Epitope Identification of an mGlu5 Receptor Nanobody Using Physics-Based Molecular Modeling and Deep Learning Techniques.

The world has witnessed a revolution in therapeutics with the development of biological medicines such as antibodies and antibody fragments, notably nanobodies. These nanobodies possess unique characteristics including high specificity and modulatory activity, making them promising candidates for therapeutic applications. Identifying their binding mode is essential for their development. Experimental structural techniques are effective to get such information, but they are expensive and time-consuming. Here, we propose a computational approach, aiming to identify the epitope of a nanobody that acts as an agonist and a positive allosteric modulator at the rat metabotropic glutamate receptor 5. We employed multiple structure modeling tools, including various artificial intelligence algorithms for epitope mapping. The computationally identified epitope was experimentally validated, confirming the success of our approach. Additional dynamics studies provided further insights on the modulatory activity of the nanobody. The employed methodologies and approaches initiate a discussion on the efficacy of diverse techniques for epitope mapping and later nanobody engineering.

A nanobody activating metabotropic glutamate receptor 4 discriminates between homo- and heterodimers.

There is growing interest in developing biologics due to their high target selectivity. The G protein-coupled homo- and heterodimeric metabotropic glutamate (mGlu) receptors regulate many synapses and are promising targets for the treatment of numerous brain diseases. Although subtype-selective allosteric small molecules have been reported, their effects on the recently discovered heterodimeric receptors are often not known. Here, we describe a nanobody that specifically and fully activates homodimeric human mGlu4 receptors. Molecular modeling and mutagenesis studies revealed that the nanobody acts by stabilizing the closed active state of the glutamate binding domain by interacting with both lobes. In contrast, this nanobody does not activate the heterodimeric mGlu2-4 but acts as a pure positive allosteric modulator. These data further reveal how an antibody can fully activate a class C receptor and bring further evidence that nanobodies represent an alternative way to specifically control mGlu receptor subtypes.

Neuropeptides, New Ligands of SARS-CoV-2 Nucleoprotein, a Potential Link between Replication, Inflammation and Neurotransmission.

This work identifies new ligands of the nucleoprotein N of SARS-CoV-2 by in silico screening, which used a new model of N, built from an Alphafold model refined by molecular dynamic simulations. The ligands were neuropeptides, such as substance P (1-7) and enkephalin, bound at a large site of the C-terminal or associated with the N-terminal ß-sheet. The BA4 and BA5 Omicron variants of N also exhibited a large site as in wt N, and an increased flexibility of the BA5 variant, enabling substance P binding. The binding sites of some ligands deduced from modeling in wt N were assessed by mutation studies in surface plasmon resonance experiments. Dynamic light scattering showed that the ligands impeded RNA binding to N, which likely inhibited replication. We suggest that the physiological role of these neuropeptides in neurotransmission, pain and vasodilation for cholecystokinin and substance P could be altered by binding to N. We speculate that N may link between viral replication and multiple pathways leading to long COVID-19 symptoms. Therefore, N may constitute a "danger hub" that needs to be inhibited, even at high cost for the host. Antivirals targeted to N may therefore reduce the risk of brain fog and stroke, and improve patients' health.

Automated antibody structure prediction using Accelrys tools: results and best practices.

We describe the methodology and results from our participation in the second Antibody Modeling Assessment experiment. During the experiment we predicted the structure of eleven unpublished antibody Fv fragments. Our prediction methods centered on template-based modeling; potential templates were selected from an antibody database based on their sequence similarity to the target in the framework regions. Depending on the quality of the templates, we constructed models of the antibody framework regions either using a single, chimeric or multiple template approach. The hypervariable loop regions in the initial models were rebuilt by grafting the corresponding regions from suitable templates onto the model. For the H3 loop region, we further refined models using ab initio methods. The final models were subjected to constrained energy minimization to resolve severe local structural problems. The analysis of the models submitted show that Accelrys tools allow for the construction of quite accurate models for the framework and the canonical CDR regions, with RMSDs to the X-ray structure on average below 1 Å for most of these regions. The results show that accurate prediction of the H3 hypervariable loops remains a challenge. Furthermore, model quality assessment of the submitted models show that the models are of quite high quality, with local geometry assessment scores similar to that of the target X-ray structures.

Novel Inhibitory Site Revealed by XAP044 Mode of Action on the Metabotropic Glutamate 7 Receptor Venus Flytrap Domain.

