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Protein-ligand binding with the coarse-grained Martini model

Souza, P. C. T., Thallmair, S., Conflitti, P., Ramírez-Palacios, C., Alessandri, R., Raniolo, S., Limongelli, V. & Marrink, S. J., 24-Jul-2020, In : Nature Communications. 11, 1, 11 p., 3714.

Research output: Contribution to journalArticleAcademicpeer-review

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. Computer-aided design of protein-ligand binding is important for the development of novel drugs. Here authors present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of protein-ligand binding interactions of small drug-like molecules.

Original languageEnglish
Article number3714
Number of pages11
JournalNature Communications
Volume11
Issue number1
Publication statusPublished - 24-Jul-2020

    Keywords

  • MOLECULAR-DYNAMICS SIMULATIONS, ADENOSINE A(2A) RECEPTOR, COMPUTATIONAL DESIGN, T4 LYSOZYME, CRYSTAL-STRUCTURE, NONPOLAR CAVITY, DRUG DISCOVERY, FREE-ENERGIES, FXR, MECHANISM

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