Structure-Guided Design of G-Protein-Coupled Receptor Polypharmacology

Systematic Investigation of Dual-Target-Directed Ligands

Multitarget-directed ligands (MTDLs) are compounds rationally designed to affect multiple targets, aiming for a better therapeutic profile. For over 20 years, MTDLs have garnered increasing attention, the idea being that their full potential would have been achieved, thanks to unprecedented target combinations and advanced medicinal chemistry strategies. This study presents a literature mining effort resulting in a data set of dual-target-directed ligands (DTDLs), the fundamental example of MTDLs. We used this data set to evaluate the rationale behind target selection and the chemical novelty of DTDLs targeting specific protein combinations. Our analysis focused on DTDL targets in terms of biological function, disease association, structure, and chemogenomic traits. We also compared DTDLs with single-target compounds. We found that well-known target pathology associations often guide DTDL design, leveraging existing chemical scaffolds and binding pocket similarities. These findings highlight the current state of the field and suggest substantial untapped potential for rational polypharmacology.

Identification of a potent and selective LAPTc inhibitor by RapidFire-Mass Spectrometry, with antichagasic activity

BACKGROUND

Chagas disease is caused by the protozoan parasite Trypanosoma cruzi and leads to ~10,000 deaths each year. Nifurtimox and benznidazole are the only two drugs available but have significant adverse effects and limited efficacy. New chemotherapeutic agents are urgently required. Here we identified inhibitors of the acidic M17 leucyl-aminopeptidase from T. cruzi (LAPTc) that show promise as novel starting points for Chagas disease drug discovery.

METHODOLOGY/PRINCIPAL FINDINGS

A RapidFire-MS screen with a protease-focused compound library identified novel LAPTc inhibitors. Twenty-eight hits were progressed to the dose-response studies, from which 12 molecules inhibited LAPTc with IC50 < 34 μM. Of these, compound 4 was the most potent hit and mode of inhibition studies indicate that compound 4 is a competitive LAPTc inhibitor, with Ki 0.27 μM. Compound 4 is selective with respect to human LAP3, showing a selectivity index of >500. Compound 4 exhibited sub-micromolar activity against intracellular T. cruzi amastigotes, and while the selectivity-window against the host cells was narrow, no toxicity was observed for un-infected HepG2 cells. In silico modelling of the LAPTc-compound 4 interaction is consistent with the competitive mode of inhibition. Molecular dynamics simulations reproduce the experimental binding strength (-8.95 kcal/mol), and indicate a binding mode based mainly on hydrophobic interactions with active site residues without metal cation coordination.

CONCLUSIONS/SIGNIFICANCE

Our data indicates that these new LAPTc inhibitors should be considered for further development as antiparasitic agents for the treatment of Chagas disease.

Computational drug development for membrane protein targets

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learning structure-based design and the evaluation of big data. Recent protein structure predictions based on machine learning tools have delivered surprisingly reliable results for water-soluble and membrane proteins but have limitations for development of drugs that target membrane proteins. Structural transitions of membrane proteins have a central role during transmembrane signaling and are often influenced by therapeutic compounds. Resolving the structural and functional basis of dynamic transmembrane signaling networks, especially within the native membrane or cellular environment, remains a central challenge for drug development. Tackling this challenge will require an interplay between experimental and computational tools, such as super-resolution optical microscopy for quantification of the molecular interactions of cellular signaling networks and their modulation by potential drugs, cryo-electron microscopy for determination of the structural transitions of proteins in native cell membranes and entire cells, and computational tools for data analysis and prediction of the structure and function of cellular signaling networks, as well as generation of promising drug candidates.

Structure-based discovery of conformationally selective inhibitors of the serotonin transporter

The serotonin transporter (SERT) removes synaptic serotonin and is the target of anti-depressant drugs. SERT adopts three conformations: outward-open, occluded, and inward-open. All known inhibitors target the outward-open state except ibogaine, which has unusual anti-depressant and substance-withdrawal effects, and stabilizes the inward-open conformation. Unfortunately, ibogaine's promiscuity and cardiotoxicity limit the understanding of inward-open state ligands. We docked over 200 million small molecules against the inward-open state of the SERT. Thirty-six top-ranking compounds were synthesized, and thirteen inhibited; further structure-based optimization led to the selection of two potent (low nanomolar) inhibitors. These stabilized an outward-closed state of the SERT with little activity against common off-targets. A cryo-EM structure of one of these bound to the SERT confirmed the predicted geometry. In mouse behavioral assays, both compounds had anxiolytic- and anti-depressant-like activity, with potencies up to 200-fold better than fluoxetine (Prozac), and one substantially reversed morphine withdrawal effects.

The Impact of the Secondary Binding Pocket on the Pharmacology of Class A GPCRs

G-protein coupled receptors (GPCRs) are considered important therapeutic targets due to their pathophysiological significance and pharmacological relevance. Class A receptors represent the largest group of GPCRs that gives the highest number of validated drug targets. Endogenous ligands bind to the orthosteric binding pocket (OBP) embedded in the intrahelical space of the receptor. During the last 10 years, however, it has been turned out that in many receptors there is secondary binding pocket (SBP) located in the extracellular vestibule that is much less conserved. In some cases, it serves as a stable allosteric site harbouring allosteric ligands that modulate the pharmacology of orthosteric binders. In other cases it is used by bitopic compounds occupying both the OBP and SBP. In these terms, SBP binding moieties might influence the pharmacology of the bitopic ligands. Together with others, our research group showed that SBP binders contribute significantly to the affinity, selectivity, functional activity, functional selectivity and binding kinetics of bitopic ligands. Based on these observations we developed a structure-based protocol for designing bitopic compounds with desired pharmacological profile.

