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https://github.com/luost26/diffab
✌🏻 Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures (NeurIPS 2022)
https://github.com/luost26/diffab
Last synced: 13 days ago
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✌🏻 Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures (NeurIPS 2022)
- Host: GitHub
- URL: https://github.com/luost26/diffab
- Owner: luost26
- License: apache-2.0
- Created: 2022-10-06T03:42:57.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2023-06-29T07:04:04.000Z (over 1 year ago)
- Last Synced: 2024-10-10T22:14:35.777Z (29 days ago)
- Language: Python
- Homepage:
- Size: 2.86 MB
- Stars: 270
- Watchers: 4
- Forks: 41
- Open Issues: 16
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# DiffAb
Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures (NeurIPS 2022)
[[Paper]](https://www.biorxiv.org/content/10.1101/2022.07.10.499510.abstract)[[Demo]](https://huggingface.co/spaces/luost26/DiffAb)
## Install
### Environment
```bash
conda env create -f env.yaml -n diffab
conda activate diffab
```
The default `cudatoolkit` version is 11.3. You may change it in [`env.yaml`](./env.yaml).
### Datasets and Trained Weights
Protein structures in the `SAbDab` dataset can be downloaded [**here**](https://opig.stats.ox.ac.uk/webapps/newsabdab/sabdab/archive/all/). Extract `all_structures.zip` into the `data` folder.
The `data` folder contains a snapshot of the dataset index (`sabdab_summary_all.tsv`). You may replace the index with the latest version [**here**](https://opig.stats.ox.ac.uk/webapps/newsabdab/sabdab/summary/all/).
Trained model weights are available [**here** (Hugging Face)](https://huggingface.co/luost26/DiffAb/tree/main) or [**here** (Google Drive)](https://drive.google.com/drive/folders/15ANqouWRTG2UmQS_p0ErSsrKsU4HmNQc?usp=sharing).
### [Optional] HDOCK
HDOCK is required to design CDRs for antigens without bound antibody frameworks. Please download HDOCK [**here**](http://huanglab.phys.hust.edu.cn/software/hdocklite/) and put the `hdock` and `createpl` programs into the [`bin`](./bin) folder.
### [Optional] PyRosetta
PyRosetta is required to relax the generated structures and compute binding energy. Please follow the instruction [**here**](https://www.pyrosetta.org/downloads) to install.
### [Optional] Ray
Ray is required to relax and evaluate the generated antibodies. Please install Ray using the following command:
```bash
pip install -U ray
```
## Design Antibodies
5 design modes are available. Each mode corresponds to a config file in the `configs/test` folder:
| Config File | Description |
| ------------------------ | ------------------------------------------------------------ |
| `codesign_single.yml` | Sample both the **sequence** and **structure** of **one** CDR. |
| `codesign_multicdrs.yml` | Sample both the **sequence** and **structure** of **all** the CDRs simultaneously. |
| `abopt_singlecdr.yml` | Optimize the **sequence** and **structure** of **one** CDR. |
| `fixbb.yml` | Sample only the **sequence** of **one** CDR (fix-backbone sequence design). |
| `strpred.yml` | Sample only the **structure** of **one** CDR (structure prediction). |
### Antibody-Antigen Complex
Below is the usage of `design_pdb.py`. It samples CDRs for antibody-antigen complexes. The full list of options can be found in [`diffab/tools/runner/design_for_pdb.py`](diffab/tools/runner/design_for_pdb.py).
```bash
python design_pdb.py \
\
--heavy \
--light \
--config
```
The `--heavy` and `--light` options can be omitted as the script can automatically identify them with AbNumber and ANARCI.
The below example designs the six CDRs separately for the `7DK2_AB_C` antibody-antigen complex.
```bash
python design_pdb.py ./data/examples/7DK2_AB_C.pdb \
--config ./config/test/codesign_single.yml
```
### Antigen Only
HDOCK is required to design antibodies for antigens without bound antibody structures (see above for instructions on installing HDOCK). Below is the usage of `design_dock.py`.
```bash
python design_dock.py \
--antigen \
--antibody \
--config
```
The `--antibody` option is optional and the default antibody template is [`3QHF_Fv.pdb`](data/examples/3QHF_Fv.pdb). The full list of options can be found in the script.
Below is an example that designs antibodies for SARS-CoV-2 Omicron RBD.
```python
python design_dock.py \
--antigen ./data/examples/Omicron_RBD.pdb \
--config ./config/test/codesign_multicdrs.yml
```
## Train
```bash
python train.py ./configs/train/
```
## Reference
```bibtex
@inproceedings{luo2022antigenspecific,
title={Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures},
author={Shitong Luo and Yufeng Su and Xingang Peng and Sheng Wang and Jian Peng and Jianzhu Ma},
booktitle={Advances in Neural Information Processing Systems},
editor={Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},
year={2022},
url={https://openreview.net/forum?id=jSorGn2Tjg}
}
```