Expanding the Library of 1,2,4-Oxadiazole Derivatives: Discovery of New Farnesoid X Receptor (FXR) Antagonists/Pregnane X Receptor (PXR) Agonists.

Compounds featuring a 1,2,4-oxadiazole core have been recently identified as a new chemotype of farnesoid X receptor (FXR) antagonists. With the aim to expand this class of compounds and to understand the building blocks necessary to maintain the antagonistic activity, we describe herein the synthesis, the pharmacological evaluation, and the in vitro pharmacokinetic properties of a novel series of 1,2,4-oxadiazole derivatives decorated on the nitrogen of the piperidine ring with different N-alkyl and N-aryl side chains. In vitro pharmacological evaluation showed compounds 5 and 11 as the first examples of nonsteroidal dual FXR/Pregnane X receptor (PXR) modulators. In HepG2 cells, these compounds modulated PXR- and FXR-regulated genes, resulting in interesting leads in the treatment of inflammatory disorders. Moreover, molecular docking studies supported the experimental results, disclosing the ligand binding mode and allowing rationalization of the activities of compounds 5 and 11.

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.

DDT - Drug Discovery Tool: a fast and intuitive graphics user interface for docking and molecular dynamics analysis.

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.

Ligand binding to telomeric G-quadruplex DNA investigated by funnel-metadynamics simulations.

G-quadruplexes (G4s) are higher-order DNA structures typically present at promoter regions of genes and telomeres. Here, the G4 formation decreases the replicative DNA at each cell cycle, finally leading to apoptosis. The ability to control this mitotic clock, particularly in cancer cells, is fascinating and passes through a rational understanding of the ligand/G4 interaction. We demonstrate that an accurate description of the ligand/G4 binding mechanism is possible using an innovative free-energy method called funnel-metadynamics (FM), which we have recently developed to investigate ligand/protein interaction. Using FM simulations, we have elucidated the binding mechanism of the anticancer alkaloid berberine to the human telomeric G4 (d[AG3(T2AG3)3]), computing also the binding free-energy landscape. Two ligand binding modes have been identified as the lowest energy states. Furthermore, we have found prebinding sites, which are preparatory to reach the final binding mode. In our simulations, the ions and the water molecules have been explicitly represented and the energetic contribution of the solvent during ligand binding evaluated. Our theoretical results provide an accurate estimate of the absolute ligand/DNA binding free energy ([Formula: see text] = -10.3 ± 0.5 kcal/mol) that we validated through steady-state fluorescence binding assays. The good agreement between the theoretical and experimental value demonstrates that FM is a most powerful method to investigate ligand/DNA interaction and can be a useful tool for the rational design also of G4 ligands.

Structural Insight into the Binding Mode of FXR and GPBAR1 Modulators.

In this chapter we provide an exhaustive overview of the binding modes of bile acid (BA) and non-BA ligands to the nuclear farnesoid X receptor (FXR) and the G-protein bile acid receptor 1 (GPBAR1). These two receptors play a key role in many diseases related to lipid and glucose disorders, thus representing promising pharmacological targets. We pay particular attention to the chemical and structural features of the ligand-receptor interaction, providing guidelines to achieve ligands endowed with selective or dual activity towards the receptor and paving the way to future drug design studies.

Introduction of Nonacidic Side Chains on 6-Ethylcholane Scaffolds in the Identification of Potent Bile Acid Receptor Agonists with Improved Pharmacokinetic Properties.

As a cellular bile acid sensor, farnesoid X receptor (FXR) and the membrane G-coupled receptor (GPBAR1) participate in maintaining bile acid, lipid, and glucose homeostasis. To date, several selective and dual agonists have been developed as promising pharmacological approach to metabolic disorders, with most of them possessing an acidic conjugable function that might compromise their pharmacokinetic distribution. Here, guided by docking calculations, nonacidic 6-ethyl cholane derivatives have been prepared. In vitro pharmacological characterization resulted in the identification of bile acid receptor modulators with improved pharmacokinetic properties.

Disruption of TFGß-SMAD3 pathway by the nuclear receptor SHP mediates the antifibrotic activities of BAR704, a novel highly selective FXR ligand.

