron layers
+│   ├── gvp_encoder.py      # GVP-based protein encoder
+│   ├── esm_encoder.py      # ESM embedding encoder
+│   ├── slae_encoder.py     # SLAE embedding encoder
+│   ├── encoder_base.py     # Encoder registry and factory
+│   ├── constants.py        # Shared constants (RBF bins, etc.)
+│   └── utils.py            # Metrics, plotting, logging utilities
+├── scripts/                # Executable scripts
+│   ├── train.py            # Training pipeline
+│   ├── inference.py        # Run inference on trained models
+│   ├── generate_esm_embeddings.py   # Precompute ESM embeddings
+│   ├── generate_slae_embeddings.py  # Precompute SLAE embeddings
+│   ├── qc_waters.py        # Quality control for water molecules 
+│   └── qc_symmetry_mates.py        # Quality control for crystal mates
+├── tests/                  # Test suite
+│   ├── test_dataset.py     # Dataset and preprocessing tests
+│   ├── test_flow.py        # Flow matching tests
+│   ├── test_encoder.py     # Encoder tests
+│   ├── test_forward.py     # End-to-end forward pass tests
+│   ├── test_gvp.py         # GVP layer tests
+│   └── test_utils.py       # Utility function tests
+└── splits/                 # Train/val/test split files
+    ├── train_list_0.95.txt # Training set (95% of data)
+    ├── valid_list_0.05.txt # Validation set (5% of data)
+    └── water_pdbs.txt      # Full list of PDBs with waters
+```
 
-You can install the environment by running `uv sync` and running the scripts with `uv run python <script>`. Or if you want to install a fresh virtual environment from scratch, follow the steps below.
+## Data Preparation
 
-Installing the environment:
+### Input PDB Files
 
+WaterFlow expects PDB files in a specific directory structure:
+
+```
+<base_pdb_dir>/
+├── 1abc/
+│   └── 1abc_final.pdb
+├── 2xyz/
+│   └── 2xyz_final.pdb
+└── ...
+```
+
+Each PDB should have `_final` suffix and contain:
+- Protein atoms (used as conditioning context)
+- Water molecules (HOH residues, used as ground truth)
+
+### Split File Format
+
+Split files are plain text with one PDB entry per line:
+
+```
+# Example: splits/train_list_0.95.txt
+110m_final
+1a2p_final
+1a3h_final
 ```
+
+### Cache Directory Structure
+
+Preprocessed data is cached under `--processed_dir`:
+
+```
+<processed_dir>/
+├── geometry/           # Cached graph structures (protein + water nodes)
+│   ├── 1abc_final.pt
+│   └── ...
+├── esm/                # ESM embeddings (per-residue)
+│   ├── 1abc_final.pt
+│   └── ...
+└── slae/               # SLAE embeddings (per-residue)
+    ├── 1abc_final.pt
+    └── ...
+```
+
+## Environment Setup
+
+We use `uv` for our environment and package management, with Python 3.12.
+
+You can install the environment by running `uv sync` and running the scripts with `uv run python <script>` (Recommended). 
+
+Or if you want to install a fresh virtual environment from scratch, follow the steps below.
+
+Installing the environment:
+
+```bash
 uv venv water --python 3.12
 source water/bin/activate
 
@@ -22,3 +104,208 @@ uv pip install biotite wandb Bio networkx e3nn pytest pytest-cov
 ```
 
