GproteinDb in 2024: new G protein-GPCR couplings, AlphaFold2-multimer models and interface interactions.

G proteins are the major signal proteins of ∼800 receptors for medicines, hormones, neurotransmitters, tastants and odorants. GproteinDb offers integrated genomic, structural, and pharmacological data and tools for analysis, visualization and experiment design. Here, we present the first major update of GproteinDb greatly expanding its coupling data and structural templates, adding AlphaFold2 structure models of GPCR-G protein complexes and advancing the interactive analysis tools for their interfaces underlying coupling selectivity. We present insights on coupling agreement across datasets and parameters, including constitutive activity, agonist-induced activity and kinetics. GproteinDb is accessible at https://gproteindb.org.

SH2db, an information system for the SH2 domain.

SH2 domains are key mediators of phosphotyrosine-based signalling, and therapeutic targets for diverse, mostly oncological, disease indications. They have a highly conserved structure with a central beta sheet that divides the binding surface of the protein into two main pockets, responsible for phosphotyrosine binding (pY pocket) and substrate specificity (pY + 3 pocket). In recent years, structural databases have proven to be invaluable resources for the drug discovery community, as they contain highly relevant and up-to-date information on important protein classes. Here, we present SH2db, a comprehensive structural database and webserver for SH2 domain structures. To organize these protein structures efficiently, we introduce (i) a generic residue numbering scheme to enhance the comparability of different SH2 domains, (ii) a structure-based multiple sequence alignment of all 120 human wild-type SH2 domain sequences and their PDB and AlphaFold structures. The aligned sequences and structures can be searched, browsed and downloaded from the online interface of SH2db (http://sh2db.ttk.hu), with functions to conveniently prepare multiple structures into a Pymol session, and to export simple charts on the contents of the database. Our hope is that SH2db can assist researchers in their day-to-day work by becoming a one-stop shop for SH2 domain related research.

GPCRdb in 2023: state-specific structure models using AlphaFold2 and new ligand resources.

G protein-coupled receptors (GPCRs) are physiologically abundant signaling hubs routing hundreds of extracellular signal substances and drugs into intracellular pathways. The GPCR database, GPCRdb supports >5000 interdisciplinary researchers every month with reference data, analysis, visualization, experiment design and dissemination. Here, we present our fifth major GPCRdb release setting out with an overview of the many resources for receptor sequences, structures, and ligands. This includes recently published additions of class D generic residue numbers, a comparative structure analysis tool to identify functional determinants, trees clustering GPCR structures by 3D conformation, and mutations stabilizing inactive/active states. We provide new state-specific structure models of all human non-olfactory GPCRs built using AlphaFold2-MultiState. We also provide a new resource of endogenous ligands along with a larger number of surrogate ligands with bioactivity, vendor, and physiochemical descriptor data. The one-stop-shop ligand resources integrate ligands/data from the ChEMBL, Guide to Pharmacology, PDSP Ki and PubChem database. The GPCRdb is available at https://gpcrdb.org.

Molecular Mechanism of Labelling Functional Cysteines by Heterocyclic Thiones.

Heterocyclic thiones have recently been identified as reversible covalent warheads, consistent with their mild electrophilic nature. Little is known so far about their mechanism of action in labelling nucleophilic sidechains, especially cysteines. The vast number of tractable cysteines promotes a wide range of target proteins to examine; however, our focus was put on functional cysteines. We chose the main protease of SARS-CoV-2 harboring Cys145 at the active site that is a structurally characterized and clinically validated target of covalent inhibitors. We screened an in-house, cysteine-targeting covalent inhibitor library which resulted in several covalent fragment hits with benzoxazole, benzothiazole and benzimidazole cores. Thione derivatives and Michael acceptors were selected for further investigations with the objective of exploring the mechanism of inhibition of the thiones and using the thoroughly characterized Michael acceptors for benchmarking our studies. Classical and hybrid quantum mechanical/molecular mechanical (QM/MM) molecular dynamics simulations were carried out that revealed a new mechanism of covalent cysteine labelling by thione derivatives, which was supported by QM and free energy calculations and by a wide range of experimental results. Our study shows that the molecular recognition step plays a crucial role in the overall binding of both sets of molecules.

