The free energy landscape of GABA binding to a pentameric ligand-gated ion channel and its disruption by mutations

Pentameric ligand-gated ion channels (pLGICs) of the Cys-loop superfamily are important neuroreceptors that mediate fast synaptic transmission. They are activated by the binding of a neurotransmitter, but the details of this process are still not fully understood. As a prototypical pLGIC, here we choose the insect resistance to dieldrin (RDL) receptor, involved in the resistance to insecticides, and investigate the binding of the neurotransmitter GABA to its extracellular domain at the atomistic level. We achieve this by means of $\mu$-sec funnel-metadynamics simulations, which efficiently enhance the sampling of bound and unbound states by using a funnel-shaped restraining potential to limit the exploration in the solvent. We reveal the sequence of events in the binding process, from the capture of GABA from the solvent to its pinning between the charged residues Arg111 and Glu204 in the binding pocket. We characterize the associated free energy landscapes in the wild-type RDL receptor and in two mutant forms, where the key residues Arg111 and Glu204 are mutated to Ala. Experimentally these mutations produce non-functional channels, which is reflected in the reduced ligand binding affinities, due to the loss of essential interactions. We also analyze the dynamical behaviour of the crucial loop C, whose opening allows the access of GABA to the binding site, while its closure locks the ligand into the protein. The RDL receptor shares structural and functional features with other pLGICs, hence our work outlines a valuable protocol to study the binding of ligands to pLGICs beyond conventional docking and molecular dynamics techniques.Comment: accepted (May 2016); 27 pages, 6 figures, Table of contents graphic, Journal of Chemical Theory and Computation (2016

Funnel metadynamics as accurate binding free-energy method

A detailed description of the events ruling ligand/protein interac- tion and an accurate estimation of the drug affinity to its target is of great help in speeding drug discovery strategies. We have de- veloped a metadynamics-based approach, named funnel metady- namics, that allows the ligand to enhance the sampling of the target binding sites and its solvated states. This method leads to an effi- cient characterization of the binding free-energy surface and an accurate calculation of the absolute protein–ligand binding free energy. We illustrate our protocol in two systems, benzamidine/ trypsin and SC-558/cyclooxygenase 2. In both cases, the X-ray con- formation has been found as the lowest free-energy pose, and the computed protein–ligand binding free energy in good agreement with experiments. Furthermore, funnel metadynamics unveils im- portant information about the binding process, such as the presence of alternative binding modes and the role of waters. The results achieved at an affordable computational cost make funnel meta- dynamics a valuable method for drug discovery and for dealing with a variety of problems in chemistry, physics, and material science

DDT - Drug Discovery Tool: a fast and intuitive graphics user interface for Docking and Molecular Dynamics analysis.

Abstract Motivation The ligand/protein binding interaction is typically investigated by docking and molecular dynamics (MD) simulations. In particular, docking-based virtual screening (VS) is used to select the best ligands from database of thousands of compounds, while MD calculations assess the energy stability of the ligand/protein binding complexes. Considering the broad use of these techniques, it is of great demand to have one single software that allows a combined and fast analysis of VS and MD results. With this in mind, we have developed the Drug Discovery Tool (DDT) that is an intuitive graphics user interface able to provide structural data and physico-chemical information on the ligand/protein interaction. Results DDT is designed as a plugin for the Visual Molecular Dynamics (VMD) software and is able to manage a large number of ligand/protein complexes obtained from AutoDock4 (AD4) docking calculations and MD simulations. DDT delivers four main outcomes: i) ligands ranking based on an energy score; ii) ligand ranking based on a ligands' conformation cluster analysis; iii) identification of the aminoacids forming the most occurrent interactions with the ligands; iv) plot of the ligands' center-of-mass coordinates in the Cartesian space. The flexibility of the software allows saving the best ligand/protein complexes using a number of user-defined options. Availability and implementation DDT_site_1 (alternative DDT_site_2); the DDT tutorial movie is available here. Supplementary information Supplementary data are available at Bioinformatics online

