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Encoding mu-opioid receptor biased agonism with interaction fingerprints

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Abstract

Opioids are potent painkillers, however, their therapeutic use requires close medical monitoring to diminish the risk of severe adverse effects. The G-protein biased agonists of the μ-opioid receptor (MOR) have shown safer therapeutic profiles than non-biased ligands. In this work, we performed extensive all-atom molecular dynamics simulations of two markedly biased ligands and a balanced reference molecule. From those simulations, we identified a protein–ligand interaction fingerprint that characterizes biased ligands. Then, we built and virtually screened a database containing 68,740 ligands with proven or potential GPCR agonistic activity. Exemplary molecules that fulfill the interacting pattern for biased agonism are showcased, illustrating the usefulness of this work for the search of biased MOR ligands and how this contributes to the understanding of MOR biased signaling.

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Acknowledgements

This work was supported by Instituto de Química. The computations were supported by the Dirección General de Cómputo y de Tecnologías de Información y Comunicación (DGTIC)-UNAM, providing Miztli computer resources under grant LANCAD-UNAM-DGTIC-367. RBH-A acknowledges CONACyT (957374) for scholarship, FC-V acknowledges a scholarship from QUIBIC Group, UNAM. KM-M thanks DGAPA-PASPA and AN thanks NIDA (Grant: R33DA044425) for financial support. Authors thank Dr. Alan Grossfield and Dr. Rogelio Rodríguez-Sotres for insightful discussions. To the developers of ChemAxon, DataWarrior, Amber MD package, VMD/NAMD for kindly providing academic licenses of their software.

Funding

DGAPA, UNAM, Programa de Apoyos para la Superación del Personal Académico (PASPA).

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Authors and Affiliations

  1. Instituto de Química, Universidad Nacional Autónoma de México, Mexico City, Mexico

    R. Bruno Hernández-Alvarado, Abraham Madariaga-Mazón, Fernando Cosme-Vela & Karina Martinez-Mayorga

  2. Facultad de Química, Universidad Nacional Autónoma de México, Mexico City, Mexico

    Andrés F. Marmolejo-Valencia

  3. Center for Translational Science, Florida International University, Port St. Lucie, FL, USA

    Adel Nefzi

  4. Torrey Pines Institute for Molecular Studies, Port St. Lucie, FL, USA

    Adel Nefzi

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  1. R. Bruno Hernández-Alvarado
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  2. Abraham Madariaga-Mazón
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  3. Fernando Cosme-Vela
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  6. Karina Martinez-Mayorga
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Correspondence to Abraham Madariaga-Mazón or Karina Martinez-Mayorga.

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Hernández-Alvarado, R.B., Madariaga-Mazón, A., Cosme-Vela, F. et al. Encoding mu-opioid receptor biased agonism with interaction fingerprints. J Comput Aided Mol Des 35, 1081–1093 (2021). https://doi.org/10.1007/s10822-021-00422-5

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