Discovery and In Vivo Proof of Concept of a Highly Potent Dual Inhibitor of Soluble Epoxide Hydrolase and Acetylcholinesterase for the Treatment of Alzheimer's Disease

With innumerable clinical failures of target-specific drug candidates for multifactorial diseases, such as Alzheimer's disease (AD), which remains inefficiently treated, the advent of multitarget drug discovery has brought a new breath of hope. Here, we disclose a class of 6-chlorotacrine (huprine)-TPPU hybrids as dual inhibitors of the enzymes soluble epoxide hydrolase (sEH) and acetylcholinesterase (AChE), a multitarget profile to provide cumulative effects against neuroinflammation and memory impairment. Computational studies confirmed the gorge-wide occupancy of both enzymes, from the main site to a secondary site, including a so far non-described AChE cryptic pocket. The lead compound displayed in vitro dual nanomolar potencies, adequate brain permeability, aqueous solubility, human microsomal stability, lack of neurotoxicity, and it rescued memory, synaptic plasticity, and neuroinflammation in an AD mouse model, after low dose chronic oral administration.

Heterobivalent Ligand for the Adenosine A2A-Dopamine D2 Receptor Heteromer

A G protein-coupled receptor heteromer that fulfills the established criteria for its existence in vivo is the complex between adenosine A_2A (A_2AR) and dopamine D₂ (D₂R) receptors. Here, we have designed and synthesized heterobivalent ligands for the A_2AR-D₂R heteromer with various spacer lengths. The indispensable simultaneous binding of these ligands to the two different orthosteric sites of the heteromer has been evaluated by radioligand competition-binding assays in the absence and presence of specific peptides that disrupt the formation of the heteromer, label-free dynamic mass redistribution assays in living cells, and molecular dynamic simulations. This combination of techniques has permitted us to identify compound 26 [K_DB1 (A_2AR) = 2.1 nM, K_DB1 (D₂R) = 0.13 nM], with a spacer length of 43-atoms, as a true bivalent ligand that simultaneously binds to the two different orthosteric sites. Moreover, bioluminescence resonance energy transfer experiments indicate that 26 favors the stabilization of the A_2AR-D₂R heteromer.

A2A Adenosine Receptor Antagonists in Neurodegenerative Diseases

BACKGROUND

Alzheimer's disease (AD) is the most common form of dementia worldwide, with approximately 6 million cases reported in America in 2020. The clinical signs of AD include cognitive dysfunction, apathy, anxiety and neuropsychiatric signs, and pathogenetic mechanisms that involve amyloid peptide-β extracellular accumulation and tau hyperphosphorylation. Unfortunately, current drugs to treat AD can provide only symptomatic relief but are not disease-modifying molecules able to revert AD progression. The endogenous modulator adenosine, through A_2A receptor activation, plays a role in synaptic loss and neuroinflammation, which are crucial for cognitive impairment and memory damage.

OBJECTIVE

In this review, recent advances covering A_2A adenosine receptor antagonists will be extensively reviewed, providing a basis for the rational design of future A_2A inhibitors.

METHODS

Herein, the literature on A_2A adenosine receptors and their role in synaptic plasticity and neuroinflammation, as well as the effects of A_2A antagonism in animal models of AD and in humans, are reviewed. Furthermore, current chemical and structure-based strategies are presented.

RESULTS

Caffeine, the most widely consumed natural product stimulant and an A_2A antagonist, improves human memory. Similarly, synthetic A_2A receptor antagonists, as described in this review, may provide a means to fight AD.

CONCLUSION

This review highlights the clinical potential of A_2A adenosine receptor antagonists as a novel approach to treat patients with AD.

Structure-Based Virtual Screening for Ligands of G Protein-Coupled Receptors: What Can Molecular Docking Do for You?

G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome and are important therapeutic targets. During the last decade, the number of atomic-resolution structures of GPCRs has increased rapidly, providing insights into drug binding at the molecular level. These breakthroughs have created excitement regarding the potential of using structural information in ligand design and initiated a new era of rational drug discovery for GPCRs. The molecular docking method is now widely applied to model the three-dimensional structures of GPCR-ligand complexes and screen for chemical probes in large compound libraries. In this review article, we first summarize the current structural coverage of the GPCR superfamily and the understanding of receptor-ligand interactions at atomic resolution. We then present the general workflow of structure-based virtual screening and strategies to discover GPCR ligands in chemical libraries. We assess the state of the art of this research field by summarizing prospective applications of virtual screening based on experimental structures. Strategies to identify compounds with specific efficacy and selectivity profiles are discussed, illustrating the opportunities and limitations of the molecular docking method. Our overview shows that structure-based virtual screening can discover novel leads and will be essential in pursuing the next generation of GPCR drugs. SIGNIFICANCE STATEMENT: Extraordinary advances in the structural biology of G protein-coupled receptors have revealed the molecular details of ligand recognition by this large family of therapeutic targets, providing novel avenues for rational drug design. Structure-based docking is an efficient computational approach to identify novel chemical probes from large compound libraries, which has the potential to accelerate the development of drug candidates.