Mechanistic insight into ligand binding to G-quadruplex DNA

Specific guanine-rich regions in human genome can form higher-order DNA structures called G-quadruplexes, which regulate many relevant biological processes. For instance, the formation of G-quadruplex at telomeres can alter cellular functions, inducing apoptosis. Thus, developing small molecules that are able to bind and stabilize the telomeric G-quadruplexes represents an attractive strategy for antitumor therapy. An example is 3-(benzo[d]thiazol-2-yl)-7-hydroxy-8-((4-(2-hydroxyethyl)piperazin-1-yl)methyl)-2H-chromen-2-one (compound 1), recently identified as potent ligand of the G-quadruplex [d(TGGGGT)]4 with promising in vitro antitumor activity. The experimental observations are suggestive of a complex binding mechanism that, despite efforts, has defied full characterization. Here, we provide through metadynamics simulations a comprehensive understanding of the binding mechanism of 1 to the G-quadruplex [d(TGGGGT)]4. In our calculations, the ligand explores all the available binding sites on the DNA structure and the free-energy landscape of the whole binding process is computed. We have thus disclosed a peculiar hopping binding mechanism whereas 1 is able to bind both to the groove and to the 3' end of the G-quadruplex. Our results fully explain the available experimental data, rendering our approach of great value for further ligand/DNA studie

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

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

G-triplex structure and formation propensity

The occurrence of a G-triplex folding intermediate of thrombin binding aptamer (TBA) has been recently predicted by metadynamics calculations, and experimentally supported by Nuclear Magnetic Resonance (NMR), Circular Dichroism (CD) and Differential Scanning Calorimetry (DSC) data collected on a 3′ end TBA-truncated 11-mer oligonucleotide (11-mer-3′-t-TBA). Here we present the solution structure of 11-mer-3′-t-TBA in the presence of potassium ions. This structure is the first experimental example of a G-triplex folding, where a network of Hoogsteen-like hydrogen bonds stabilizes six guanines to form two G:G:G triad planes. The G-triplex folding of 11-mer-3′-t-TBA is stabilized by the potassium ion and destabilized by increasing the temperature. The superimposition of the experimental structure with that predicted by metadynamics shows a great similarity, with only significant differences involving two loops. These new structural data show that 11-mer-3′-t-TBA assumes a G-triplex DNA conformation as its stable form, reinforcing the idea that G-triplex folding intermediates may occur in vivo in human guanine-rich sequences. NMR and CD screening of eight different constructs obtained by removing from one to four bases at either the 3′ and the 5′ ends show that only the 11-mer-3′-t-TBA yields a relatively stable G-triple

Protein-ligand binding with the coarse-grained Martini model

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

Discovery of Bile Acid Derivatives as Potent ACE2 Activators by Virtual Screening and Essential Dynamics

The angiotensin-converting enzyme II (ACE2) is a key molecular player in the regulation of vessel contraction, inflammation, and reduction of oxidative stress. In addition, ACE2 has assumed a prominent role in the fight against the COVID-19 pandemic-causing virus SARS-CoV-2, as it is the very first receptor in the host of the viral spike protein. The binding of the spike protein to ACE2 triggers a cascade of events that eventually leads the virus to enter the host cell and initiate its life cycle. At the same time, SARS-CoV-2 infection downregulates ACE2 expression especially in the lung, altering the biochemical signals regulated by the enzyme and contributing to the poor clinical prognosis characterizing the late stage of the COVID-19 disease. Despite its important biological role, a very limited number of ACE2 activators are known. Here, using a combined in silico and experimental approach, we show that ursodeoxycholic acid (UDCA) derivatives work as ACE2 activators. In detail, we have identified two potent ACE2 ligands, BAR107 and BAR708, through a docking virtual screening campaign and elucidated their mechanism of action from essential dynamics of the enzyme observed during microsecond molecular dynamics calculations. The in silico results were confirmed by in vitro pharmacological assays with the newly identified compounds showing ACE2 activity comparable to that of DIZE, the most potent ACE2 activator known so far. Our work provides structural insight into ACE2/ligand-binding interaction useful for the design of compounds with therapeutic potential against SARS-CoV-2 infection, inflammation, and other ACE2-related diseases