Liver fibrosis, a major health concern worldwide, results from abnormal collagen deposition by activated hepatic stellate cells (HSCs) in an injured liver. The farnesoid-x-receptor (FXR) is a bile acid sensor that counteracts HSCs transdifferentiation. While targeting FXR holds promise, 6-ethyl-CDCA known as obeticholic acid, the first in class of FXR ligands, causes side effects, partially because the lack of selectivity toward GPBAR1, a putative itching receptor. Here, we describe the 3-deoxy-6-ethyl derivative of CDCA, BAR704, as a highly selective steroidal FXR agonist. METHODS: Liver Fibrosis was induced in mice by carbon tetrachloride (CCl4). MAIN RESULTS: In transactivation assay BAR704 activated FXR with and EC50 of 967 nM while exerted no agonistic activity on other receptors including GPBAR1. In naïve mice, BAR704 modulated the expression of FXR target genes in the liver of wild type mice but not in FXR-/- mice. In cirrhotic mice, administration of BAR704, 15 mg/kg for 9 weeks, spared the liver biosynthetic activity (bilirubin and albumin plasma levels), reduced liver fibrosis score (Sirius red staining), expression of pro-fibrogenetic (Colα1α, TGFß and αSMA) and inflammatory genes (IL-1ß, TNFα) and portal pressure. From mechanistic stand point, we have found that exposure of LX2 cells, a human HSCs line, to BAR704 increased the transcription of the short heterodimer partner (SHP) and induced the binding of this nuclear receptor to SMAD3, thus abrogating the binding of phosho-SMAD3 to the TGFß promoter. CONCLUSIONS AND APPLICATIONS: BAR704 is a selective FXR agonist that reduces liver fibrosis by interfering with the TGFß-SMAD3 pathway in HSCs. Selective FXR agonists may represent an attractive strategy for the treatment of liver fibrosis.

Kinetics of protein-ligand unbinding: Predicting pathways, rates, and rate-limiting steps.

The ability to predict the mechanisms and the associated rate constants of protein-ligand unbinding is of great practical importance in drug design. In this work we demonstrate how a recently introduced metadynamics-based approach allows exploration of the unbinding pathways, estimation of the rates, and determination of the rate-limiting steps in the paradigmatic case of the trypsin-benzamidine system. Protein, ligand, and solvent are described with full atomic resolution. Using metadynamics, multiple unbinding trajectories that start with the ligand in the crystallographic binding pose and end with the ligand in the fully solvated state are generated. The unbinding rate k off is computed from the mean residence time of the ligand. Using our previously computed binding affinity we also obtain the binding rate k on. Both rates are in agreement with reported experimental values. We uncover the complex pathways of unbinding trajectories and describe the critical rate-limiting steps with unprecedented detail. Our findings illuminate the role played by the coupling between subtle protein backbone fluctuations and the solvation by water molecules that enter the binding pocket and assist in the breaking of the shielded hydrogen bonds. We expect our approach to be useful in calculating rates for general protein-ligand systems and a valid support for drug design.

Unbinding Kinetics of a p38 MAP Kinase Type II Inhibitor from Metadynamics Simulations.

Understanding the structural and energetic requisites of ligand binding toward its molecular target is of paramount relevance in drug design. In recent years, atomistic free energy calculations have proven to be a valid tool to complement experiments in characterizing the thermodynamic and kinetic properties of protein/ligand interaction. Here, we investigate, through a recently developed metadynamics-based protocol, the unbinding mechanism of an inhibitor of the pharmacologically relevant target p38 MAP kinase. We provide a thorough description of the ligand unbinding pathway identifying the most stable binding mode and other thermodynamically relevant poses. From our simulations, we estimated the unbinding rate as koff = 0.020 ± 0.011 s-1. This is in good agreement with the experimental value (koff = 0.14 s-1). Next, we developed a Markov state model that allowed identifying the rate-limiting step of the ligand unbinding process. Our calculations further show that the solvation of the ligand and that of the active site play crucial roles in the unbinding process. This study paves the way to investigations on the unbinding dynamics of more complex p38 inhibitors and other pharmacologically relevant inhibitors in general, demonstrating that metadynamics can be a powerful tool in designing new drugs with engineered binding/unbinding kinetics.

Conformational Changes in the Epidermal Growth Factor Receptor: Role of the Transmembrane Domain Investigated by Coarse-Grained MetaDynamics Free Energy Calculations.