 If you have trouble installing torch_cluster or scatter, I would suggest changing the cuda version in the wheel.
+
+## Model Architecture
+
+WaterFlow uses a two-stage architecture:
+
+1. **Protein Encoder**: Encodes protein structure into per-residue embeddings
+2. **Flow Network**: Predicts velocity field for water molecule trajectories
+
+### Encoder Types
+
+| Encoder | Description | Precomputation Required |
+|---------|-------------|------------------------|
+| `gvp` | Geometric Vector Perceptron encoder that learns from 3D coordinates | No |
+| `esm` | Uses ESM3 language model embeddings | Yes (`generate_esm_embeddings.py`) |
+| `slae` | Uses SLAE ([Strictly Local All-Atom Environment](https://www.biorxiv.org/content/10.1101/2025.10.03.680398v1)) embeddings | Yes (`generate_slae_embeddings.py`) |
+
+## Embedding Generation
+
+For `esm` and `slae` encoder types, you must precompute embeddings before training or inference.
+
+### ESM Embeddings (for `--encoder_type esm`)
+
+```bash
+uv run python -m scripts.generate_esm_embeddings \
+    --split_file splits/water_pdbs.txt \
+    --cache_dir ~/flow_cache/ \
+    --device cuda:0
+```
+
+### SLAE Embeddings (for `--encoder_type slae`)
+
+```bash
+uv run python -m scripts.generate_slae_embeddings \
+    --split_file splits/water_pdbs.txt \
+    --cache_dir ~/flow_cache/ \
+    --slae_ckpt /path/to/SLAE/checkpoints/autoencoder.ckpt
+```
+
+## Training
+
+### GVP Encoder (no precomputed embeddings required)
+
+```bash
+uv run python -m scripts.train \
+    --train_list splits/train_list_0.95.txt \
+    --val_list splits/valid_list_0.05.txt \
+    --encoder_type gvp \
+    --batch_size 4
+```
+
+### ESM Encoder (requires precomputed ESM embeddings)
+
+```bash
+uv run python -m scripts.train \
+    --train_list splits/train_list_0.95.txt \
+    --val_list splits/valid_list_0.05.txt \
+    --encoder_type esm \
+    --batch_size 1 \
+    --grad_accum_steps 4 \
+    --processed_dir ~/flow_cache/
+```
+
+### Resuming from Checkpoints
+
+To resume training from a checkpoint, you can load the model weights and optimizer state:
+
+```bash
+# Checkpoints are saved in <save_dir>/<run_name>/checkpoints/
+# - best.pt: Best validation loss
+# - epoch_N.pt: Periodic checkpoints every --save_every epochs
+```
+
+### Key Training Arguments
+
+| Argument | Default | Description |
+|----------|---------|-------------|
+| `--train_list` | required | Path to training split file |
+| `--val_list` | required | Path to validation split file |
+| `--encoder_type` | `gvp` | Encoder type: `gvp`, `esm`, or `slae` |
+| `--batch_size` | `4` | Batch size (use smaller for ESM due to memory) |
+| `--grad_accum_steps` | `1` | Gradient accumulation steps (effective batch = batch_size * grad_accum_steps) |
+| `--flow_layers` | `3` | Number of flow GVP layers |
+| `--hidden_s` | `256` | Scalar hidden dimension |
+| `--hidden_v` | `64` | Vector hidden dimension |
+| `--epochs` | `200` | Number of training epochs |
+| `--lr` | `1e-3` | Learning rate |
+| `--scheduler` | `cosine` | LR scheduler: `cosine`, `step`, or `none` |
+| `--warmup_steps` | `0` | Linear warmup steps |
+| `--processed_dir` | `~/flow_cache/` | Cache directory for preprocessed data |
+| `--save_dir` | `/home/srivasv/flow_checkpoints` | Directory to save checkpoints |
+| `--save_every` | `10` | Save checkpoint every N epochs |
+| `--eval_every` | `5` | Run evaluation every N epochs |
+
+### Weights & Biases Logging
+
+Training automatically logs to W&B. Configure with:
+
+| Argument | Default | Description |
+|----------|---------|-------------|
+| `--wandb_project` | `water-flow` | W&B project name |
+| `--wandb_dir` | `/home/srivasv/wandb_logs` | Local W&B log directory |
+| `--run_name` | auto-generated | Custom run name (format: `YYYYMMDD_HHMMSS_encoder_layers_hidden`) |
+
+## Quality Filtering
+
+WaterFlow applies multiple quality filters to ensure high-quality training data.
+
+### Structure-Level Quality Checks
+
+These checks determine whether a structure is included in training:
+
+| Parameter | Default | Description |
+|-----------|---------|-------------|
+| `--max_com_dist` | `25.0` | Max protein-water center-of-mass distance (A) |
+| `--max_clash_fraction` | `0.05` | Max fraction of waters clashing with protein |
+| `--clash_dist` | `2.0` | Distance threshold for clash detection (A) |
+| `--min_water_residue_ratio` | `0.6` | Minimum waters per residue ratio |
+
+### Per-Water Quality Filters
+
+These filters remove individual low-quality waters (can be toggled):
+
+| Parameter | Default | Toggle Flag | Description |
+|-----------|---------|-------------|-------------|
+| `--max_protein_dist` | `5.0` | `--no_filter_by_distance` | Remove waters far from protein |
+| `--min_edia` | `0.4` | `--no_filter_by_edia` | Remove waters with low EDIA scores |
+| `--max_bfactor_zscore` | `1.5` | `--no_filter_by_bfactor` | Remove waters with high B-factor |
+
+<details>
+<summary><strong>About EDIA Scores</strong></summary>
+
+EDIA measures how well an atom's position is supported by the experimental electron density map. Higher EDIA scores indicate more reliable atomic positions.
+
+EDIA results are expected at: `<edia_dir>/<pdb_id>/<pdb_id>_residue_stats.csv`
+
+</details>
+
+## Inference
+
+Run inference on a trained model:
+
+```bash
+uv run python -m scripts.inference \
+    --run_dir /path/to/training_run \
+    --pdb_list splits/test_list.txt \
+    --output_dir ./outputs \
+    --method rk4 \
+    --num_steps 100
+```
+
+### Key Inference Arguments
+
+| Argument | Default | Description |
+|----------|---------|-------------|
+| `--run_dir` | required | Path to training run directory (contains config.json) |
+| `--pdb_list` | required | Text file with PDB entries (one per line) |
+| `--output_dir` | required | Directory for output plots, GIFs, and metrics |
+| `--method` | `rk4` | Integration method: `euler` (fast) or `rk4` (accurate) |
+| `--num_steps` | `100` | Number of integration steps |
+| `--checkpoint` | `best.pt` | Checkpoint filename to load |