The G protein database, GproteinDb.

Two-thirds of signaling substances, several sensory stimuli and over one-third of drugs act via receptors coupling to G proteins. Here, we present an online platform for G protein research with reference data and tools for analysis, visualization and design of scientific studies across disciplines and areas. This platform may help translate new pharmacological, structural and genomic data into insights on G protein signaling vital for human physiology and medicine. The G protein database is accessible at https://gproteindb.org.

Boronic acid inhibitors of penicillin-binding protein 1b: serine and lysine labelling agents.

Penicillin-binding proteins (PBPs) contribute to bacterial cell wall biosynthesis and are targets of antibacterial agents. Here, we investigated PBP1b inhibition by boronic acid derivatives. Chemical starting points were identified by structure-based virtual screening and aliphatic boronic acids were selected for further investigations. Structure-activity relationship studies focusing on the branching of the boron-connecting carbon and quantum mechanical/molecular mechanical simulations showed that reaction barrier free energies are compatible with fast reversible covalent binding and small or missing reaction free energies limit the inhibitory activity of the investigated boronic acid derivatives. Therefore, covalent labelling of the lysine residue of the catalytic dyad was also investigated. Compounds with a carbonyl warhead and an appropriately positioned boronic acid moiety were shown to inhibit and covalently label PBP1b. Reversible covalent labelling of the catalytic lysine by imine formation and the stabilisation of the imine by dative N-B bond is a new strategy for PBP1b inhibition.

GPCRdb in 2021: integrating GPCR sequence, structure and function.

G protein-coupled receptors (GPCRs) form both the largest family of membrane proteins and drug targets, mediating the action of one-third of medicines. The GPCR database, GPCRdb serves >4 000 researchers every month and offers reference data, analysis of own or literature data, experiment design and dissemination of published datasets. Here, we describe new and updated GPCRdb resources with a particular focus on integration of sequence, structure and function. GPCRdb contains all human non-olfactory GPCRs (and >27 000 orthologs), G-proteins and arrestins. It includes over 2 000 drug and in-trial agents and nearly 200 000 ligands with activity and availability data. GPCRdb annotates all published GPCR structures (updated monthly), which are also offered in a refined version (with re-modeled missing/distorted regions and reverted mutations) and provides structure models of all human non-olfactory receptors in inactive, intermediate and active states. Mutagenesis data in the GPCRdb spans natural genetic variants, GPCR-G protein interfaces, ligand sites and thermostabilising mutations. A new sequence signature tool for identification of functional residue determinants has been added and two data driven tools to design ligand site mutations and constructs for structure determination have been updated extending their coverage of receptors and modifications. The GPCRdb is available at https://gpcrdb.org.

Activation-Free Sulfonyl Fluoride Probes for Fragment Screening.

SuFEx chemistry is based on the unique reactivity of the sulfonyl fluoride group with a range of nucleophiles. Accordingly, sulfonyl fluorides label multiple nucleophilic amino acid residues, making these reagents popular in both chemical biology and medicinal chemistry applications. The reactivity of sulfonyl fluorides nominates this warhead chemotype as a candidate for an external, activation-free general labelling tag. Here, we report the synthesis and characterization of a small sulfonyl fluoride library that yielded the 3-carboxybenzenesulfonyl fluoride warhead for tagging tractable targets at nucleophilic residues. Based on these results, we propose that coupling diverse fragments to this warhead would result in a library of sulfonyl fluoride bits (SuFBits), available for screening against protein targets. SuFBits will label the target if it binds to the core fragment, which facilitates the identification of weak fragments by mass spectrometry.

A stepwise one-pot synthesis of aliphatic thiols and their derivatives from acrylamides and sulfur.