The epidermal growth factor receptor (EGFR) is a dimeric membrane protein that regulates key aspects of cellular function. Activation of the EGFR is linked to changes in the conformation of the transmembrane (TM) domain, brought about by changes in interactions of the TM helices of the membrane lipid bilayer. Using an advanced computational approach that combines Coarse-Grained molecular dynamics and well-tempered MetaDynamics (CG-MetaD), we characterize the large-scale motions of the TM helices, simulating multiple association and dissociation events between the helices in membrane, thus leading to a free energy landscape of the dimerization process. The lowest energy state of the TM domain is a right-handed dimer structure in which the TM helices interact through the N-terminal small-X3-small sequence motif. In addition to this state, which is thought to correspond to the active form of the receptor, we have identified further low-energy states that allow us to integrate with a high level of detail a range of previous experimental observations. These conformations may lead to the active state via two possible activation pathways, which involve pivoting and rotational motions of the helices, respectively. Molecular dynamics also reveals correlation between the conformational changes of the TM domains and of the intracellular juxtamembrane domains, paving the way for a comprehensive understanding of EGFR signaling at the cell membrane.

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 studies.

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-triplex.

Funnel metadynamics as accurate binding free-energy method.

A detailed description of the events ruling ligand/protein interaction and an accurate estimation of the drug affinity to its target is of great help in speeding drug discovery strategies. We have developed a metadynamics-based approach, named funnel metadynamics, that allows the ligand to enhance the sampling of the target binding sites and its solvated states. This method leads to an efficient 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 conformation 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 important 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 metadynamics a valuable method for drug discovery and for dealing with a variety of problems in chemistry, physics, and material science.

Funnel-metadynamics and solution NMR to estimate protein-ligand affinities.

One of the intrinsic properties of proteins is their capacity to interact selectively with other molecules in their environment, inducing many chemical equilibria each differentiated by the mutual affinities of the components. A comprehensive understanding of these molecular binding processes at atomistic resolution requires formally the complete description of the system dynamics and statistics at the relevant time scales. While solution NMR observables are averaged over different time scales, from picosecond to second, recent new molecular dynamics protocols accelerated considerably the simulation time of realistic model systems. Based on known ligands recently discovered either by crystallography or NMR for the human peroxiredoxin 5, their affinities were for the first time accurately evaluated at atomistic resolution comparing absolute binding free-energy estimated by funnel-metadynamics simulations and solution NMR experiments. In particular, free-energy calculations are demonstrated to discriminate two closely related ligands as pyrocatechol and 4-methylpyrocathecol separated just by 1 kcal/mol in aqueous solution. The results provide a new experimental and theoretical basis for the estimation of ligand-protein affinities.

Sampling protein motion and solvent effect during ligand binding.

An exhaustive description of the molecular recognition mechanism between a ligand and its biological target is of great value because it provides the opportunity for an exogenous control of the related process. Very often this aim can be pursued using high resolution structures of the complex in combination with inexpensive computational protocols such as docking algorithms. Unfortunately, in many other cases a number of factors, like protein flexibility or solvent effects, increase the degree of complexity of ligand/protein interaction and these standard techniques are no longer sufficient to describe the binding event. We have experienced and tested these limits in the present study in which we have developed and revealed the mechanism of binding of a new series of potent inhibitors of Adenosine Deaminase. We have first performed a large number of docking calculations, which unfortunately failed to yield reliable results due to the dynamical character of the enzyme and the complex role of the solvent. Thus, we have stepped up the computational strategy using a protocol based on metadynamics. Our approach has allowed dealing with protein motion and solvation during ligand binding and finally identifying the lowest energy binding modes of the most potent compound of the series, 4-decyl-pyrazolo[1,5-a]pyrimidin-7-one.

Marine and semi-synthetic hydroxysteroids as new scaffolds for pregnane X receptor modulation.

In recent years many sterols with unusual structures and promising biological profiles have been identified from marine sources. Here we report the isolation of a series of 24-alkylated-hydroxysteroids from the soft coral Sinularia kavarattiensis, acting as pregnane X receptor (PXR) modulators. Starting from this scaffold a number of derivatives were prepared and evaluated for their ability to activate the PXR by assessing transactivation and quantifying gene expression. Our study reveals that ergost-5-en-3ß-ol (4) induces PXR transactivation in HepG2 cells and stimulates the expression of the PXR target gene CYP3A4. To shed light on the molecular basis of the interaction between these ligands and PXR, we investigated, through docking simulations, the binding mechanism of the most potent compound of the series, 4, to the PXR. Our findings provide useful functional and structural information to guide further investigations and drug design.

