Structure-Based Discovery of Negative Allosteric Modulators of the Metabotropic Glutamate Receptor 5

A novel heuristic of rigid docking scores positively correlates with full-length nuclear receptor LRH-1 regulation

The nuclear receptor Liver Receptor Homolog-1 (LRH-1, NR5A2) is a ligand-regulated transcription factor and validated drug target for several human diseases. LRH-1 activation is regulated by small molecule ligands, which bind to the ligand binding domain (LBD) within the full-length LRH-1. We recently identified 57 compounds that bind LRH-1, and unexpectedly found these compounds regulated either the isolated LBD, or the full-length LRH-1 in cells, with little overlap. Here, we correlated compound binding energy from a single rigid-body scoring function with full-length LRH-1 activity in cells. Although docking scores of the 57 hit compounds did not correlate with LRH-1 regulation in wet lab assays, a subset of the compounds had large differences in binding energy docked to the isolated LBD vs. full-length LRH-1, which we used to empirically derive a new metric of the docking scores we call "ΔΔG". Initial regressions, correlations and contingency analyses all suggest compounds with high ΔΔG values more frequently regulated LRH-1 in wet lab assays. We then docked all 57 compounds to 18 separate crystal structures of LRH-1 to obtain averaged ΔΔG values for each compound, which robustly and reproducibly associated with full-length LRH-1 activity in cells. Network analyses on the 18 crystal structures of LRH-1 suggest unique communication paths exist between the subsets of LRH-1 crystal structures that produced high vs. low ΔΔG values, identifying a structural relationship between ΔΔG and the position of Helix 6, a previously established regulatory helix important for LRH-1 regulation. Together, these data suggest rigid-body computational docking can be used to quickly calculate ΔΔG, which positively correlated with the ability of these 57 hit compounds to regulate full-length LRH-1 in cell-based assays. We propose ΔΔG as a novel computational tool that can be applied to LRH-1 drug screens to prioritize compounds for resource-intense secondary screening.

Negative allosteric modulator of Group Ⅰ mGluRs: Recent advances and therapeutic perspective for neuropathic pain

Neuropathic pain (NP) is a widespread public health problem that existing therapeutic treatments cannot manage adequately; therefore, novel treatment strategies are urgently required. G-protein-coupled receptors are important for intracellular signal transduction, and widely participate in physiological and pathological processes, including pain perception. Group I metabotropic glutamate receptors (mGluRs), including mGluR1 and mGluR5, are predominantly implicated in central sensitization, which can lead to hyperalgesia and allodynia. Many orthosteric site antagonists targeting Group I mGluRs have been found to alleviate NP, but their poor efficacy, low selectivity, and numerous side effects limit their development in NP treatment. Here we reviewed the advantages of Group I mGluRs negative allosteric modulators (NAMs) over orthosteric site antagonists based on allosteric modulation mechanism, and the challenges and opportunities of Group I mGluRs NAMs in NP treatment. This article aims to elucidate the advantages and future development potential of Group I mGluRs NAMs in the treatment of NP.

Large library docking identifies positive allosteric modulators of the calcium-sensing receptor

Positive allosteric modulator (PAM) drugs enhance the activation of the calcium-sensing receptor (CaSR) and suppress parathyroid hormone (PTH) secretion. Unfortunately, these hyperparathyroidism-treating drugs can induce hypocalcemia and arrhythmias. Seeking improved modulators, we docked libraries of 2.7 million and 1.2 billion molecules against the CaSR structure. The billion-molecule docking found PAMs with a 2.7-fold higher hit rate than the million-molecule library, with hits up to 37-fold more potent. Structure-based optimization led to nanomolar leads. In ex vivo organ assays, one of these PAMs was 100-fold more potent than the standard of care, cinacalcet, and reduced serum PTH levels in mice without the hypocalcemia typical of CaSR drugs. As determined from cryo-electron microscopy structures, the PAMs identified here promote CaSR conformations that more closely resemble the activated state than those induced by the established drugs.

The novel peptide LCGM-10 attenuates metabotropic glutamate receptor 5 activity and demonstrates behavioral effects in animal models

We employed a structural bioinformatics approach to develop novel peptides with predicted affinity to the binding site for negative allosteric modulators (NAMs) of metabotropic glutamate receptor 5 (mGluR5). Primary screening in zebrafish (Danio rerio) revealed a stimulatory effect of two peptides, LCGM-10 and LCGM-15. Target validation studies using calcium ion flux imaging and a luciferase reporter assay confirmed mGluR5 as the target. LCGM-10 showed greater potency than LCGM-15; it was comparable to that of the mGluR5 NAM 2-methyl-6-(phenylethynyl) pyridine (MPEP). Rodent behavioral screening in the open field and elevated plus maze revealed increased locomotor activity in both tests after acute LCGM-10 treatment, supported by further analysis of home cage spontaneous locomotor activity (SLA). The stimulating effect of a single LCGM-10 administration on SLA was evident up to 60 min after administration and was not accompanied by hypokinetic rebound observed for caffeine. According to our results, LCGM-10 has therapeutic potential to treat hypo- and dyskinesias of various etiologies. Further investigation of LCGM-10 effects in the delay discounting model of impulsive choice in rats revealed reduced trait impulsivity after single and chronic administrations, suggesting potential implication for attention deficit hyperactivity disorder, obsessive compulsive disorder, and addictions.

Small molecule allosteric modulation of the adenosine A1 receptor

G protein-coupled receptors (GPCRs) represent the target for approximately a third of FDA-approved small molecule drugs. The adenosine A₁ receptor (A₁R), one of four adenosine GPCR subtypes, has important (patho)physiological roles in humans. A₁R has well-established roles in the regulation of the cardiovascular and nervous systems, where it has been identified as a potential therapeutic target for a number of conditions, including cardiac ischemia-reperfusion injury, cognition, epilepsy, and neuropathic pain. A₁R small molecule drugs, typically orthosteric ligands, have undergone clinical trials. To date, none have progressed into the clinic, predominantly due to dose-limiting unwanted effects. The development of A₁R allosteric modulators that target a topographically distinct binding site represent a promising approach to overcome current limitations. Pharmacological parameters of allosteric ligands, including affinity, efficacy and cooperativity, can be optimized to regulate A₁R activity with high subtype, spatial and temporal selectivity. This review aims to offer insights into the A₁R as a potential therapeutic target and highlight recent advances in the structural understanding of A₁R allosteric modulation.

Computer-Aided Drug Design towards New Psychotropic and Neurological Drugs

Central nervous system (CNS) disorders are a therapeutic area in drug discovery where demand for new treatments greatly exceeds approved treatment options. This is complicated by the high failure rate in late-stage clinical trials, resulting in exorbitant costs associated with bringing new CNS drugs to market. Computer-aided drug design (CADD) techniques minimise the time and cost burdens associated with drug research and development by ensuring an advantageous starting point for pre-clinical and clinical assessments. The key elements of CADD are divided into ligand-based and structure-based methods. Ligand-based methods encompass techniques including pharmacophore modelling and quantitative structure activity relationships (QSARs), which use the relationship between biological activity and chemical structure to ascertain suitable lead molecules. In contrast, structure-based methods use information about the binding site architecture from an established protein structure to select suitable molecules for further investigation. In recent years, deep learning techniques have been applied in drug design and present an exciting addition to CADD workflows. Despite the difficulties associated with CNS drug discovery, advances towards new pharmaceutical treatments continue to be made, and CADD has supported these findings. This review explores various CADD techniques and discusses applications in CNS drug discovery from 2018 to November 2022.