+| `--batch_size` | `8` | Number of proteins to process in parallel |
+| `--save_gifs` | `false` | Save trajectory GIFs (slower) |
+| `--threshold` | `1.0` | Distance threshold for precision/recall (A) |
+| `--water_ratio` | `None` | Sample `num_residues * ratio` waters (if not set, uses ground truth count) |
+| `--use_sc` | `false` | Use self-conditioning during integration |
+
+### Output Structure
+
+```
+<output_dir>/<run_name>/
+├── plots/              # 3D visualization PNGs for each PDB
+│   ├── 1abc_final.png
+│   └── ...
+├── gifs/               # Trajectory GIFs (if --save_gifs)
+│   ├── 1abc_final.gif
+│   └── ...
+└── metrics.json        # Per-sample and summary statistics
+```
+
+## Testing
+
+Run the test suite with pytest:
+
+```bash
+# run all tests
+uv run pytest tests/
+
+# run with coverage report
+uv run pytest tests/ --cov=src --cov-report=html
+
+# run specific test file
+uv run pytest tests/test_flow.py -v
+
+# run tests matching a pattern
+uv run pytest tests/ -k "test_forward" -v
+```
+
+### Test Categories
+
+- `test_dataset.py`: Data loading, preprocessing, and caching
+- `test_flow.py`: Flow matching training and integration
+- `test_encoder.py`: Encoder architectures and registry
+- `test_forward.py`: End-to-end forward pass validation
+- `test_gvp.py`: GVP layer equivariance and correctness
+- `test_utils.py`: Metrics, plotting, and utility functions
diff --git a/pyproject.toml b/pyproject.toml
index e59121b..1889179 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -9,197 +9,21 @@ dependencies = [
   "torch-scatter",
   "torch-cluster",
   "pyg-lib",
-  "biotite",
-  "wandb",
-  "networkx",
   "e3nn",
-  "biopython",
-  "matplotlib>=3.10.8",
+  "esm",
+  "biotite",
   "pymol-open-source-whl>=3.1.0.4",
-  "aiohappyeyeballs>=2.6.1",
-  "aiohttp>=3.13.2",
-  "aiosignal>=1.4.0",
-  "annotated-types>=0.7.0",
-  "antlr4-python3-runtime>=4.9.3",
-  "anyio>=4.12.1",
-  "asttokens>=3.0.1",
-  "atomworks==2.2.0",
-  "attrs>=25.4.0",
-  "biopandas>=0.4.1",
-  "biotraj>=1.2.2",
-  "black>=25.12.0",
-  "boto3>=1.42.22",
-  "botocore>=1.42.22",
-  "brotli>=1.2.0",
-  "certifi>=2025.11.12",
-  "charset-normalizer>=3.4.4",
-  "click>=8.3.1",
-  "cloudpathlib>=0.23.0",
-  "comm>=0.2.3",
-  "contourpy>=1.3.3",
-  "coverage>=7.13.0",
-  "cycler>=0.12.1",
-  "cython>=3.2.4",
-  "cytoolz>=0.12.3",
-  "decorator>=5.2.1",
-  "dna-features-viewer>=3.1.5",
-  "einops>=0.8.1",
-  "einx>=0.3.0",
-  "esm>=3.2.3",
-  "execnet>=2.1.2",
-  "executing>=2.2.1",
-  "filelock>=3.20.1",
-  "flake8>=7.3.0",
-  "fonttools>=4.61.1",
-  "frozendict>=2.4.7",
-  "frozenlist>=1.8.0",
-  "fsspec>=2025.12.0",
-  "gitdb>=4.0.12",
-  "gitpython>=3.1.45",
-  "h11>=0.16.0",
-  "hf-xet>=1.2.0",
-  "httpcore>=1.0.9",
-  "httpx>=0.28.1",
-  "huggingface-hub>=0.36.0",
-  "hydra-core>=1.3.2",
-  "hydride>=1.2.3",
-  "hypothesis>=6.148.7",
-  "idna>=3.11",
-  "iniconfig>=2.3.0",
-  "ipython>=9.9.0",
-  "ipython-pygments-lexers>=1.1.1",
-  "ipywidgets>=8.1.8",
-  "isort>=7.0.0",
-  "jedi>=0.19.2",
-  "jinja2>=3.1.6",
-  "jmespath>=1.0.1",
-  "joblib>=1.5.3",
-  "jupyterlab-widgets>=3.0.16",
-  "kiwisolver>=1.4.9",
-  "librt>=0.7.4",
-  "lightning>=2.6.0",
-  "lightning-utilities>=0.15.2",
-  "loguru>=0.7.3",
-  "looseversion>=1.3.0",
-  "markdown-it-py>=4.0.0",
-  "markupsafe>=3.0.3",
-  "matplotlib-inline>=0.2.1",
-  "mccabe>=0.7.0",
-  "mdurl>=0.1.2",
-  "mmtf-python>=1.1.3",
-  "mpmath>=1.3.0",
-  "msgpack>=1.1.2",
-  "msgpack-numpy>=0.4.8",
-  "multidict>=6.7.0",
-  "mypy>=1.19.1",
-  "mypy-extensions>=1.1.0",
-  "numpy>=1.26.4",
-  "nvidia-cublas-cu12>=12.6.4.1",
-  "nvidia-cuda-cupti-cu12>=12.6.80",
-  "nvidia-cuda-nvrtc-cu12>=12.6.77",
-  "nvidia-cuda-runtime-cu12>=12.6.77",
-  "nvidia-cudnn-cu12>=9.10.2.21",
-  "nvidia-cufft-cu12>=11.3.0.4",
-  "nvidia-cufile-cu12>=1.11.1.6",
-  "nvidia-curand-cu12>=10.3.7.77",
-  "nvidia-cusolver-cu12>=11.7.1.2",
-  "nvidia-cusparse-cu12>=12.5.4.2",
-  "nvidia-cusparselt-cu12>=0.7.1",
-  "nvidia-nccl-cu12>=2.27.3",
-  "nvidia-nvjitlink-cu12>=12.6.85",
-  "nvidia-nvshmem-cu12>=3.5.19",
-  "nvidia-nvtx-cu12>=12.6.77",
-  "omegaconf>=2.3.0",
-  "opt-einsum>=3.4.0",
-  "opt-einsum-fx>=0.1.4",
-  "packaging>=25.0",
-  "pandas>=2.3.3",
-  "parso>=0.8.5",
-  "pathspec>=0.12.1",
-  "pexpect>=4.9.0",
-  "pillow>=12.0.0",
-  "platformdirs>=4.5.1",
-  "pluggy>=1.6.0",
-  "prompt-toolkit>=3.0.52",
-  "propcache>=0.4.1",
-  "protobuf>=6.33.2",
-  "psutil>=7.1.3",
-  "ptyprocess>=0.7.0",
-  "pure-eval>=0.2.3",
-  "py3dmol>=2.5.3",
-  "pyarrow>=17.0.0",
-  "pycodestyle>=2.14.0",
-  "pydantic>=2.12.5",
-  "pydantic-core>=2.41.5",
-  "pydssp>=0.9.1",
-  "pyflakes>=3.4.0",
-  "pygments>=2.19.2",
-  "pygtrie>=2.5.0",
-  "pymol-remote>=1.1.0",
-  "pyparsing>=3.2.5",
-  "pytest>=9.0.2",
-  "pytest-cov>=7.0.0",
-  "pytest-mock>=3.15.1",
-  "pytest-timeout>=2.4.0",
-  "pytest-xdist>=3.8.0",
-  "python-dateutil>=2.9.0.post0",
-  "pytokens>=0.3.0",
-  "pytorch-lightning>=2.6.0",
-  "pytz>=2025.2",
-  "pyyaml>=6.0.3",
-  "rdkit>=2025.3.6",
-  "regex>=2025.11.3",
-  "requests>=2.32.5",
-  "rich>=14.2.0",
-  "s3transfer>=0.16.0",
-  "safetensors>=0.7.0",
-  "scikit-learn>=1.8.0",
-  "scipy>=1.16.3",
-  "sentry-sdk>=2.48.0",
-  "setuptools>=80.9.0",
-  "shellingham>=1.5.4",
-  "six>=1.17.0",
-  "smmap>=5.0.2",
-  "sortedcontainers>=2.4.0",
-  "stack-data>=0.6.3",
-  "sympy>=1.14.0",
-  "tenacity>=9.1.2",
-  "threadpoolctl>=3.6.0",
-  "tokenizers>=0.21.4",
-  "toolz>=1.1.0",
-  "torch-runstats>=0.2.0",
-  "torchmetrics>=1.8.2",
-  "torchtext>=0.18.0",
-  "tqdm>=4.67.1",
-  "traitlets>=5.14.3",
-  "transformers>=4.48.1",
-  "triton>=3.4.0",
-  "typer>=0.21.1",
-  "typing-extensions>=4.15.0",
-  "typing-inspection>=0.4.2",
-  "tzdata>=2025.3",
-  "urllib3>=2.6.2",
-  "wcwidth>=0.2.14",
-  "widgetsnbextension>=4.0.15",
-  "xxhash>=3.6.0",
-  "yarl>=1.22.0",
-  "zstandard>=0.25.0",
-  "zstd>=1.5.7.2",
+  "scipy",
+  "pandas",
+  "matplotlib",
+  "pillow",
+  "loguru",
+  "tqdm",
+  "wandb",
 ]
 
