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

---

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

---

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 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

---

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)