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Terahertz spectroscopy and machine learning algorithm for non-destructive evaluation of protein conformation

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Abstract

Given the condition that protein conformation and activity are highly susceptible to environment factors such as temperature and pH, evaluation of protein conformation and activity is urgently needed in many fields. For example, most protein drugs need a stable and proper environment during production, storage and transportation, and it’s an enormous challenge to maintain protein activity throughout the whole process. Therefore, it’s necessary to ensure the safety and effectiveness of protein drugs by monitoring their activity before use. In our study, we presented an improved method for non-destructive evaluation of protein conformation and biological activity by terahertz spectroscopy combined with t-SNE-XGBoost. Firstly, bovine serum albumin (BSA) samples heated to different temperature were measured with THz-TDS. The obtained results indicated that native-conformation BSA will undergo transient states in the process of temperature induced denaturation. However, for any single given sample, it’s difficult to identify its conformation and activity directly by using the measured raw terahertz data. Therefore, we applied several different algorithms to the raw data for recognition of BSA samples with different conformation and activity induced by temperature. Finally, the models obtained by different algorithms were evaluated by calculating the root mean standard error of prediction (RMSEP) and the correlation coefficient of prediction (\(R_p\)). The THz-TDS plus t-SNE-XGBoost proved to be an effective non-destructive and label-free method for evaluation of protein conformation and activity. It can provide a new technique in many applications, such as pharmaceutical industry, clinical diagnosis and quality control.

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Acknowledgements

This work was funded by the National Natural Science Foundation of China (NSFC) (61302007), the China Postdoctoral Science Foundation (2017M610771) and the Innovative Talents Training Program of University of Science and Technology Beijing (F000005).

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Authors and Affiliations

  1. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100081, China

    Can Cao, Zhaohui Zhang, Xiaoyan Zhao & Tianyao Zhang

  2. Beijing Engineering Research Center of Industrial Spectrum Imaging, Beijing, 100081, China

    Can Cao, Zhaohui Zhang, Xiaoyan Zhao & Tianyao Zhang

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  1. Can Cao
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  2. Zhaohui Zhang
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  3. Xiaoyan Zhao
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  4. Tianyao Zhang
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Correspondence to Zhaohui Zhang.

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Cao, C., Zhang, Z., Zhao, X. et al. Terahertz spectroscopy and machine learning algorithm for non-destructive evaluation of protein conformation. Opt Quant Electron 52, 225 (2020). https://doi.org/10.1007/s11082-020-02345-1

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