Comparative Study of Allosteric GPCR Binding Sites and Their Ligandability Potential.

The steadily growing number of experimental G-protein-coupled receptor (GPCR) structures has revealed diverse locations of allosteric modulation, and yet few drugs target them. This gap highlights the need for a deeper understanding of allosteric modulation in GPCR drug discovery. The current work introduces a systematic annotation scheme to structurally classify GPCR binding sites based on receptor class, transmembrane helix contacts, and, for membrane-facing sites, membrane sublocation. This GPCR specific annotation scheme was applied to 107 GPCR structures bound by small molecules contributing to 24 distinct allosteric binding sites for comparative evaluation of three binding site detection methods (BioGPS, SiteMap, and FTMap). BioGPS identified the most in 22 of 24 sites. In addition, our property analysis showed that extrahelical allosteric ligands and binding sites represent a distinct chemical space characterized by shallow pockets with low volume, and the corresponding allosteric ligands showed an enrichment of halogens. Furthermore, we demonstrated that combining receptor and ligand similarity can be a viable method for ligandability assessment. One challenge regarding site prediction is the ligand shaping effect on the observed binding site, especially for extrahelical sites where the ligand-induced effect was most pronounced. To our knowledge, this is the first study presenting a binding site annotation scheme standardized for GPCRs, and it allows a comparison of allosteric binding sites across different receptors in an objective way. The insight from this study provides a framework for future GPCR binding site studies and highlights the potential of targeting allosteric sites for drug development.

Structure of the complement C5a receptor bound to the extra-helical antagonist NDT9513727.

The complement system is a crucial component of the host response to infection and tissue damage. Activation of the complement cascade generates anaphylatoxins including C5a and C3a. C5a exerts a pro-inflammatory effect via the G-protein-coupled receptor C5a anaphylatoxin chemotactic receptor 1 (C5aR1, also known as CD88) that is expressed on cells of myeloid origin. Inhibitors of the complement system have long been of interest as potential drugs for the treatment of diseases such as sepsis, rheumatoid arthritis, Crohn's disease and ischaemia-reperfusion injuries. More recently, a role of C5a in neurodegenerative conditions such as Alzheimer's disease has been identified. Peptide antagonists based on the C5a ligand have progressed to phase 2 trials in psoriasis and rheumatoid arthritis; however, these compounds exhibited problems with off-target activity, production costs, potential immunogenicity and poor oral bioavailability. Several small-molecule competitive antagonists for C5aR1, such as W-54011 and NDT9513727, have been identified by C5a radioligand-binding assays. NDT9513727 is a non-peptide inverse agonist of C5aR1, and is highly selective for the primate and gerbil receptors over those of other species. Here, to study the mechanism of action of C5a antagonists, we determine the structure of a thermostabilized C5aR1 (known as C5aR1 StaR) in complex with NDT9513727. We found that the small molecule bound between transmembrane helices 3, 4 and 5, outside the helical bundle. One key interaction between the small molecule and residue Trp2135.49 seems to determine the species selectivity of the compound. The structure demonstrates that NDT9513727 exerts its inverse-agonist activity through an extra-helical mode of action.

BiKi Life Sciences: A New Suite for Molecular Dynamics and Related Methods in Drug Discovery.

In this paper, we introduce the BiKi Life Sciences suite. This software makes it easy for computational medicinal chemists to run ad hoc molecular dynamics protocols in a novel and task-oriented environment; as a notebook, BiKi (acronym of Binding Kinetics) keeps memory of any activity together with dependencies among them. It offers unique accelerated protein-ligand binding/unbinding methods and other useful tools to gain actionable knowledge from molecular dynamics simulations and to simplify the drug discovery process.

Structure-based predictions of activity cliffs.