Elemental sulfur enables the convenient formation of C-S bonds and the direct incoporation of S-S bonds. The reactivity of easily accessible electron deficient alkenes towards sulfur, however, is barely disclosed. Herein, we investigated the reactivity of acrylamides with sulfur and eventually developed a new pseudo-multicomponent reaction for the preparation of polysulfides. Sequential one-pot reduction led to diversely substituted thiols. Additional third stage one-pot modifications provided thioethers, unsymmetric disulfide and thioester.

Conservation of Allosteric Ligand Binding Sites in G-Protein Coupled Receptors.

Despite the growing number of G protein-coupled receptor (GPCR) structures, only 39 structures have been cocrystallized with allosteric inhibitors. These structures have been studied by protein mapping using the FTMap server, which determines the clustering of small organic probe molecules distributed on the protein surface. The method has found druggable sites overlapping with the cocrystallized allosteric ligands in 21 GPCR structures. Mapping of Alphafold2 generated models of these proteins confirms that the same sites can be identified without the presence of bound ligands. We then mapped the 394 GPCR X-ray structures available at the time of the analysis (September 2020). Results show that for each of the 21 structures with bound ligands there exist many other GPCRs that have a strong binding hot spot at the same location, suggesting potential allosteric sites in a large variety of GPCRs. These sites cluster at nine distinct locations, and each can be found in many different proteins. However, ligands binding at the same location generally show little or no similarity, and the amino acid residues interacting with these ligands also differ. Results confirm the possibility of specifically targeting these sites across GPCRs for allosteric modulation and help to identify the most likely binding sites among the limited number of potential locations. The FTMap server is available free of charge for academic and governmental use at https://ftmap.bu.edu/.

Small molecule inhibitors of RAS proteins with oncogenic mutations.

RAS proteins control a number of essential cellular processes as molecular switches in the human body. Presumably due to their important signalling role, RAS proteins are among the most frequently mutated oncogenes in human cancers. Hence, numerous efforts were done to develop appropriate therapies for RAS-mutant cancers in the last three decades. This review aimed to collect all of the reported small molecules that affect RAS signalling. These molecules can be divided in four main branches. First, we address approaches blocking RAS membrane association. Second, we focus on the stabilization efforts of non-productive RAS complexes. Third, we examine the approach to block RAS downstream signalling through disturbance of RAS-effector complex formation. Finally, we discuss direct inhibition; particularly the most recently reported covalent inhibitors, which are already advanced to human clinical trials.

Assessment of Tractable Cysteines for Covalent Targeting by Screening Covalent Fragments.

Targeted covalent inhibition and the use of irreversible chemical probes are important strategies in chemical biology and drug discovery. To date, the availability and reactivity of cysteine residues amenable for covalent targeting have been evaluated by proteomic and computational tools. Herein, we present a toolbox of fragments containing a 3,5-bis(trifluoromethyl)phenyl core that was equipped with chemically diverse electrophilic warheads showing a range of reactivities. We characterized the library members for their reactivity, aqueous stability and specificity for nucleophilic amino acids. By screening this library against a set of enzymes amenable for covalent inhibition, we showed that this approach experimentally characterized the accessibility and reactivity of targeted cysteines. Interesting covalent fragment hits were obtained for all investigated cysteine-containing enzymes.

WIDOCK: a reactive docking protocol for virtual screening of covalent inhibitors.

