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An insight into paracetamol and its metabolites using molecular docking and molecular dynamics simulation

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Abstract

Paracetamol is a relatively safe analgesia/antipyretic drug without the risks of addiction, dependence, tolerance, and withdrawal when used alone. However, when administrated in an opioid/paracetamol combination product, which often contains a large quantity of paracetamol, it can be potentially dangerous due to the risk of hepatotoxicity. Paracetamol is known to be metabolized into N-(4-hydroxyphenyl)-arachidonamide (AM404) via fatty acid amide hydrolase (FAAH) and into N-acetyl-p-benzoquinone imine (NAPQI) via cytochrome P450 (CYP) enzymes. However, the underlying mechanism of paracetamol is still unclear. In addition, paracetamol has the potential to interact with other drugs that are also involved with CYP family enzymes (inducer/inhibitor/substrate), an example being illicit drugs. In our present work, we looked into the relationship between paracetamol and its metabolites (AM404 and NAPQI) using molecular docking and molecular dynamics (MD) simulations. We first carried out a series of molecular docking studies between paracetamol/AM404/NAQPI and their reported targets, including CYP 2E1, FAAH, TRPA1, CB1, and TRPV1. Subsequently, we performed MD simulations and energy decomposition for CB1-AM404, TRPV1-AM404, and TRPV1-NAPQI for further investigation of the dynamics interactions. Finally, we summarized and discussed the reported drug–drug interactions between paracetamol and central nervous system drugs, especially illicit drugs. Overall, we are able to provide new insights into the structural and functional roles of paracetamol and its metabolites that can inform the potential prevention and treatment of paracetamol overdose.

Paracetamol and its metabolites

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Acknowledgments

The authors would like to acknowledge funding support to the X.-Q. Xie laboratory from the NIH NIDA (P30 DA035778A1), the National Institutes of Health (NIH) (R01 DA025612), and the Department of Defense (W81XWH-16-1-0490), funding support to the J.M. Wang laboratory from the NIH of the United States (R01-GM079383, R21-GM097617), and funding to Y.Q. Wang from the National Natural Science Foundation of China (31400667), Chongqing Municipal Education Commission Science and Technology Research Project (KJ1500902, KJ1600908) and Chongqing Research Program of Basic Research and Frontier Technology (cstc2014jcyjA10044, cstc2018jcyjAX0683). Computational support from the Center for Research Computing of University of Pittsburgh, and the Extreme Science and Engineering Discovery Environment (CHE090098), are acknowledged.

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  1. Yuanqiang Wang, Weiwei Lin and Nan Wu contributed equally to this work.

Authors and Affiliations

  1. Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, 15261, USA

    Yuanqiang Wang, Weiwei Lin, Nan Wu, Xibing He, Junmei Wang, Zhiwei Feng & Xiang-Qun Xie

  2. National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, PA, 15261, USA

    Yuanqiang Wang, Weiwei Lin, Nan Wu, Xibing He, Junmei Wang, Zhiwei Feng & Xiang-Qun Xie

  3. Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, 15261, USA

    Yuanqiang Wang, Weiwei Lin, Nan Wu, Xibing He, Junmei Wang, Zhiwei Feng & Xiang-Qun Xie

  4. Departments of Computational Biology and Structural Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15261, USA

    Yuanqiang Wang, Weiwei Lin, Nan Wu, Xibing He, Junmei Wang, Zhiwei Feng & Xiang-Qun Xie

  5. School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China

    Yuanqiang Wang

  6. Chongqing Key Laboratory of Medicinal Chemistry and Molecular Pharmacology, Chongqing, 400054, China

    Yuanqiang Wang

  7. Chongqing Key Laboratory of Target Based Drug Screening and Effect Evaluation, Chongqing, 400054, China

    Yuanqiang Wang

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  1. Yuanqiang Wang
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  2. Weiwei Lin
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Contributions

X.-Q. X. and Z.F. designed the research. Y.W., W.L. and N.W. performed the research, carried out the analysis and wrote the manuscript. X.H. and J.W. performed MD simulation and carried out the analysis.

Corresponding authors

Correspondence to Zhiwei Feng or Xiang-Qun Xie.

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Wang, Y., Lin, W., Wu, N. et al. An insight into paracetamol and its metabolites using molecular docking and molecular dynamics simulation. J Mol Model 24, 243 (2018). https://doi.org/10.1007/s00894-018-3790-9

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