 [dependency-groups]
-dev = [
-    "black>=23.0.0",
-    "flake8>=6.0.0",
-    "hypothesis>=6.70.0",
-    "isort>=5.12.0",
-    "mypy>=1.0.0",
-    "pytest>=7.0.0",
-    "pytest-cov>=4.0.0",
-    "pytest-mock>=3.10.0",
-    "pytest-timeout>=2.1.0",
-    "pytest-xdist>=3.0.0",
-]
+dev = ["pytest", "pytest-cov", "mypy", "ruff"]
 
 # PyTorch CUDA 12.6 index (so `torch`/`torchvision` come from the right place)
 [[tool.uv.index]]
@@ -221,4 +45,3 @@ torchvision = { index = "pytorch-cu126" }
 torch-scatter = { index = "pyg-cu126" }
 torch-cluster = { index = "pyg-cu126" }
 pyg-lib = { index = "pyg-cu126" }
-
diff --git a/uv.lock b/uv.lock
index d5ba22e..d84dd61 100644
--- a/uv.lock
+++ b/uv.lock
@@ -72,12 +72,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
 ]
 
-[[package]]
-name = "antlr4-python3-runtime"
-version = "4.9.3"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/3e/38/7859ff46355f76f8d19459005ca000b6e7012f2f1ca597746cbcd1fbfe5e/antlr4-python3-runtime-4.9.3.tar.gz", hash = "sha256:f224469b4168294902bb1efa80a8bf7855f24c99aef99cbefc1bcd3cce77881b", size = 117034, upload-time = "2021-11-06T17:52:23.524Z" }
-
 [[package]]
 name = "anyio"
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-    { name = "prompt-toolkit", specifier = ">=3.0.52" },
-    { name = "propcache", specifier = ">=0.4.1" },
-    { name = "protobuf", specifier = ">=6.33.2" },
-    { name = "psutil", specifier = ">=7.1.3" },
-    { name = "ptyprocess", specifier = ">=0.7.0" },
-    { name = "pure-eval", specifier = ">=0.2.3" },
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-    { name = "pyarrow", specifier = ">=17.0.0" },
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-    { name = "pydssp", specifier = ">=0.9.1" },
-    { name = "pyflakes", specifier = ">=3.4.0" },
+    { name = "esm" },
+    { name = "loguru" },
+    { name = "matplotlib" },
+    { name = "pandas" },
+    { name = "pillow" },
     { name = "pyg-lib", index = "https://data.pyg.org/whl/torch-2.8.0+cu126.html" },
-    { name = "pygments", specifier = ">=2.19.2" },
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-    { name = "tokenizers", specifier = ">=0.21.4" },
-    { name = "toolz", specifier = ">=1.1.0" },
+    { name = "scipy" },
     { name = "torch", specifier = "==2.8.0", index = "https://download.pytorch.org/whl/cu126" },
     { name = "torch-cluster", index = "https://data.pyg.org/whl/torch-2.8.0+cu126.html" },
     { name = "torch-geometric" },
-    { name = "torch-runstats", specifier = ">=0.2.0" },
     { name = "torch-scatter", index = "https://data.pyg.org/whl/torch-2.8.0+cu126.html" },
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-    { name = "torchtext", specifier = ">=0.18.0" },
     { name = "torchvision", index = "https://download.pytorch.org/whl/cu126" },
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-    { name = "tzdata", specifier = ">=2025.3" },
-    { name = "urllib3", specifier = ">=2.6.2" },
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     { name = "wandb" },
-    { name = "wcwidth", specifier = ">=0.2.14" },
-    { name = "widgetsnbextension", specifier = ">=4.0.15" },
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-    { name = "zstandard", specifier = ">=0.25.0" },
-    { name = "zstd", specifier = ">=1.5.7.2" },
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 [package.metadata.requires-dev]
 dev = [
-    { name = "black", specifier = ">=23.0.0" },
-    { name = "flake8", specifier = ">=6.0.0" },
-    { name = "hypothesis", specifier = ">=6.70.0" },
-    { name = "isort", specifier = ">=5.12.0" },
-    { name = "mypy", specifier = ">=1.0.0" },
-    { name = "pytest", specifier = ">=7.0.0" },
-    { name = "pytest-cov", specifier = ">=4.0.0" },
-    { name = "pytest-mock", specifier = ">=3.10.0" },
-    { name = "pytest-timeout", specifier = ">=2.1.0" },
-    { name = "pytest-xdist", specifier = ">=3.0.0" },
+    { name = "mypy" },
+    { name = "pytest" },
+    { name = "pytest-cov" },
+    { name = "ruff" },
 ]
 