Here we present WIDOCK, a virtual screening protocol that supports the selection of diverse electrophiles as covalent inhibitors by incorporating ligand reactivity towards cysteine residues into AutoDock4. WIDOCK applies the reactive docking method (Backus et al. in Nature 534:570-574, 2016) and extends it into a virtual screening tool by introducing facile experimental or computational parametrization and a ligand focused evaluation scheme together with a retrospective and prospective validation against various therapeutically relevant targets. Parameters accounting for ligand reactivity are derived from experimental reaction kinetic data or alternatively from computed reaction barriers. The performance of this docking protocol was first evaluated by investigating compound series with diverse warhead chemotypes against KRASG12C, MurA and cathepsin B. In addition, WIDOCK was challenged on larger electrophilic libraries screened against OTUB2 and NUDT7. These retrospective analyses showed high sensitivity in retrieving experimental actives, by also leading to superior ROC curves, AUC values and better enrichments than the standard covalent docking tool available in AutoDock4 when compound collections with diverse warheads were investigated. Finally, we applied WIDOCK for the prospective identification of covalent human MAO-A inhibitors acting via a new mechanism by binding to Cys323. The inhibitory activity of several predicted compounds was experimentally confirmed and the labelling of Cys323 was proved by subsequent MS/MS measurements. These findings demonstrate the usefulness of WIDOCK as a warhead-sensitive, covalent virtual screening protocol.

Novel potent (dihydro)benzofuranyl piperazines as human histamine receptor ligands - Functional characterization and modeling studies on H3 and H4 receptors.

Histamine acts through four different receptors (H1R-H4R), the H3R and H4R being the most explored in the last years as drug targets. The H3R is a potential target to treat narcolepsy, Parkinson's disease, epilepsy, schizophrenia and several other CNS-related conditions, while H4R blockade leads to anti-inflammatory and immunomodulatory effects. Our group has been exploring the dihydrobenzofuranyl-piperazines (LINS01 series) as human H3R/H4R ligands as potential drug candidates. In the present study, a set of 12 compounds were synthesized from adequate (dihydro)benzofuran synthons through simple reactions with corresponding piperazines, giving moderate to high yields. Four compounds (1b, 1f, 1g and 1h) showed high hH3R affinity (pKi > 7), compound 1h being the most potent (pKi 8.4), and compound 1f showed the best efficiency (pKi 8.2, LE 0.53, LLE 5.85). BRET-based assays monitoring Gαi activity indicated that the compounds are potent antagonists. Only one compound (2c, pKi 7.1) presented high affinity for hH4R. In contrast to what was observed for hH3R, it showed partial agonist activity. Docking experiments indicated that bulky substituents occupy a hydrophobic pocket in hH3R, while the N-allyl group forms favorable interactions with hydrophobic residues in the TM2, 3 and 7, increasing the selectivity towards hH3R. Additionally, the importance of the indole NH in the interaction with Glu5.46 from hH4R was confirmed by the modeling results, explaining the affinity and agonistic activity of compound 2c. The data reported in this work represent important findings for the rational design of future compounds for hH3R and hH4R.

Controlling the selectivity of aminergic GPCR ligands from the extracellular vestibule.

In addition to the orthosteric binding pocket (OBP) of GPCRs, recent structural studies have revealed that there are several allosteric sites available for pharmacological intervention. The secondary binding pocket (SBP) of aminergic GPCRs is located in the extracellular vestibule of these receptors, and it has been suggested to be a potential selectivity pocket for bitopic ligands. Here, we applied a virtual screening protocol based on fragment docking to the SBP of the orthosteric ligand-receptor complex. This strategy was employed for a number of aminergic receptors. First, we designed dopamine D3 preferring bitopic compounds from a D2 selective orthosteric ligand. Next, we designed 5-HT2B selective bitopic compounds starting from the 5-HT1B preferring ergoline core of LSD. Comparing the serotonergic profiles of the new derivatives to that of LSD, we found that these derivatives became significantly biased towards the desired 5-HT2B receptor target. Finally, addressing the known limitations of H1 antihistamines, our protocol was successfully used to eliminate the well-known side effects related to the muscarinic M1 activity of amitriptyline while preserving H1 potency in some of the designed bitopic compounds. These applications highlight the usefulness of our new virtual screening protocol and offer a powerful strategy towards bitopic GPCR ligands with designed receptor profiles.

Discovery of a Non-Nucleoside SETD2 Methyltransferase Inhibitor against Acute Myeloid Leukemia.