Metabotropic glutamate (mGlu) receptors play a key role in modulating most synapses in the brain. The mGlu7 receptors inhibit presynaptic neurotransmitter release and offer therapeutic possibilities for post-traumatic stress disorders or epilepsy. Screening campaigns provided mGlu7-specific allosteric modulators as the inhibitor XAP044 (Gee et al. J. Biol. Chem. 2014). In contrast to other mGlu receptor allosteric modulators, XAP044 does not bind in the transmembrane domain but to the extracellular domain of the mGlu7 receptor and not at the orthosteric site. Here, we identified the mode of action of XAP044, combining synthesis of derivatives, modeling and docking experiments, and mutagenesis. We propose a unique mode of action of these inhibitors, preventing the closure of the Venus flytrap agonist binding domain. While acting as a noncompetitive antagonist of L-AP4, XAP044 and derivatives act as apparent competitive antagonists of LSP4-2022. These data revealed more potent XAP044 analogues and new possibilities to target mGluRs.

Metabotropic glutamate receptor orthosteric ligands and their binding sites.

Metabotropic glutamate receptors (mGluRs) have been discovered almost four decades ago. Since then, their pharmacology has been largely developed as well as their structural organization. Indeed mGluRs are attractive therapeutic targets for numerous psychiatric and neurological disorders because of their modulating role of synaptic transmission. The more recent drug discovery programs have mostly concentrated on allosteric modulators. However, orthosteric agonists and antagonists have remained unavoidable pharmacological tools as, although not expected, many of them can reach the brain, or can be modified to reach the brain. This review focuses on the most common orthosteric ligands as well as on the few allosteric modulators interacting with the glutamate binding domain. The 3D-structures of these ligands at their binding sites are reported. For most of them, X-Ray structures or docked homology models are available. Because of the high conservation of the binding site, subtype selective agonists were not easy to find. Yet, some were discovered when extending their chemical structures in order to reach selective sites of the receptors.

Amino Acids Bearing Aromatic or Heteroaromatic Substituents as a New Class of Ligands for the Lysosomal Sialic Acid Transporter Sialin.

Sialin, encoded by the SLC17A5 gene, is a lysosomal sialic acid transporter defective in Salla disease, a rare inherited leukodystrophy. It also enables metabolic incorporation of exogenous sialic acids, leading to autoantibodies against N-glycolylneuraminic acid in humans. Here, we identified a novel class of human sialin ligands by virtual screening and structure-activity relationship studies. The ligand scaffold is characterized by an amino acid backbone with a free carboxylate, an N-linked aromatic or heteroaromatic substituent, and a hydrophobic side chain. The most potent compound, 45 (LSP12-3129), inhibited N-acetylneuraminic acid 1 (Neu5Ac) transport in a non-competitive manner with IC50 ≈ 2.5 µM, a value 400-fold lower than the KM for Neu5Ac. In vitro and molecular docking studies attributed the non-competitive character to selective inhibitor binding to the Neu5Ac site in a cytosol-facing conformation. Moreover, compound 45 rescued the trafficking defect of the pathogenic mutant (R39C) causing Salla disease. This new class of cell-permeant inhibitors provides tools to investigate the physiological roles of sialin and help develop pharmacological chaperones for Salla disease.

Increased Potency and Selectivity for Group III Metabotropic Glutamate Receptor Agonists Binding at Dual sites.

A group III metabotropic glutamate (mGlu) receptor agonist (PCEP) was identified by virtual HTS. This orthosteric ligand is composed by an l-AP4-derived fragment that mimics glutamate and a chain that binds into a neighboring pocket, offering possibilities to improve affinity and selectivity. Herein we describe a series of derivatives where the distal chain is replaced by an aromatic or heteroaromatic group. Potent agonists were identified, including some with a mGlu4 subtype preference, e.g., 17m (LSP1-2111) and 16g (LSP4-2022). Molecular modeling suggests that aromatic functional groups may bind at either one of the two chloride regulatory sites. These agonists may thus be considered as particular bitopic/dualsteric ligands. 17m was shown to reduce GABAergic synaptic transmission at striatopallidal synapses. We now demonstrate its inhibitory effect at glutamatergic parallel fiber-Purkinje cell synapses in the cerebellar cortex. Although these ligands have physicochemical properties that are markedly different from typical CNS drugs, they hold significant therapeutic potential.

Structure-based virtual screening: an application to human topoisomerase II alpha.

The eukaryotic topoisomerase II is involved in several vital processes, such as replication, transcription, and recombination. Many compounds interfering with the catalytic action of this enzyme are efficient in human cancer chemotherapy. We applied a methodology combining molecular modeling and virtual screening techniques to identify human topoisomerase II alphainhibitors. Data from structural biology and enzymatic assays together with a good background on the enzyme mechanism of action were helpful in the approach. A human topoisomerase II alpha model provided an insight into the structural features responsible for the activity of the enzyme. A protocol comprising several substructural and protein structure-based three-dimensional pharmacophore filters enabled the successful retrieving of inhibitors of the enzyme from large databases of compounds, thus validating the approach. A subset of protein structural features required for the enzyme inhibition at the protein-DNA interface were identified and incorporated into the pharmacophore models. Compounds sharing a DNA-intercalating chromophore and a moiety interfering with the protein active site emerged as good inhibitors.