Installing the OpenADMET PXR anvil prediction

I had a couple of issues installing the PXR model from OpenAMET on my Apple Silicon Mac (https://huggingface.co/openadmet/pxr-chemeleon-baseline) so I thought I’d post what I got to work. It may be my setup is different in some way but this worked for me.

This is baseline model a single task CheMeleon model trained on pEC50 data curated from ChEMBL for PXR. It is a no split model, meaning it has been trained with no data allocated to validation and test sets and with just a training set of 1.0.

Instructions for installing and running the pxr-chemeleon-v1 model, which predicts PXR bioactivity for a set of compounds, using OpenADMET’s Anvil framework (openadmet-models).

Prerequisites

Before you start, make sure the following are installed on your computer:

• git — used to download the model and code
• git lfs — a git extension needed to download the (large) model files
• conda or mamba — used to create an isolated Python environment

You can check whether you already have these by running:

git --version
git lfs --version
conda --version   # or: mamba --version

If any of these commands fail, install the missing tool before continuing.

Git is automatically installed with Xcode Command Line Tools. If Git is not installed, entering git in the Terminal will trigger a Mac dialog asking if you would like to Install Xcode Command Line Tools. Click “Install” to begin the download and installation process.

Use Homebrew to install git lfs,

brew install git-lfs

Instructions for installing conda https://docs.conda.io/projects/conda/en/latest/user-guide/install/macos.html

Installation

Open a terminal and work through the following steps in order, running each
command one at a time and waiting for it to finish before moving to the next.

Enable Git LFS, this only needs to be done once.

git lfs install

Download the model

I created a folder called PXR and moved into it

cd /Users/chrisswain/Projects/PXR

Then cloned the model into the folder

git clone https://github.com/OpenADMET/openadmet-models

cd openadmet-models/

Then created the conda environment

conda env create -f devtools/conda-envs/openadmet-models.yaml

Then activated the environment

conda activate openadmet-models
pip install -e .

I then ran a calculation using full paths to files provided.

openadmet-models % openadmet predict \
    --input-path /Users/chrisswain/Projects/PXR/pxr-chemeleon-v1/compounds_for_inference.csv \
    --input-col OPENADMET_CANONICAL_SMILES \
    --model-dir  /Users/chrisswain/Projects/PXR/pxr-chemeleon-v1/anvil_training/ \
    --output-csv  /Users/chrisswain/Projects/PXR/pxr-chemeleon-v1/predictions.csv \
    --accelerator cpu
    
INFO     Finished prediction                                                                             
INFO     Predictions saved to /Users/chrisswain/Projects/PXR/pxr-chemeleon-v1/predictions.csv  

To run your own prediction you need to edit the path to the input file

–input-path /Users/chrisswain/Projects/PXR/pxr-chemeleon-v1/compounds_for_inference.csv

and the name of the column containing the SMILES

–input-col OPENADMET_CANONICAL_SMILES

If you want to use the gpu edit

–accelerator cpu

If you are also interested in docking ligands into PXR this PYMOL session is a great start. https://macinchem.org/2026/08/07/openadmet-pxr-challenge-pymol-session-file/