 [[package]]
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 ]
 
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 name = "zstd"
 version = "1.5.7.2"

From a20bdfcce1b8e226d231707f1d7274195660fd45 Mon Sep 17 00:00:00 2001
From: Vratin Srivastava <vratins@andrew.cmu.edu>
Date: Wed, 4 Mar 2026 10:07:21 -0600
Subject: [PATCH 02/10] removing tests from readme, cleaning pyproject

---
 README.md      | 27 ---------------------------
 pyproject.toml |  1 -
 2 files changed, 28 deletions(-)

diff --git a/README.md b/README.md
index 0c7fc80..dc35cfd 100644
--- a/README.md
+++ b/README.md
@@ -282,30 +282,3 @@ uv run python -m scripts.inference \
 │   └── ...
 └── metrics.json        # Per-sample and summary statistics
 ```
-
-## Testing
-
-Run the test suite with pytest:
-
-```bash
-# run all tests
-uv run pytest tests/
-
-# run with coverage report
-uv run pytest tests/ --cov=src --cov-report=html
-
-# run specific test file
-uv run pytest tests/test_flow.py -v
-
-# run tests matching a pattern
-uv run pytest tests/ -k "test_forward" -v
-```
-
-### Test Categories
-
-- `test_dataset.py`: Data loading, preprocessing, and caching
-- `test_flow.py`: Flow matching training and integration
-- `test_encoder.py`: Encoder architectures and registry
-- `test_forward.py`: End-to-end forward pass validation
-- `test_gvp.py`: GVP layer equivariance and correctness
-- `test_utils.py`: Metrics, plotting, and utility functions
diff --git a/pyproject.toml b/pyproject.toml
index 1889179..3af8bbc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,6 @@ version = "0.1.0"
 requires-python = ">=3.12,<3.13"
 dependencies = [
   "torch==2.8.0",
-  "torchvision",
   "torch-geometric",
   "torch-scatter",
   "torch-cluster",

From e233a946b17d8b73808ec09b50fe5299b7d9b5e5 Mon Sep 17 00:00:00 2001
From: Doris Mai <maihuanghao@gmail.com>
Date: Mon, 9 Mar 2026 18:49:19 +0000
Subject: [PATCH 03/10] added pre-commit dependencies, removes torchvision from
 tool, and checks pymol-open-source install

---
 pyproject.toml |   7 ++--
 uv.lock        | 106 +++++++++++++++++++++++++++++++++++++------------
 2 files changed, 83 insertions(+), 30 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 3af8bbc..377b24b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -11,7 +11,7 @@ dependencies = [
   "e3nn",
   "esm",
   "biotite",
-  "pymol-open-source-whl>=3.1.0.4",
+  "pymol-open-source",
   "scipy",
   "pandas",
   "matplotlib",
@@ -22,9 +22,9 @@ dependencies = [
 ]
 
 [dependency-groups]
-dev = ["pytest", "pytest-cov", "mypy", "ruff"]
+dev = ["pytest", "pytest-cov", "mypy", "ty", "prek", "ruff"]
 
-# PyTorch CUDA 12.6 index (so `torch`/`torchvision` come from the right place)
+# PyTorch CUDA 12.6 index (so `torch` comes from the right place)
 [[tool.uv.index]]
 name = "pytorch-cu126"
 url = "https://download.pytorch.org/whl/cu126"
@@ -39,7 +39,6 @@ explicit = true
 
 [tool.uv.sources]
 torch = { index = "pytorch-cu126" }
-torchvision = { index = "pytorch-cu126" }
 
 torch-scatter = { index = "pyg-cu126" }
 torch-cluster = { index = "pyg-cu126" }
diff --git a/uv.lock b/uv.lock
index d84dd61..1d3d539 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,5 +1,5 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = "==3.12.*"
 resolution-markers = [
     "platform_machine != 'aarch64' and sys_platform == 'linux'",
@@ -910,18 +910,21 @@ wheels = [
 
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 ]
 
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 ]
 
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+version = "0.0.21"
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+]
+
 [[package]]
 name = "typing-extensions"
 version = "4.15.0"
@@ -1931,13 +1983,12 @@ dependencies = [
     { name = "pandas" },
     { name = "pillow" },
     { name = "pyg-lib" },
-    { name = "pymol-open-source-whl" },
+    { name = "pymol-open-source" },
     { name = "scipy" },
     { name = "torch" },
     { name = "torch-cluster" },
     { name = "torch-geometric" },
     { name = "torch-scatter" },
-    { name = "torchvision" },
     { name = "tqdm" },
     { name = "wandb" },
 ]
@@ -1945,9 +1996,11 @@ dependencies = [
 [package.dev-dependencies]
 dev = [
     { name = "mypy" },
+    { name = "prek" },
     { name = "pytest" },
     { name = "pytest-cov" },
     { name = "ruff" },
+    { name = "ty" },
 ]
 
 [package.metadata]
@@ -1960,13 +2013,12 @@ requires-dist = [
     { name = "pandas" },
     { name = "pillow" },
     { name = "pyg-lib", index = "https://data.pyg.org/whl/torch-2.8.0+cu126.html" },
-    { name = "pymol-open-source-whl", specifier = ">=3.1.0.4" },
+    { name = "pymol-open-source" },
     { name = "scipy" },
     { name = "torch", specifier = "==2.8.0", index = "https://download.pytorch.org/whl/cu126" },
     { name = "torch-cluster", index = "https://data.pyg.org/whl/torch-2.8.0+cu126.html" },
     { name = "torch-geometric" },
     { name = "torch-scatter", index = "https://data.pyg.org/whl/torch-2.8.0+cu126.html" },
-    { name = "torchvision", index = "https://download.pytorch.org/whl/cu126" },
     { name = "tqdm" },
     { name = "wandb" },
 ]
@@ -1974,9 +2026,11 @@ requires-dist = [
 [package.metadata.requires-dev]
 dev = [
     { name = "mypy" },
+    { name = "prek" },
     { name = "pytest" },
     { name = "pytest-cov" },
     { name = "ruff" },
+    { name = "ty" },
 ]
 
 [[package]]

From eb7cf4a1a3892f88def78d771dbad3a7d9897a50 Mon Sep 17 00:00:00 2001
From: Vratin Srivastava <vratins@andrew.cmu.edu>
Date: Mon, 9 Mar 2026 14:27:52 -0500
Subject: [PATCH 04/10] added ruff to pyproject deps and switched to ty from
 mypy

---
 pyproject.toml | 18 +++++++++++++++++-
 1 file changed, 17 insertions(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 377b24b..4aeb3b8 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -22,7 +22,7 @@ dependencies = [
 ]
 
 [dependency-groups]
-dev = ["pytest", "pytest-cov", "mypy", "ty", "prek", "ruff"]
+dev = ["pytest", "pytest-cov", "ty", "prek", "ruff"]
 
 # PyTorch CUDA 12.6 index (so `torch` comes from the right place)
 [[tool.uv.index]]
@@ -43,3 +43,19 @@ torch = { index = "pytorch-cu126" }
 torch-scatter = { index = "pyg-cu126" }
 torch-cluster = { index = "pyg-cu126" }
 pyg-lib = { index = "pyg-cu126" }
+
+[tool.ruff.lint]
+fixable = ["I001", "F401", "UP"]
+ignore = ["E402", "E721", "E731", "E741", "F722", "F821", "UP015", "UP037"]
+select = ["E", "F", "I001", "UP"]
+
+[tool.ruff.lint.flake8-import-conventions.extend-aliases]
+"collections" = "co"
+"functools" = "ft"
+"itertools" = "it"
+
+[tool.ruff.lint.isort]
+combine-as-imports = true
+extra-standard-library = ["typing_extensions"]
+lines-after-imports = 2
+order-by-type = false

From eb1f1cdcefbc9f22f7646e0313b5a09cf86126f5 Mon Sep 17 00:00:00 2001
From: Vratin Srivastava <vratins@andrew.cmu.edu>
Date: Fri, 20 Mar 2026 12:19:35 -0500
Subject: [PATCH 05/10] adding documentation for how dataset is processed

---
 README.md | 65 +++++++++++++++++++++++++++++++++++++++++++++----------
 1 file changed, 53 insertions(+), 12 deletions(-)

diff --git a/README.md b/README.md
index dc35cfd..aa1a9be 100644
--- a/README.md
+++ b/README.md
@@ -55,6 +55,35 @@ Each PDB should have `_final` suffix and contain:
 - Protein atoms (used as conditioning context)
 - Water molecules (HOH residues, used as ground truth)
 
+### Data Processing Pipeline
+
+WaterFlow processes PDB files through several stages to create training-ready graph representations:
+
+**PDB Parsing**
+- Uses Biotite to extract protein atoms and water molecules (HOH residues)
+- Modified residues are mapped to standard amino acids (MSE→M, SEC→U)
+- Hydrogen atoms are excluded; only the first model is used
+- For atoms with alternate conformations, the highest-occupancy conformer is selected
+
+**Crystal Contact Detection**
+- Uses PyMOL's `symexp` to generate symmetry mates within 5.0Å cutoff
+- Symmetry mate atoms are included as additional protein context when `include_mates=True`
+- Mate atoms are stored separately for proper handling during training
+
+**Graph Representation**
+- Node types: `protein` (ASU + symmetry mates), `water` (ground truth)
+- Edge types (defined in `src/constants.py`):
+  - `('protein', 'pp', 'protein')`: protein-protein edges
+  - `('protein', 'pw', 'water')`: protein to water
+  - `('water', 'wp', 'protein')`: water to protein
+  - `('water', 'ww', 'water')`: water-water edges
+- Default edge cutoff: 8.0Å (`RBF_CUTOFF` in constants.py)
+
+**Feature Encoding**
+- Element vocabulary (15 elements + "other" bucket = 16 dims):
+  `C, N, O, S, P, SE, MG, ZN, CA, FE, NA, K, CL, F, BR`
+- Edge features: RBF distance encoding (16 Bessel basis functions)
+
 ### Split File Format
 
 Split files are plain text with one PDB entry per line:
@@ -68,21 +97,33 @@ Split files are plain text with one PDB entry per line:
 
 ### Cache Directory Structure
 
-Preprocessed data is cached under `--processed_dir`:
+Preprocessed data is cached under `--processed_dir` in a three-layer architecture:
 
