Predicting Proteolysis in Complex Proteomes Using Deep Learning
Abstract
:1. Introduction
2. Results and Discussion
2.1. Accurate Prediction of Protease Cleavage Sites in Native ECM Proteins Is Challenging
2.2. Protease Cleavage Site Prediction Performance Can Be Improved Using a Deep Bidirectional Recurrent Neural Network Architecture
2.3. Development of a Web Tool to Predict Protein Susceptibilities: Step #1 Amino Acid Composition
2.4. Development of a Webtool to Predict Protein Susceptibilities: Step #2 Integration of Protease Cleavage Site Prediction Models
3. Materials and Methods
3.1. Dataset Collection
3.2. Deep RNN Protease Model
3.2.1. Evaluation Metrics
3.2.2. Feature Extraction
3.2.3. One-Hot Encoding
3.2.4. Train, Test and Validate Data Split
3.2.5. Architecture of the Deep RNN
3.3. UVR/ROS and Protease MPSC Susceptibility Model Calculations
3.4. LC–MS/MS Methods for Generating Experimental Testing Dataset
3.4.1. Cell Culture
3.4.2. HDF-Deposited ECM In Vitro
3.4.3. MMP9 Degradation of ECM and DCN/VTN In Vitro
3.4.4. HDF-Deposited ECM Sample Preparation
3.4.5. DCN and VTN Gel Sample Preparation
3.4.6. Peptide Preparation for Mass Spectrometry
3.4.7. Liquid Chromatography–Tandem Mass Spectrometry
3.5. Webserver Development and Data Visualization
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Ozols, M.; Eckersley, A.; Platt, C.I.; Stewart-McGuinness, C.; Hibbert, S.A.; Revote, J.; Li, F.; Griffiths, C.E.M.; Watson, R.E.B.; Song, J.; et al. Predicting Proteolysis in Complex Proteomes Using Deep Learning. Int. J. Mol. Sci. 2021, 22, 3071. https://doi.org/10.3390/ijms22063071
Ozols M, Eckersley A, Platt CI, Stewart-McGuinness C, Hibbert SA, Revote J, Li F, Griffiths CEM, Watson REB, Song J, et al. Predicting Proteolysis in Complex Proteomes Using Deep Learning. International Journal of Molecular Sciences. 2021; 22(6):3071. https://doi.org/10.3390/ijms22063071
Chicago/Turabian StyleOzols, Matiss, Alexander Eckersley, Christopher I. Platt, Callum Stewart-McGuinness, Sarah A. Hibbert, Jerico Revote, Fuyi Li, Christopher E. M. Griffiths, Rachel E. B. Watson, Jiangning Song, and et al. 2021. "Predicting Proteolysis in Complex Proteomes Using Deep Learning" International Journal of Molecular Sciences 22, no. 6: 3071. https://doi.org/10.3390/ijms22063071
APA StyleOzols, M., Eckersley, A., Platt, C. I., Stewart-McGuinness, C., Hibbert, S. A., Revote, J., Li, F., Griffiths, C. E. M., Watson, R. E. B., Song, J., Bell, M., & Sherratt, M. J. (2021). Predicting Proteolysis in Complex Proteomes Using Deep Learning. International Journal of Molecular Sciences, 22(6), 3071. https://doi.org/10.3390/ijms22063071