# 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
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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.

# Test Environment
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Ubuntu, Centos

# Requirements
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(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

# Run software
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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.


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Developed by Matthew Conover and Prof. Renzhi Cao at Pacific Lutheran University:

Please contact Renzhi Cao for any questions: caora@plu.edu (PI)