Easy Installation

This guide helps you install PSAIA with basic features. We recommend building PSAIA with Docker to avoid dependency issues. We recommend compiling PSAIA(and possibly its requirements) from the source code using the latest compiler for the best performace. You can also deploy PSAIA without building by Docker . Please note that PSAIA only supports Linux; for Windows users, please consider using WSL or docker.

Prerequisites

This program needs Naccess, you can download it if from http://www.bioinf.manchester.ac.uk/naccess/ and then put the directory named naccess2.1.1 in Program/.

Install requirements

Some of these packages can be installed with popular package management system, such as apt and yum:

sudo apt update && sudo apt install -y libopenblas-openmp-dev liblapack-dev libscalapack-mpi-dev libelpa-dev libfftw3-dev libcereal-dev libxc-dev g++ make cmake bc git lib32z1

Please refer to our [guide](Stephen523/MIALAB: A repository for MIALAB (github.com)) on installing requirements.

Get PSAIA source code

Of course a copy of PSAIA source code is required, which can be obtained via one of the following choices:

Clone the whole repo with git: `git clone https://github.com/Stephen523/MIALAB.git
Clone the minimum required part of repo: git clone https://github.com/Stephen523/MIALAB.git --depth=1
Get the source code of a stable version from here

Update to latest release

Please check the release page for the release note of a new version.

It is OK to download the new source code from beginning following the previous step.

To update your cloned git repo in-place:

git remote -v
# Check if the output contains the line below
# origin https://github.com/deepmodeling/abacus-develop.git (fetch)
# The remote name is marked as "upstream" if you clone the repo from your own fork.

# Replace "origin" with "upstream" or the remote name corresponding to deepmodeling/abacus-develop if necessary
git fetch origin
git checkout v3.2.0 # Replace the tag with the latest version
git describe --tags # Verify if the tag has been successfully checked out

Then proceed to the Build and Install part. If you encountered errors, try remove the build directory first and reconfigure.

To use the codes under active development:

git checkout develop
git pull

Run

Put pdb files of proteins in the folder named /data/pdb/.

Then run the following order to run:
bash main.sh
The result of each chain starts with “chain x”,which shows the residue patchs that is most likely to be a protein binding sites in this chain. The patch number can be modified in work/sort_patch.sh.

Then, you will get the results in the folder: /result/

Container Deployment

Please note that containers target at developing and testing, but not massively parallel computing for production. Docker has a bad support to MPI, which may cause performance degradation.

We’ve built a ready-for-use version of ABACUS with docker here. For a quick start: pull the image, prepare the data, run container. Instructions on using the image can be accessed in Dockerfile. A mirror is available by docker pull registry.dp.tech/deepmodeling/abacus.

We also offer a pre-built docker image containing all the requirements for development. Please refer to our Package Page.

The project is ready for VS Code development container. Please refer to Developing inside a Container. Choose Open a Remote Window -> Clone a Repository in Container Volume in VS Code command palette, and put the git address of ABACUS when prompted.

For online development environment, we support GitHub Codespaces: Create a new Codespace

We also support Gitpod: Open in Gitpod