Prediction of plasma protein binding rate based on machine learning

FU Mingyu; ZHU Yiyang; WU Chunyong; HOU Fengzhen; GUAN Yuan

doi:10.11665/j.issn.1000-5048.20210607

Journal of China Pharmaceutical University > 2021 > 52(6): 699-706. > DOI: 10.11665/j.issn.1000-5048.20210607

FU Mingyu, ZHU Yiyang, WU Chunyong, HOU Fengzhen, GUAN Yuan. Prediction of plasma protein binding rate based on machine learning[J]. Journal of China Pharmaceutical University, 2021, 52(6): 699-706. DOI: 10.11665/j.issn.1000-5048.20210607

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Prediction of plasma protein binding rate based on machine learning

1.
School of Science, China Pharmaceutical University, Nanjing 211198
2.
Department of Pharmaceutical Analysis, China Pharmaceutical University, Nanjing 211198, China

Funds: This study was supported by the National Natural Science Foundation of China (No.82074128), and the Program for Innovation Team of the "Double-First Class" Disciplines (No.CPU2018GY30)

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Received Date: March 03, 2021
Revised Date: November 08, 2021

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Abstract

Abstract

Predicting the protein binding rate of drugs in plasma is helpful to us in understanding the pharmacokinetic characteristics of drugs, with much value of reference for early research on drug discovery. In this study, plasma protein binding rate information of 2 452 clinical drugs were collected.Two pieces of software, Molecular Operating Environment (MOE) and Mordred, were used to calculate molecular descriptors, which were used as input features of the model.Extreme gradient boosting (XGBoost) algorithm and random forest (RF) algorithm were then used to build a machine learning model.The results showed that, compared with MOE, the prediction performance of the constructed model was better using the molecular descriptor calculated by Mordred as the input of the model.The prediction performance results of the model constructed using the XGBoost algorithm and the RF algorithm were similar, and the R2 of the optimal model were both 0.715.According to the research results, it can be concluded that the drug plasma protein binding rate is closely related to some physical and chemical properties of the drug molecule, such as water solubility, octanol/water partition coefficient and conjugated double bonds.Using these parameters to predict the plasma protein binding rate of drugs has the advantages of convenience and efficiency, which can provide reference for related pharmacokinetic studies.
- plasma protein binding rate,
- machine learning,
- XGBoost algorithm,
- RF algorithm,
- drug discovery

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