In drug discovery, it is generally accepted that neighboring molecules in a given descriptor's space display similar activities. However, even in regions that provide strong predictability, structurally similar molecules can occasionally display large differences in potency. In QSAR jargon, these discontinuities in the activity landscape are known as "activity cliffs". In this study, we assessed the reliability of ligand docking and virtual ligand screening schemes in predicting activity cliffs. We performed our calculations on a diverse, independently collected database of cliff-forming cocrystals. Starting from ideal situations, which allowed us to establish our baseline, we progressively moved toward simulating more realistic scenarios. Ensemble- and template-docking achieved a significant level of accuracy, suggesting that, despite the well-known limitations of empirical scoring schemes, activity cliffs can be accurately predicted by advanced structure-based methods.

Multitarget drug discovery for Alzheimer's disease: triazinones as BACE-1 and GSK-3ß inhibitors.

Cumulative evidence strongly supports that the amyloid and tau hypotheses are not mutually exclusive, but concomitantly contribute to neurodegeneration in Alzheimer's disease (AD). Thus, the development of multitarget drugs which are involved in both pathways might represent a promising therapeutic strategy. Accordingly, reported here in is the discovery of 6-amino-4-phenyl-3,4-dihydro-1,3,5-triazin-2(1H)-ones as the first class of molecules able to simultaneously modulate BACE-1 and GSK-3ß. Notably, one triazinone showed well-balanced in vitro potencies against the two enzymes (IC50 of (18.03±0.01) µM and (14.67±0.78) µM for BACE-1 and GSK-3ß, respectively). In cell-based assays, it displayed effective neuroprotective and neurogenic activities and no neurotoxicity. It also showed good brain permeability in a preliminary pharmacokinetic assessment in mice. Overall, triazinones might represent a promising starting point towards high quality lead compounds with an AD-modifying potential.

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.

Increased throughput in methods for simulating protein ligand binding and unbinding.

By incorporating full flexibility and enabling the quantification of crucial parameters such as binding free energies and residence times, methods for investigating protein-ligand binding and unbinding via molecular dynamics provide details on the involved mechanisms at the molecular level. While these advancements hold promise for impacting drug discovery, a notable drawback persists: their relatively time-consuming nature limits throughput. Herein, we survey recent implementations which, employing a blend of enhanced sampling techniques, a clever choice of collective variables, and often machine learning, strive to enhance the efficiency of new and previously reported methods without compromising accuracy. Particularly noteworthy is the validation of these methods that was often performed on systems mirroring real-world drug discovery scenarios.

Investigating the Unbinding of Muscarinic Antagonists from the Muscarinic 3 Receptor.

Patient symptom relief is often heavily influenced by the residence time of the inhibitor-target complex. For the human muscarinic receptor 3 (hMR3), tiotropium is a long-acting bronchodilator used in conditions such as asthma or chronic obstructive pulmonary disease (COPD). The mechanistic insights into this inhibitor remain unclear; specifically, the elucidation of the main factors determining the unbinding rates could help develop the next generation of antimuscarinic agents. Using our novel unbinding algorithm, we were able to investigate ligand dissociation from hMR3. The unbinding paths of tiotropium and two of its analogues, N-methylscopolamin and homatropine methylbromide, show a consistent qualitative mechanism and allow us to identify the structural bottleneck of the process. Furthermore, our machine learning-based analysis identified key roles of the ECL2/TM5 junction involved in the transition state. Additionally, our results point to relevant changes at the intracellular end of the TM6 helix leading to the ICL3 kinase domain, highlighting the closest residue L482. This residue is located right between two main protein binding sites involved in signal transduction for hMR3's activation and regulation. We also highlight key pharmacophores of tiotropium that play determining roles in the unbinding kinetics and could aid toward drug design and lead optimization.

Galantamine-memantine hybrids for Alzheimer's disease: The influence of linker rigidity in biological activity and pharmacokinetic properties.