 ```
 <processed_dir>/
-├── geometry/           # Cached graph structures (protein + water nodes)
-│   ├── 1abc_final.pt
-│   └── ...
-├── esm/                # ESM embeddings (per-residue)
-│   ├── 1abc_final.pt
-│   └── ...
-└── slae/               # SLAE embeddings (per-residue)
-    ├── 1abc_final.pt
-    └── ...
+├── geometry/              # Graph structures (or geometry_mates/ when include_mates=True)
+│   └── <pdb_id>_final.pt
+│       - protein_pos: centered protein coordinates (N, 3)
+│       - protein_x: element one-hot encoding (N, 16)
+│       - protein_res_idx: residue indices for grouping
+│       - water_pos, water_x: water coordinates and features
+│       - mate_pos, mate_x, mate_res_idx: symmetry mate data (if included)
+├── esm/                   # ESM embeddings (per-residue)
+│   └── <pdb_id>_final.pt
+│       - residue_embeddings: ESM3 embeddings (N_res, embed_dim)
+│       - sequence: extracted sequence string
+│       - num_residues: residue count
+└── slae/                  # SLAE embeddings (per-atom, 128-dim)
+    └── <pdb_id>_final.pt
+        - node_embeddings: atom-level embeddings aligned to geometry order
+        - atom37_coords: standard atom37 coordinates (N_res, 37, 3)
 ```
 
+**Cache Generation Notes:**
+- Geometry cache is generated automatically when `preprocess=True` (default)
+- ESM/SLAE caches require running the respective `generate_*_embeddings.py` scripts first
+- Preprocessing failures are logged to `<geometry_dir>/preprocessing_failures.log`
+
 ## Environment Setup
 
 We use `uv` for our environment and package management, with Python 3.12.
@@ -220,7 +261,7 @@ These checks determine whether a structure is included in training:
 | `--max_com_dist` | `25.0` | Max protein-water center-of-mass distance (A) |
 | `--max_clash_fraction` | `0.05` | Max fraction of waters clashing with protein |
 | `--clash_dist` | `2.0` | Distance threshold for clash detection (A) |
-| `--min_water_residue_ratio` | `0.6` | Minimum waters per residue ratio |
+| `--min_water_residue_ratio` | `0.8` | Minimum waters per residue ratio |
 
 ### Per-Water Quality Filters
 
@@ -228,7 +269,7 @@ These filters remove individual low-quality waters (can be toggled):
 
 | Parameter | Default | Toggle Flag | Description |
 |-----------|---------|-------------|-------------|
-| `--max_protein_dist` | `5.0` | `--no_filter_by_distance` | Remove waters far from protein |
+| `--max_protein_dist` | `6.0` | `--no_filter_by_distance` | Remove waters far from protein |
 | `--min_edia` | `0.4` | `--no_filter_by_edia` | Remove waters with low EDIA scores |
 | `--max_bfactor_zscore` | `1.5` | `--no_filter_by_bfactor` | Remove waters with high B-factor |
 

From cda6fa52a2d1e99112ec09aef7b6babfa98b9343 Mon Sep 17 00:00:00 2001
From: Vratin Srivastava <vratins@andrew.cmu.edu>
Date: Fri, 20 Mar 2026 12:39:56 -0500
Subject: [PATCH 06/10] relative paths + adding numpy to pyproject

---
 README.md      | 4 ++--
 pyproject.toml | 1 +
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index aa1a9be..80111b7 100644
--- a/README.md
+++ b/README.md
@@ -234,7 +234,7 @@ To resume training from a checkpoint, you can load the model weights and optimiz
 | `--scheduler` | `cosine` | LR scheduler: `cosine`, `step`, or `none` |
 | `--warmup_steps` | `0` | Linear warmup steps |
 | `--processed_dir` | `~/flow_cache/` | Cache directory for preprocessed data |
-| `--save_dir` | `/home/srivasv/flow_checkpoints` | Directory to save checkpoints |
+| `--save_dir` | `../flow_checkpoints` | Directory to save checkpoints |
 | `--save_every` | `10` | Save checkpoint every N epochs |
 | `--eval_every` | `5` | Run evaluation every N epochs |
 
@@ -245,7 +245,7 @@ Training automatically logs to W&B. Configure with:
 | Argument | Default | Description |
 |----------|---------|-------------|
 | `--wandb_project` | `water-flow` | W&B project name |
-| `--wandb_dir` | `/home/srivasv/wandb_logs` | Local W&B log directory |
+| `--wandb_dir` | `../wandb_logs` | Local W&B log directory |
 | `--run_name` | auto-generated | Custom run name (format: `YYYYMMDD_HHMMSS_encoder_layers_hidden`) |
 
 ## Quality Filtering
diff --git a/pyproject.toml b/pyproject.toml
index d0c8a00..5f3f663 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -14,6 +14,7 @@ dependencies = [
   "pymol-open-source",
   "scipy",
   "pandas",
+  "numpy",
   "matplotlib",
   "pillow",
   "loguru",

From 6f1c3265a6f0082d0881e58e98045f61ec778bd7 Mon Sep 17 00:00:00 2001
From: Vratin Srivastava <vratins@andrew.cmu.edu>
Date: Mon, 23 Mar 2026 15:23:41 -0500
Subject: [PATCH 07/10] adjusting readme for source code changes

