Enhancing protein backbone angle prediction by using simpler models of deep neural networks

Fereshteh Mataeimoghadam*, M. A. Hakim Newton, Abdollah Dehzangi, Abdul Karim, B. Jayaram, Shoba Ranganathan, Abdul Sattar

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    16 Citations (Scopus)
    16 Downloads (Pure)


    Protein structure prediction is a grand challenge. Prediction of protein structures via the representations using backbone dihedral angles has recently achieved significant progress along with the on-going surge of deep neural network (DNN) research in general. However, we observe that in the protein backbone angle prediction research, there is an overall trend to employ more and more complex neural networks and then to throw more and more features to the neural networks. While more features might add more predictive power to the neural network, we argue that redundant features could rather clutter the scenario and more complex neural networks then just could counterbalance the noise. From artificial intelligence and machine learning perspectives, problem representations and solution approaches do mutually interact and thus affect performance. We also argue that comparatively simpler predictors can more easily be reconstructed than the more complex ones. With these arguments in mind, we present a deep learning method named Simpler Angle Predictor (SAP) to train simpler DNN models that enhance protein backbone angle prediction. We then empirically show that SAP can significantly outperform existing state-of-the-art methods on well-known benchmark datasets: for some types of angles, the differences are 6–8 in terms of mean absolute error (MAE). The SAP program along with its data is available from the website https://gitlab.com/mahnewton/sap.

    Original languageEnglish
    Article number19430
    Pages (from-to)1-12
    Number of pages12
    JournalScientific Reports
    Issue number1
    Publication statusPublished - 10 Nov 2020

    Bibliographical note

    Copyright the Author(s) 2020. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

    Author correction: Mataeimoghadam, F., Newton, M.A.H., Dehzangi, A. et al. Author Correction: Enhancing protein backbone angle prediction by using simpler models of deep neural networks. Sci Rep 11, 18072 (2021). https://doi.org/10.1038/s41598-021-96666-0


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