Discovery of a Potent and Orally Active Dual GPBAR1/CysLT1R Modulator for the Treatment of Metabolic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) are two highly prevalent human diseases caused by excessive fat deposition in the liver. Although multiple approaches have been suggested, NAFLD/NASH remains an unmet clinical need. Here, we report the discovery of a novel class of hybrid molecules designed to function as cysteinyl leukotriene receptor 1 (CysLT1R) antagonists and G protein bile acid receptor 1 (GPBAR1/TGR5) agonists for the treatment of NAFLD/NASH. The most potent of these compounds generated by harnessing the scaffold of the previously described CystLT1R antagonists showed efficacy in reversing liver histopathology features in a preclinical model of NASH, reshaping the liver transcriptome and the lipid and energy metabolism in the liver and adipose tissues. In summary, the present study described a novel orally active dual CysLT1R antagonist/GPBAR1 agonist that effectively protects against the development of NAFLD/NASH, showing promise for further development

Phosphorylation of FAM134C by CK2 controls starvation-induced ER-phagy.

Selective degradation of the endoplasmic reticulum (ER) via autophagy (ER-phagy) is initiated by ER-phagy receptors, which facilitate the incorporation of ER fragments into autophagosomes. FAM134 reticulon family proteins (FAM134A, FAM134B, and FAM134C) are ER-phagy receptors with structural similarities and nonredundant functions. Whether they respond differentially to the stimulation of ER-phagy is unknown. Here, we describe an activation mechanism unique to FAM134C during starvation. In fed conditions, FAM134C is phosphorylated by casein kinase 2 (CK2) at critical residues flanking the LIR domain. Phosphorylation of these residues negatively affects binding affinity to the autophagy proteins LC3. During starvation, mTORC1 inhibition limits FAM134C phosphorylation by CK2, hence promoting receptor activation and ER-phagy. Using a novel tool to study ER-phagy in vivo and FAM134C knockout mice, we demonstrated the physiological relevance of FAM134C phosphorylation during starvation-induced ER-phagy in liver lipid metabolism. These data provide a mechanistic insight into ER-phagy regulation and an example of autophagy selectivity during starvation.We thank G. Diez Roux and P. Ashley-Norman for critical reading of the manuscript. We thank the microscopy, MS, advanced histopathology, and FACS facilities at TIGEM Institute. We thank E. Nusco for helping us with AAV injections. Funding: This work was supported by European Research Council (ERC) (714551), Telethon intramural grants, and Associazione Italiana per la Ricerca sul Cancro (AIRC) (IG 2015 Id 17717) (to C.S.) and Telethon Foundation (TMPGCBX16TT), AFM Telethon (Trampoline Grant), and AIRC (MFAG-2020-24856) (to P.G.). G.D.L. is a recipient of AIRC fellowship “Francesco Alicino” (25407). V.L. acknowledges funding from the ERC (101001784), the Italian MIUR-PRIN 2017 (2017FJZZRC), and the Swiss National Supercomputing Center (CSCS) (project ID u8). The work of A.S. was supported by the German Research Foundation DFG (SFB1177/2 and WO210/20-2) and the Dr. Rolf M. Schwiete Stiftung (13/2017). A.E. is supported by the RETOS projects Programme of Spanish Ministry of Science, Innovation and Universities, Spanish State Research Agency (grants SAF2015-67538-R and PID2019-104012RB-I00), and the ERC (638891). A.B.P.-G. is a recipient of Ph.D. fellowship from MICIU/AEI (BES-2017-081381). A.R. is a recipient of Umberto Veronesi Foundation postdoctoral fellowship. Author contributions: G.D.L. and F.I. performed most of the experiments. F.I. and A.B.P.-G. performed in vivo experiments. M.M. performed mutagenesis experiments. S.A. and V.L. performed LC3-FAM134C binding analysis. C.P.Q.M. performed in vitro phosphorylation assays. L.C. analyzed CK2 substrate phosphorylation. F.S., A.P., C.C., and A.S. analyzed proteomic data. G.N. provided critical suggestions. A.R. performed proteomic experiments. A.E. supervised in vivo experiments. M.R., L.A.P., and O.M. supervised CK2 experiments. C.S. designed the study. P.G. and C.S. conceived and supervised the experiments. C.S., P.G., V.L., and M.R. wrote the paper. G.D.L. and F.I. prepared the figures. All the authors read the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.S