---
 README.md | 13 +++++--------
 1 file changed, 5 insertions(+), 8 deletions(-)

diff --git a/README.md b/README.md
index 80111b7..167b1fe 100644
--- a/README.md
+++ b/README.md
@@ -11,24 +11,21 @@ WaterFlow/
 │   ├── flow.py             # FlowMatcher and FlowWaterGVP model
 │   ├── gvp.py              # Geometric Vector Perceptron layers
 │   ├── gvp_encoder.py      # GVP-based protein encoder
-│   ├── esm_encoder.py      # ESM embedding encoder
-│   ├── slae_encoder.py     # SLAE embedding encoder
-│   ├── encoder_base.py     # Encoder registry and factory
+│   ├── encoder_base.py     # Encoder registry and factory (includes ESM/SLAE)
 │   ├── constants.py        # Shared constants (RBF bins, etc.)
 │   └── utils.py            # Metrics, plotting, logging utilities
 ├── scripts/                # Executable scripts
 │   ├── train.py            # Training pipeline
 │   ├── inference.py        # Run inference on trained models
 │   ├── generate_esm_embeddings.py   # Precompute ESM embeddings
-│   ├── generate_slae_embeddings.py  # Precompute SLAE embeddings
-│   ├── qc_waters.py        # Quality control for water molecules 
-│   └── qc_symmetry_mates.py        # Quality control for crystal mates
+│   └── generate_slae_embeddings.py  # Precompute SLAE embeddings
 ├── tests/                  # Test suite
 │   ├── test_dataset.py     # Dataset and preprocessing tests
 │   ├── test_flow.py        # Flow matching tests
 │   ├── test_encoder.py     # Encoder tests
 │   ├── test_forward.py     # End-to-end forward pass tests
 │   ├── test_gvp.py         # GVP layer tests
+│   ├── test_train_config.py # Training configuration tests
 │   └── test_utils.py       # Utility function tests
 └── splits/                 # Train/val/test split files
     ├── train_list_0.95.txt # Training set (95% of data)
@@ -261,7 +258,7 @@ These checks determine whether a structure is included in training:
 | `--max_com_dist` | `25.0` | Max protein-water center-of-mass distance (A) |
 | `--max_clash_fraction` | `0.05` | Max fraction of waters clashing with protein |
 | `--clash_dist` | `2.0` | Distance threshold for clash detection (A) |
-| `--min_water_residue_ratio` | `0.8` | Minimum waters per residue ratio |
+| `--min_water_residue_ratio` | `0.6` | Minimum waters per residue ratio |
 
 ### Per-Water Quality Filters
 
@@ -269,7 +266,7 @@ These filters remove individual low-quality waters (can be toggled):
 
 | Parameter | Default | Toggle Flag | Description |
 |-----------|---------|-------------|-------------|
-| `--max_protein_dist` | `6.0` | `--no_filter_by_distance` | Remove waters far from protein |
+| `--max_protein_dist` | `5.0` | `--no_filter_by_distance` | Remove waters far from protein |
 | `--min_edia` | `0.4` | `--no_filter_by_edia` | Remove waters with low EDIA scores |
 | `--max_bfactor_zscore` | `1.5` | `--no_filter_by_bfactor` | Remove waters with high B-factor |
 

From 090c7b4dae5fb69037a77dc1ed1fb1bbe3f369c7 Mon Sep 17 00:00:00 2001
From: Vratin Srivastava <vratins@andrew.cmu.edu>
Date: Mon, 23 Mar 2026 15:36:50 -0500
Subject: [PATCH 08/10] clarifying comments; manual install updates; edia specs

---
 README.md | 19 ++++++++++++++++---
 1 file changed, 16 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 167b1fe..330297d 100644
--- a/README.md
+++ b/README.md
@@ -104,7 +104,11 @@ Preprocessed data is cached under `--processed_dir` in a three-layer architectur
 │       - protein_x: element one-hot encoding (N, 16)
 │       - protein_res_idx: residue indices for grouping
 │       - water_pos, water_x: water coordinates and features
-│       - mate_pos, mate_x, mate_res_idx: symmetry mate data (if included)
+│       - num_asu_protein: ASU atom count (mate boundary metadata)
+│       # Note: When include_mates=True, mate atoms are concatenated into
+│       # protein_pos/protein_x. Recover boundaries via:
+│       #   ASU atoms = protein_pos[:num_asu_protein]
+│       #   Mate atoms = protein_pos[num_asu_protein:]
 ├── esm/                   # ESM embeddings (per-residue)
 │   └── <pdb_id>_final.pt
 │       - residue_embeddings: ESM3 embeddings (N_res, embed_dim)
@@ -138,7 +142,8 @@ source water/bin/activate
 uv pip install torch==2.8.0
 uv pip install torch_geometric
 uv pip install torch_cluster torch_scatter pyg_lib -f https://data.pyg.org/whl/torch-2.8.0+cu126.html
-uv pip install biotite wandb Bio networkx e3nn pytest pytest-cov
+uv pip install esm biotite pymol-open-source scipy pandas numpy matplotlib pillow loguru tqdm wandb e3nn
+uv pip install pytest pytest-cov  # dev dependencies
 ```
 