Neurodegenerative processes characterizing Alzheimer's disease (AD) are strictly related to the impairment of cholinergic and glutamatergic neurotransmitter systems which provoke synaptic loss. These experimental evidences still represent the foundation of the actual standard-of-care treatment for AD, albeit palliative, consisting on the coadministration of an acetylcholinesterase inhibitor and the NMDAR antagonist memantine. In looking for more effective treatments, we previously developed a series of galantamine-memantine hybrids where compound 1 (ARN14140) emerged with the best-balanced action toward the targets of interest paired to neuroprotective efficacy in a murine AD model. Unfortunately, it showed a suboptimal pharmacokinetic profile, which required intracerebroventricular administration for in vivo studies. In this work we designed and synthesized new hybrids with fewer rotatable bonds, which is related to higher brain exposure. Particularly, compound 2, bearing a double bond in the tether, ameliorated the biological profile of compound 1 in invitro studies, increasing cholinesterases inhibitory potencies and selective antagonism toward excitotoxic-related GluN1/2B NMDAR over beneficial GluN1/2A NMDAR. Furthermore, it showed increased plasma stability and comparable microsomal stability in vitro, paired with lower half-life and faster clearance in vivo. Remarkably, pharmacokinetic evaluations of compound 2 showed a promising increase in brain uptake in comparison to compound 1, representing the starting point for further chemical optimizations.

Combining dyad protonation and active site plasticity in BACE-1 structure-based drug design.

The ability of the BACE-1 catalytic dyad to adopt multiple protonation states and the conformational flexibility of the active site have hampered the reliability of computational screening campaigns carried out on this drug target for Alzheimer's disease. Here, we propose a protocol that, for the first time, combining quantum mechanical calculations, molecular dynamics, and conformational ensemble virtual ligand screening addresses these issues simultaneously. The encouraging results prefigure this approach as a valuable tool for future drug discovery campaigns.

Dopamine D3 receptor ligands: a patent review (2014-2020).

INTRODUCTION: Compelling evidence identified D3 dopamine receptor (D3R) as a suitable target for therapeutic intervention on CNS-associated disorders, cancer, and other conditions. Several efforts have been made toward developing potent and selective ligands for modulating signaling pathways operated by these GPCRs. The rational design of D3R ligands endowed with a pharmacologically relevant profile has traditionally not encountered much support from computational methods due to a very limited knowledge of the receptor structure and of its conformational dynamics. Recent progress in structural biology will change this state of affairs in the next decade. AREAS COVERED: This review provides an overview of the recent (2014-2020) patent literature on novel classes of D3R ligands developed within the framework of CNS-related diseases, cancer, and additional conditions. When possible, an in-depth description of both in vitro and in vivo generated data is presented. New therapeutic applications of known molecules with activity at D3R are discussed. EXPERT OPINION: Building on current knowledge, future D3R-focused drug discovery campaigns will be propelled by a combination of unprecedented availability of structural information with advanced computational and analytical methods. The design of D3R ligands with the sought activity, efficacy, and selectivity profile will become increasingly more streamlined.

The multitarget FAAH inhibitor/D3 partial agonist ARN15381 decreases nicotine self-administration in male rats.

Tobacco use disorder is a worldwide health problem for which available medications show limited efficacy. Nicotine is the psychoactive component of tobacco responsible for its addictive liability. Similar to other addictive drugs, nicotine enhances mesolimbic dopamine transmission. Inhibition of the fatty acid amide hydrolase (FAAH), the enzyme responsible for the degradation of the endocannabinoid anandamide (AEA), palmitoylethanolamide (PEA) and oleoylethanolamide (OEA), reduces nicotine-enhanced dopamine transmission and acquisition of nicotine self-administration in rats. Down-regulation of dopamine transmission by antagonists or partial agonists of the dopamine D3 receptor (DRD3) also reduced nicotine self-administration and conditioned place preference. Based on these premises, we evaluated the effect of ARN15381, a multitarget compound showing FAAH inhibition and DRD3 partial agonist activity in the low nanomolar range, on nicotine self-administration in rats. Pretreatment with ARN15381 dose dependently decreased self-administration of a nicotine dose at the top of the nicotine dose/response (D/R) curve, while it did not affect self-administration of a nicotine dose laying on the descending limb of the D/R curve. Conversely, pretreatment with the selective FAAH inhibitor URB597 and the DRD3 partial agonist CJB090 failed to modify nicotine self-administration independent of the nicotine dose self-administered. Our data indicates that the concomitant FAAH inhibition and DRD3 partial agonism produced by ARN15381 is key to the observed reduction of nicotine self-administration, demonstrating that a multitarget approach may hold clinical importance for the treatment of tobacco use disorder.

