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Article

Revealing the Mutation Patterns of Drug-Resistant Reverse Transcriptase Variants of Human Immunodeficiency Virus through Proteochemometric Modeling

by
Jingxuan Qiu
1,
Xinxin Tian
1,
Jiangru Liu
1,
Yulong Qin
1,
Junjie Zhu
1,
Dongpo Xu
1 and
Tianyi Qiu
2,*
1
School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
2
Shanghai Public Health Clinical Center, Fudan University, Shanghai 200032, China
*
Author to whom correspondence should be addressed.
Biomolecules 2021, 11(9), 1302; https://doi.org/10.3390/biom11091302
Submission received: 15 July 2021 / Revised: 31 August 2021 / Accepted: 1 September 2021 / Published: 2 September 2021
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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Abstract

Drug-resistant cases of human immunodeficiency virus (HIV) nucleoside reverse transcriptase inhibitors (NRTI) are constantly accumulating due to the frequent mutations of the reverse transcriptase (RT). Predicting the potential drug resistance of HIV-1 NRTIs could provide instructions for the proper clinical use of available drugs. In this study, a novel proteochemometric (PCM) model was constructed to predict the drug resistance between six NRTIs against different variants of RT. Forty-seven dominant mutation sites were screened using the whole protein of HIV-1 RT. Thereafter, the physicochemical properties of the dominant mutation sites can be derived to generate the protein descriptors of RT. Furthermore, by combining the molecular descriptors of NRTIs, PCM modeling can be constructed to predict the inhibition ability between RT variants and NRTIs. The results indicated that our PCM model could achieve a mean AUC value of 0.946 and a mean accuracy of 0.873 on the external validation set. Finally, based on PCM modeling, the importance of features was calculated to reveal the dominant amino acid distribution and mutation patterns on RT, to reflect the characteristics of drug-resistant sequences.
Keywords: HIV; reverse transcriptase; drug resistance; computational model HIV; reverse transcriptase; drug resistance; computational model

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MDPI and ACS Style

Qiu, J.; Tian, X.; Liu, J.; Qin, Y.; Zhu, J.; Xu, D.; Qiu, T. Revealing the Mutation Patterns of Drug-Resistant Reverse Transcriptase Variants of Human Immunodeficiency Virus through Proteochemometric Modeling. Biomolecules 2021, 11, 1302. https://doi.org/10.3390/biom11091302

AMA Style

Qiu J, Tian X, Liu J, Qin Y, Zhu J, Xu D, Qiu T. Revealing the Mutation Patterns of Drug-Resistant Reverse Transcriptase Variants of Human Immunodeficiency Virus through Proteochemometric Modeling. Biomolecules. 2021; 11(9):1302. https://doi.org/10.3390/biom11091302

Chicago/Turabian Style

Qiu, Jingxuan, Xinxin Tian, Jiangru Liu, Yulong Qin, Junjie Zhu, Dongpo Xu, and Tianyi Qiu. 2021. "Revealing the Mutation Patterns of Drug-Resistant Reverse Transcriptase Variants of Human Immunodeficiency Virus through Proteochemometric Modeling" Biomolecules 11, no. 9: 1302. https://doi.org/10.3390/biom11091302

APA Style

Qiu, J., Tian, X., Liu, J., Qin, Y., Zhu, J., Xu, D., & Qiu, T. (2021). Revealing the Mutation Patterns of Drug-Resistant Reverse Transcriptase Variants of Human Immunodeficiency Virus through Proteochemometric Modeling. Biomolecules, 11(9), 1302. https://doi.org/10.3390/biom11091302

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