Molecular basis of cyclooxygenase enzymes (COXs) selective inhibition.

The widely used nonsteroidal anti-inflammatory drugs block the cyclooxygenase enzymes (COXs) and are clinically used for the treatment of inflammation, pain, and cancers. A selective inhibition of the different isoforms, particularly COX-2, is desirable, and consequently a deeper understanding of the molecular basis of selective inhibition is of great demand. Using an advanced computational technique we have simulated the full dissociation process of a highly potent and selective inhibitor, SC-558, in both COX-1 and COX-2. We have found a previously unreported alternative binding mode in COX-2 explaining the time-dependent inhibition exhibited by this class of inhibitors and consequently their long residence time inside this isoform. Our metadynamics-based approach allows us to illuminate the highly dynamical character of the ligand/protein recognition process, thus explaining a wealth of experimental data and paving the way to an innovative strategy for designing new COX inhibitors with tuned selectivity.

Perspectives on Ligand/Protein Binding Kinetics Simulations: Force Fields, Machine Learning, Sampling, and User-Friendliness.

Computational techniques applied to drug discovery have gained considerable popularity for their ability to filter potentially active drugs from inactive ones, reducing the time scale and costs of preclinical investigations. The main focus of these studies has historically been the search for compounds endowed with high affinity for a specific molecular target to ensure the formation of stable and long-lasting complexes. Recent evidence has also correlated the in vivo drug efficacy with its binding kinetics, thus opening new fascinating scenarios for ligand/protein binding kinetic simulations in drug discovery. The present article examines the state of the art in the field, providing a brief summary of the most popular and advanced ligand/protein binding kinetics techniques and evaluating their current limitations and the potential solutions to reach more accurate kinetic models. Particular emphasis is put on the need for a paradigm change in the present methodologies toward ligand and protein parametrization, the force field problem, characterization of the transition states, the sampling issue, and algorithms' performance, user-friendliness, and data openness.

Transferring chemical and energetic knowledge between molecular systems with machine learning.

Predicting structural and energetic properties of a molecular system is one of the fundamental tasks in molecular simulations, and it has applications in chemistry, biology, and medicine. In the past decade, the advent of machine learning algorithms had an impact on molecular simulations for various tasks, including property prediction of atomistic systems. In this paper, we propose a novel methodology for transferring knowledge obtained from simple molecular systems to a more complex one, endowed with a significantly larger number of atoms and degrees of freedom. In particular, we focus on the classification of high and low free-energy conformations. Our approach relies on utilizing (i) a novel hypergraph representation of molecules, encoding all relevant information for characterizing multi-atom interactions for a given conformation, and (ii) novel message passing and pooling layers for processing and making free-energy predictions on such hypergraph-structured data. Despite the complexity of the problem, our results show a remarkable Area Under the Curve of 0.92 for transfer learning from tri-alanine to the deca-alanine system. Moreover, we show that the same transfer learning approach can also be used in an unsupervised way to group chemically related secondary structures of deca-alanine in clusters having similar free-energy values. Our study represents a proof of concept that reliable transfer learning models for molecular systems can be designed, paving the way to unexplored routes in prediction of structural and energetic properties of biologically relevant systems.

Conformational plasticity and allosteric communication networks explain Shelterin protein TPP1 binding to human telomerase.

The Shelterin complex protein TPP1 interacts with human telomerase (TERT) by means of the TEL-patch region, controlling telomere homeostasis. Aberrations in the TPP1-TERT heterodimer formation might lead to short telomeres and severe diseases like dyskeratosis congenita and Hoyeraal-Hreidarsson syndrome. In the present study, we provide a thorough characterization of the structural properties of the TPP1's OB-domain by combining data coming from microsecond-long molecular dynamics calculations, time-series analyses, and graph-based networks. Our results show that the TEL-patch conformational freedom is influenced by a network of long-range amino acid communications that together determine the proper TPP1-TERT binding. Furthermore, we reveal that in TPP1 pathological variants Glu169Δ, Lys170Δ and Leu95Gln, the TEL-patch plasticity is reduced, affecting the correct binding to TERT and, in turn, telomere processivity, which eventually leads to accelerated aging of affected cells. Our study provides a structural basis for the design of TPP1-targeting ligands with therapeutic potential against cancer and telomeropathies.