SERAPhiC: a benchmark for in silico fragment-based drug design.

Our main objective was to compile a data set of high-quality protein-fragment complexes and make it publicly available. Once assembled, the data set was challenged using docking procedures to address the following questions: (i) Can molecular docking correctly reproduce the experimentally solved structures? (ii) How thorough must the sampling be to replicate the experimental data? (iii) Can commonly used scoring functions discriminate between the native pose and other energy minima? The data set, named SERAPhiC (Selected Fragment Protein Complexes), is publicly available in a ready-to-dock format ( http://www.iit.it/en/drug-discovery-and-development/seraphic.html ). It offers computational medicinal chemists a reliable test set for both in silico protocol assessment and software development.

Inflammation causes remodeling of mitochondrial cytochrome c oxidase mediated by the bifunctional gene C15orf48.

Dysregulated mitochondrial function is a hallmark of immune-mediated inflammatory diseases. Cytochrome c oxidase (CcO), which mediates the rate-limiting step in mitochondrial respiration, is remodeled during development and in response to changes of oxygen availability, but there has been little study of CcO remodeling during inflammation. Here, we describe an elegant molecular switch mediated by the bifunctional transcript C15orf48, which orchestrates the substitution of the CcO subunit NDUFA4 by its paralog C15ORF48 in primary macrophages. Expression of C15orf48 is a conserved response to inflammatory signals and occurs in many immune-related pathologies. In rheumatoid arthritis, C15orf48 mRNA is elevated in peripheral monocytes and proinflammatory synovial tissue macrophages, and its expression positively correlates with disease severity and declines in remission. C15orf48 is also expressed by pathogenic macrophages in severe coronavirus disease 2019 (COVID-19). Study of a rare metabolic disease syndrome provides evidence that loss of the NDUFA4 subunit supports proinflammatory macrophage functions.

Discovery and SAR Evolution of Pyrazole Azabicyclo[3.2.1]octane Sulfonamides as a Novel Class of Non-Covalent N-Acylethanolamine-Hydrolyzing Acid Amidase (NAAA) Inhibitors for Oral Administration.

Inhibition of intracellular N-acylethanolamine-hydrolyzing acid amidase (NAAA) activity is a promising approach to manage the inflammatory response under disabling conditions. In fact, NAAA inhibition preserves endogenous palmitoylethanolamide (PEA) from degradation, thus increasing and prolonging its anti-inflammatory and analgesic efficacy at the inflamed site. In the present work, we report the identification of a potent, systemically available, novel class of NAAA inhibitors, featuring a pyrazole azabicyclo[3.2.1]octane structural core. After an initial screening campaign, a careful structure-activity relationship study led to the discovery of endo-ethoxymethyl-pyrazinyloxy-8-azabicyclo[3.2.1]octane-pyrazole sulfonamide 50 (ARN19689), which was found to inhibit human NAAA in the low nanomolar range (IC50 = 0.042 µM) with a non-covalent mechanism of action. In light of its favorable biochemical, in vitro and in vivo drug-like profile, sulfonamide 50 could be regarded as a promising pharmacological tool to be further investigated in the field of inflammatory conditions.

Recipes for the selection of experimental protein conformations for virtual screening.