 If you have trouble installing torch_cluster or scatter, I would suggest changing the cuda version in the wheel.
@@ -234,6 +239,9 @@ To resume training from a checkpoint, you can load the model weights and optimiz
 | `--save_dir` | `../flow_checkpoints` | Directory to save checkpoints |
 | `--save_every` | `10` | Save checkpoint every N epochs |
 | `--eval_every` | `5` | Run evaluation every N epochs |
+| `--edia_dir` | (none) | Root directory for EDIA CSV files |
+| `--min_edia` | `0.4` | Minimum EDIA score threshold for waters |
+| `--no_filter_by_edia` | - | Disable EDIA-based water filtering |
 
 ### Weights & Biases Logging
 
@@ -275,7 +283,12 @@ These filters remove individual low-quality waters (can be toggled):
 
 EDIA measures how well an atom's position is supported by the experimental electron density map. Higher EDIA scores indicate more reliable atomic positions.
 
-EDIA results are expected at: `<edia_dir>/<pdb_id>/<pdb_id>_residue_stats.csv`
+**Configuration:**
+- EDIA filtering is enabled by default but only activates if `--edia_dir` is provided
+- If `--edia_dir` is not set, EDIA filtering is skipped (with a warning logged)
+- Use `--no_filter_by_edia` to explicitly disable EDIA filtering
+
+**Directory structure:** `{edia_dir}/{pdb_id}/{pdb_id}_residue_stats.csv`
 
 </details>
 

From d5963837ea977c1cab4be2cc7dd61415d1dd74d3 Mon Sep 17 00:00:00 2001
From: Vratin Srivastava <vratins@andrew.cmu.edu>
Date: Mon, 23 Mar 2026 16:05:49 -0500
Subject: [PATCH 09/10] pyproject

---
 pyproject.toml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pyproject.toml b/pyproject.toml
index 5f3f663..3445131 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -20,6 +20,7 @@ dependencies = [
   "loguru",
   "tqdm",
   "wandb",
+  "jaxtyping",
 ]
 
 [dependency-groups]

From c62aef086a834ac2311c0b6f53b3d46a758e9e7f Mon Sep 17 00:00:00 2001
From: Vratin Srivastava <vratins@andrew.cmu.edu>
Date: Tue, 24 Mar 2026 11:40:24 -0500
Subject: [PATCH 10/10] making the parsing documentation clearer

---
 README.md | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 330297d..bbd681c 100644
--- a/README.md
+++ b/README.md
@@ -58,8 +58,10 @@ WaterFlow processes PDB files through several stages to create training-ready gr
 
 **PDB Parsing**
 - Uses Biotite to extract protein atoms and water molecules (HOH residues)
-- Modified residues are mapped to standard amino acids (MSE→M, SEC→U)
-- Hydrogen atoms are excluded; only the first model is used
+- Modified residues are retained during structure parsing and geometry preprocessing
+- When generating ESM embeddings, modified residues are mapped to encoder-compatible amino acid identities (e.g., MSE→M/MET, SEC→U/SEC)
+- Hydrogen atoms are excluded
+- Only the first model is used
 - For atoms with alternate conformations, the highest-occupancy conformer is selected
 
 **Crystal Contact Detection**