AngularQA is a single-model quality assessment tool to evaluate quality of predicted protein structures. It is built on a new representation that converts raw atom information into a series of carbon-alpha (Cα) atoms with side-chain information, defined by their dihedral angles and bond lengths to the prior residue. An LSTM network is used to predict the quality by treating each amino acid as a time-step and consider the final value returned by the LSTM cells.
Conover, Matthew, Max Staples, Dong Si, Miao Sun, and Renzhi Cao. "AngularQA: protein model quality assessment with LSTM networks." Computational and Mathematical Biophysics 7, no. 1 (2019): 1-9.
Ubuntu, Centos
(1). Python3.5
(2). TensorFlow
sudo pip install tensorflow
GPU is NOT needed.
(3) Install Keras:
sudo pip install keras
(4) Install the h5py library:
sudo pip install h5py
As reference, here is the environment I have used for those packages: python==3.5.6 h5py==2.9.0 Keras==2.3.1 Keras-Applications==1.0.8 Keras-Preprocessing==1.1.0 numpy==1.16.2 tensorflow==1.13.0rc1 tensorflow-estimator==1.13.0rc0 tensorflow-gpu==1.2.1
You could provide one PDB format model or a folder with several PDB format models for this software. Here are examples to test:
#cd script
#python3 AngularQA.py ../test/T0759.pdb ../test/Prediction_singleModel
#python3 AngularQA.py ../test/Models ../test/Prediction_ModelPool
You should be able to find a file named AngularPrediction.txt in the output folder.
Developed by Matthew Conover and Prof. Renzhi Cao at Pacific Lutheran University:
Please contact Renzhi Cao for any questions: caora@plu.edu (PI)