Protein–ligand binding with the coarse-grained Martini model

Souza, Paulo C. T.; Thallmair, Sebastian; Conflitti, Paolo; Ramírez-Palacios, Carlos; Alessandri, Riccardo; Raniolo, Stefano; Limongelli, Vittorio; Marrink, Siewert J.

doi:10.1038/s41467-020-17437-5

Cited by 173 publications

(205 citation statements)

References 101 publications

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“…However, any empirical and coarse-grained force-field does have limitations 63 33 . With a very recent re-parameterization, MARTINI has been shown to effectively capture protein-ligand binding specificity at accurate energy scales 64 . The major re-parameterization changes were in improved packing of the CG beads, and re-parameterized bond distances to improve volume and shape.…”

Section: Discussionmentioning

confidence: 99%

Thermodynamics and free energy landscape of BAR-domain dimerization from molecular simulations

Jhaveri

Maisuria

Varga

et al. 2020

Preprint

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Nearly all proteins interact specifically with other proteins, often forming reversible bound structures whose stability is critical to function. Proteins with BAR domains function to bind to, bend, and remodel biological membranes, where the dimerization of BAR domains is a key step in this function. Here we characterize the binding thermodynamics of homodimerization between the LSP1 BAR domain proteins in solution, using Molecular Dynamics (MD) simulations. By combining the MARTINI coarse-grained protein models with enhanced sampling through metadynamics, we construct a two-dimensional free energy surface quantifying the bound versus unbound ensembles as a function of two distance variables. Our simulations portray a heterogeneous and extraordinarily stable bound ensemble for these modeled LSP1 proteins. The proper crystal structure dimer has a large hydrophobic interface that is part of a stable minima on the free energy surface, which is enthalpically the minima of all bound structures. However, we also find several other stable nonspecific dimers with comparable free energies to the specific dimer. Through structure-based clustering of these bound structures, we find that some of these ‘nonspecific’ contacts involve extended tail regions that help stabilize the higher-order oligomers formed by BAR-domains, contacts that are separated from the homodimer interface. We find that the known membrane-binding residues of the LSP1 proteins rarely participate in any of the bound interfaces, but that both patches of residues are aligned to interact with the membrane in the specific dimer. Hence, we would expect a strong selection of the specific dimer in binding to the membrane. The effect of a 100mM NaCl buffer reduces the relative stability of nonspecific dimers compared to the specific dimer, indicating that it would help prevent aggregation of the proteins. With these results, we provide the first free energy characterization of interaction pathways in this important class of membrane sculpting domains, revealing a variety of interfacial contacts outside of the specific dimer that may help stabilize its oligomeric assemblies.

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Section: Discussionmentioning

confidence: 99%

Thermodynamics and free energy landscape of BAR-domain dimerization from molecular simulations

Jhaveri

Maisuria

Varga

et al. 2020

Preprint

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“…The use of Martini CG models will enable a new approach: dynamic docking with no a priori knowledge of the binding pocket in the target structure. The concept here is to sample protein–ligand interactions with CG MD simulations, which is around 300 to 1,000 times faster than atomistic MD ( Souza et al, 2020 ). A practical example of such speed up can be given for propranolol binding to β2 adrenergic receptor, which has been simulated in atomistic ( Dror et al, 2011 ) and coarse-grained ( Souza et al, 2020 ) resolution.…”

Section: Virtual Screening: Martini Dynamic Dockingmentioning

confidence: 99%

Perspectives on High-Throughput Ligand/Protein Docking With Martini MD Simulations

Souza

Limongelli

et al. 2021

Front. Mol. Biosci.

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Molecular docking is central to rational drug design. Current docking techniques suffer, however, from limitations in protein flexibility and solvation models and by the use of simplified scoring functions. All-atom molecular dynamics simulations, on the other hand, feature a realistic representation of protein flexibility and solvent, but require knowledge of the binding site. Recently we showed that coarse-grained molecular dynamics simulations, based on the most recent version of the Martini force field, can be used to predict protein/ligand binding sites and pathways, without requiring any a priori information, and offer a level of accuracy approaching all-atom simulations. Given the excellent computational efficiency of Martini, this opens the way to high-throughput drug screening based on dynamic docking pipelines. In this opinion article, we sketch the roadmap to achieve this goal.

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“…Hence dynamical docking considers flexibility of drug-protein binding and conformational changes, solvation of drug-protein complex and temperature [38,39]. Unbiased millisecond-long can predict spontaneous drug-protein entire binding [40]. In addition, recent developments in dynamical docking such as enhanced sampling for dynamical docking, path-based and alchemical transformations have greatly impacted drug discovery [38].…”

Section: Molecular Dynamics Simulationmentioning

confidence: 99%

Identification of Potential SARS-CoV-2 Main Protease and Spike Protein Inhibitors from the Genus Aloe: An In Silico Study for Drug Development

et al. 2021

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Severe acute respiratory syndrome coronavirus (SARS-CoV-2) disease is a global rapidly spreading virus showing very high rates of complications and mortality. Till now, there is no effective specific treatment for the disease. Aloe is a rich source of isolated phytoconstituents that have an enormous range of biological activities. Since there are no available experimental techniques to examine these compounds for antiviral activity against SARS-CoV-2, we employed an in silico approach involving molecular docking, dynamics simulation, and binding free energy calculation using SARS-CoV-2 essential proteins as main protease and spike protein to identify lead compounds from Aloe that may help in novel drug discovery. Results retrieved from docking and molecular dynamics simulation suggested a number of promising inhibitors from Aloe. Root mean square deviation (RMSD) and root mean square fluctuation (RMSF) calculations indicated that compounds 132, 134, and 159 were the best scoring compounds against main protease, while compounds 115, 120, and 131 were the best scoring ones against spike glycoprotein. Compounds 120 and 131 were able to achieve significant stability and binding free energies during molecular dynamics simulation. In addition, the highest scoring compounds were investigated for their pharmacokinetic properties and drug-likeness. The Aloe compounds are promising active phytoconstituents for drug development for SARS-CoV-2.

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Protein–ligand binding with the coarse-grained Martini model

Cited by 173 publications

References 101 publications

Thermodynamics and free energy landscape of BAR-domain dimerization from molecular simulations

Thermodynamics and free energy landscape of BAR-domain dimerization from molecular simulations

Perspectives on High-Throughput Ligand/Protein Docking With Martini MD Simulations

Identification of Potential SARS-CoV-2 Main Protease and Spike Protein Inhibitors from the Genus Aloe: An In Silico Study for Drug Development

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