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 wellcharacterized 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.

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The crystal structure of P2Y receptor (P2YR), a class A GPCR, revealed a special extra-helical site for its antagonist, BPTU, which locates in-between the membrane and the protein. However, due to the limitation of crystallization experiments, the membrane was mimicked by use of detergents, and the information related to the binding of BPTU to the receptor in the membrane environment is rather limited. In the present work, we conducted a total of ∼7.5 μs all-atom simulations in explicit solvent using conventional molecular dynamics and multiple enhanced sampling methods, with models of BPTU and a POPC bilayer, both in the absence and presence of P2YR. Our simulations revealed that BPTU prefers partitioning into the interface of polar/lipophilic region of the lipid bilayer before associating with the receptor. Then, it interacts with the second extracellular loop of the receptor and reaches the binding site through the lipid-receptor interface. In addition, by use of funnel-metadynamics simulations which efficiently enhance the sampling of bound and unbound states, we provide a statistically accurate description of the underlying binding free energy landscape. The calculated absolute ligand-receptor binding affinity is in excellent agreement with the experimental data (Δ G = -11.5 kcal mol, Δ G= -11.7 kcal mol). Our study broadens the view of the current experimental/theoretical models and our understanding of the protein-ligand recognition mechanism in the lipid environment. The strategy used in this work is potentially applicable to investigate ligands association/dissociation with other membrane-embedded sites, allowing identification of compounds targeting membrane receptors of pharmacological interest.

The molecular chaperone HSP90 oversees the functional activation of a large number of client proteins. Because of its role in multiple pathways linked to cancer and neurodegeneration, drug discovery targeting HSP90 has been actively pursued. Yet, a number of inhibitors failed to meet expectations due to induced toxicity problems. In this context, allosteric perturbation has emerged as an alternative strategy for the pharmacological modulation of HSP90 functions. Specifically, novel allosteric stimulators showed the interesting capability of accelerating HSP90 closure dynamics and ATPase activities while inducing tumor cell death. Here, we gain atomistic insight into the mechanisms of allosteric ligand recognition and their consequences on the functional dynamics of HSP90, starting from the fully unbound state. We integrate advanced computational sampling methods based on FunnelMetadynamics, with the analysis of internal dynamics of the structural ensembles visited during the simulations. We observe several binding/unbinding events, and from these, we derive an accurate estimation of the absolute binding free energy. Importantly, we show that different binding poses induce different dynamics states. Our work for the first time explicitly correlates HSP90 responses to binding/unbinding of an allosteric ligand to the modulation of functionally oriented protein motions.

Interactions between peptides are relevant from a biomedical point of view, in particular for the role played by their aggregates in different important pathologies, and also because peptide aggregates represent promising scaffolds for innovative materials. In the present article, the aggregation properties of the homo-peptides formed by α-aminoisobutyric acid (U) residues are discussed. The peptides investigated have chain lengths between six and 15 residues and comprise benzyl and naphthyl groups at the N- and C-termini, respectively. Spectroscopic experiments and molecular dynamics simulations show that the shortest homo-peptide, constituted by six U, does not exhibit any tendency to aggregate under the conditions examined. On the other hand, the homologous peptide with 15 U forms very stable and compact aggregates in 70/30(v/v) methanol/water solution. Atomic force microscopy images indicate that these aggregates promote formation of long fibrils once they are deposited on a mica surface. The aggregation phenomenon is mainly due to hydrophobic interactions occurring between very stable helical structures, and the aromatic groups in the peptides seem to play a minor role.