The use of multiple X-ray protein structures has been reported to be an efficient alternative for the representation of the binding pocket flexibility needed for accurate small molecules docking. However, the docking performance of the individual single conformations varies widely, and adding certain conformations to an ensemble is even counterproductive. Here we used a very large and diverse benchmark of 1068 X-ray protein conformations of 99 therapeutically relevant proteins, first, to compare the performance of the ensemble and single-conformation docking and, second, to find the properties of the best-performing conformers that can be used to select a smaller set of conformers for ensemble docking. The conformer selection has been validated through retrospective virtual screening experiments aimed at separating known ligand binders from decoys. We found that the conformers cocrystallized with the largest ligands displayed high selectivity for binders, and when combined in ensembles they consistently provided better results than randomly chosen protein conformations. The use of ensembles encompassing between 3 and 5 experimental conformations consistently improved the docking accuracy and binders vs decoys separation.

Multi-target dopamine D3 receptor modulators: Actionable knowledge for drug design from molecular dynamics and machine learning.

Local changes in the structure of G-protein coupled receptors (GPCR) binders largely affect their pharmacological profile. While the sought efficacy can be empirically obtained by introducing local modifications, the underlining structural explanation can remain elusive. Here, molecular dynamics (MD) simulations of the eticlopride-bound inactive state of the Dopamine D3 Receptor (D3DR) have been clustered using a machine learning-based approach in the attempt to rationalize the efficacy change in four congeneric modulators. Accumulating extended MD trajectories of receptor-ligand complexes, we observed how the increase in ligand flexibility progressively destabilized the crystal structure of the inactivated receptor. To prospectively validate this model, a partial agonist was rationally designed based on structural insights and computational modeling, and eventually synthesized and tested. Results turned out to be in line with the predictions. This case study suggests that the investigation of ligand flexibility in the framework of extended MD simulations can assist and inform drug design strategies, highlighting its potential role as a powerful in silico counterpart to functional assays.

Multitarget Compounds for Bipolar Disorder: From Rational Design to Preliminary Pharmacokinetic Evaluation.

Due to the complex and multifactorial nature of bipolar disorder (BD), single-target drugs have traditionally provided limited relief with no disease-modifying effects. In line with the polypharmacology paradigm, we attempted to overcome these limitations by devising two series of multitarget-directed ligands endowed with both a partial agonist profile at dopamine receptor D3 (D3R) and inhibitory activity against glycogen synthase kinase 3 beta (GSK-3ß). These are two structurally unrelated targets that play independent, yet connected, roles in cognition and mood regulation. Two compounds (7 and 10) emerged as promising D3R/GSK-3ß multitarget-directed ligands with nanomolar activity at D3R and low-micromolar inhibition of GSK-3ß, thereby confirming, albeit preliminarily, the feasibility of our strategy. Furthermore, 7 showed promising drug-like properties in stability and pharmacokinetic studies.

Small molecule aurora kinases inhibitors.

Aurora kinases represent one of the emerging targets in oncology drug discovery. These kinases play important role in centrosome maturation, chromosome separation and cytokinesis. They are overexpressed in a broad range of tumor cell lines and human primary tumors; thus, their inhibition may open up new opportunities to develop novel anti-cancer agents. A range of potent small molecule inhibitors of Aurora kinases have been identified and found to have antitumor activity. Some of these agents are undergoing evaluation in clinical trials. Most synthetic Aurora kinase inhibitors are ATP-competitive, which makes selectivity a potential problem. However, despite the high sequence similarity in the ATP-binding pocket, several compounds are very specific in their targets. The ability of the inhibitors to extend their binding to regions adjacent to the ATP pocket, including the hydrophobic back pocket, contributes to the selectivity, since structural differences can be found in these regions. A common structural feature of the inhibitors is a planar heterocyclic ring system able to occupy the adenino-binding region and to mimic the adenine-kinase interactions, by making backbone hydrogen bond interactions, but also by extensive hydrophobic contacts within this part of the pocket. In this review we would like to analyse the main inhibitors, focusing on chemical structures, SAR and biological properties. The specific targeting of these kinases could result in highly active drugs with minimal collateral host toxicity. Moreover, the combination of Aurora inhibitors with other chemotherapeutic agents may open new opportunities in cancer chemotherapy.