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Protein–ligand binding with the coarse-grained Martini model

Author

Listed:
  • Paulo C. T. Souza

    (University of Groningen)

  • Sebastian Thallmair

    (University of Groningen)

  • Paolo Conflitti

    (Università della Svizzera italiana (USI))

  • Carlos Ramírez-Palacios

    (University of Groningen)

  • Riccardo Alessandri

    (University of Groningen)

  • Stefano Raniolo

    (Università della Svizzera italiana (USI))

  • Vittorio Limongelli

    (Università della Svizzera italiana (USI)
    University of Naples “Federico II”)

  • Siewert J. Marrink

    (University of Groningen)

Abstract

The detailed understanding of the binding of small molecules to proteins is the key for the development of novel drugs or to increase the acceptance of substrates by enzymes. Nowadays, computer-aided design of protein–ligand binding is an important tool to accomplish this task. Current approaches typically rely on high-throughput docking essays or computationally expensive atomistic molecular dynamics simulations. Here, we present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of protein–ligand interactions of small drug-like molecules. Remarkably, we achieve high accuracy without the need of any a priori knowledge of binding pockets or pathways. Our approach is applied to a range of systems from the well-characterized T4 lysozyme over members of the GPCR family and nuclear receptors to a variety of enzymes. The presented results open the way to high-throughput screening of ligand libraries or protein mutations using the coarse-grained Martini model.

Suggested Citation

  • Paulo C. T. Souza & Sebastian Thallmair & Paolo Conflitti & Carlos Ramírez-Palacios & Riccardo Alessandri & Stefano Raniolo & Vittorio Limongelli & Siewert J. Marrink, 2020. "Protein–ligand binding with the coarse-grained Martini model," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-17437-5
    DOI: 10.1038/s41467-020-17437-5
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