AngularQA
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.
Citation
Matthew Conover, Max Staples, Dong Si, Renzhi Cao. "AngularQA: Protein Model Quality Assessment with LSTM Networks", submitted, 2018.
Test Environment
Ubuntu, Centos
Requirements
(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 python-h5py
Run software
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)