RefineGNN - Iterative refinement graph neural network for antibody sequence-structure co-design (RefineGNN)

Overview

Iterative refinement graph neural network for antibody sequence-structure co-design (RefineGNN)

This is the implementation of our ICLR 2022 paper: https://arxiv.org/pdf/2110.04624.pdf

Warning: this repo is still under construction...

Language model and CDR structure prediction (Section 4.1)

Antibody structure data is retreived from the Structural Antibody Database (SAbDab). The training, validation, and test sets are provided in data/sabdab. Please decompress the files in that folder. To train a generative model for CDR-H3, please run

python ab_train.py --cdr_type 3 

Antigen-binding antibody design (Section 4.2)

antibody-antigen binding data is provided in data/rabd. To train a generative model, please run

python ab_train.py --train_path data/rabd/train.jsonl --val_path data/rabd/val.jsonl --test_path data/rabd/test.jsonl
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Comments
  • do we need to train a mAb/antigen pair to redesign the CDRs?

    do we need to train a mAb/antigen pair to redesign the CDRs?

    We have a few cases of mAb/antigen pairs where we know there is or isn't binding, but we don't know the exact binding mechanism (epitope/paratope).

    If we want to increase binding or stability of a mAb/antigen pair with RefineGNN, starting with an Alphafold multimer pdb of the mAb Fv and the antigen (which may be wrong), how do we run RefineGNN to redesign the CDRs to increase the affinity/binding? Do we need to train our mAb/antigen pairs to redesign the CDRs?

    opened by avilella 0
  • Toward the biological meaning of generating CDR region with remaining sequence?

    Toward the biological meaning of generating CDR region with remaining sequence?

    Hi, thanks for the great work! I have a problem toward the biological meaning of the work. Since the CDR region is antigen-specific, how can we generate CDR sequence and structure with only remaining sequence give and without antigen-conditioned? I hope you can help me with my confusion.

    opened by YifanDengWHU 0
  • create a docker container for reproducible model inference

    create a docker container for reproducible model inference

    Hi Wengong,

    I read the RefineGNN paper today and would love to run it within a docker container. I created a dockerfile that I hope fulfills the installation requirements. One thing I noticed was a difficulty around installing torch==1.8.2 - the long term support version seems to be not available via pip install. Have you seen this problem, too? I simply used torch==1.9.0 in this build - It seems like one might get more lucky using a conda version of pytorch-lts if 1.8.2 is a strict requirement.

    How have you installing torch==1.8.2?

    opened by NiklasTR 0
Owner
Wengong Jin
Wengong Jin
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