Histone methyltransferases (HMTs) have attracted considerable attention as potential targets for pharmaceutical intervention in various malignant diseases. These enzymes are known for introducing methyl marks at specific locations of histone proteins, creating a complex system that regulates epigenetic control of gene expression and cell differentiation. Here, we describe the identification of first-generation cell-permeable non-nucleoside type inhibitors of SETD2, the only mammalian HMT that is able to tri-methylate the K36 residue of histone H3. By generating the epigenetic mark H3K36me3, SETD2 is involved in the progression of acute myeloid leukemia. We developed a structure-based virtual screening protocol that was first validated in retrospective studies. Next, prospective screening was performed on a large library of commercially available compounds. Experimental validation of 22 virtual hits led to the discovery of three compounds that showed dose-dependent inhibition of the enzymatic activity of SETD2. Compound C13 effectively blocked the proliferation of two acute myeloid leukemia (AML) cell lines with MLL rearrangements and led to decreased H3K36me3 levels, prioritizing this chemotype as a viable chemical starting point for drug discovery projects.

Continuous-Flow Synthesis of Thioureas, Enabled by Aqueous Polysulfide Solution.

We have developed the continuous-flow synthesis of thioureas in a multicomponent reaction starting from isocyanides, amidines, or amines and sulfur. The aqueous polysulfide solution enabled the application of sulfur under homogeneous and mild conditions. The crystallized products were isolated by simple filtration after the removal of the co-solvent, and the sulfur retained in the mother liquid. Presenting a wide range of thioureas synthesized by this procedure confirms the utility of the convenient continuous-flow application of sulfur.

Affinity and Selectivity Assessment of Covalent Inhibitors by Free Energy Calculations.

Covalent inhibitors have been gaining increased attention in drug discovery due to their beneficial properties such as long residence time, high biochemical efficiency, and specificity. Optimization of covalent inhibitors is a complex task that involves parallel monitoring of the noncovalent recognition elements and the covalent reactivity of the molecules to avoid potential idiosyncratic side effects. This challenge calls for special design protocols, including a variety of computational chemistry methods. Covalent inhibition proceeds through multiple steps, and calculating free energy changes of the subsequent binding events along the overall binding process would help us to better control the design of drug candidates. Inspired by the recent success of free energy calculations on reversible binders, we developed a complex protocol to compute free energies related to the noncovalent and covalent binding steps with thermodynamic integration and hybrid quantum mechanical/molecular mechanical (QM/MM) potential of mean force (PMF) calculations, respectively. In optimization settings, we examined two therapeutically relevant proteins complexed with congeneric sets of irreversible cysteine targeting covalent inhibitors. In the selectivity paradigm, we studied the irreversible binding of covalent inhibitors to phylogenetically close targets by a mutational approach. The results of the calculations are in good agreement with the experimental free energy values derived from the inhibition and kinetic constants (Ki and kinact) of the enzyme-inhibitor binding. The proposed method might be a powerful tool to predict the potency, selectivity, and binding mechanism of irreversible covalent inhibitors.

Benchmark Sets for Binding Hot Spot Identification in Fragment-Based Ligand Discovery.

Binding hot spots are regions of proteins that, due to their potentially high contribution to the binding free energy, have high propensity to bind small molecules. We present benchmark sets for testing computational methods for the identification of binding hot spots with emphasis on fragment-based ligand discovery. Each protein structure in the set binds a fragment, which is extended into larger ligands in other structures without substantial change in its binding mode. Structures of the same proteins without any bound ligand are also collected to form an unbound benchmark. We also discuss a set developed by Astex Pharmaceuticals for the validation of hot and warm spots for fragment binding. The set is based on the assumption that a fragment that occurs in diverse ligands in the same subpocket identifies a binding hot spot. Since this set includes only ligand-bound proteins, we added a set with unbound structures. All four sets were tested using FTMap, a computational analogue of fragment screening experiments to form a baseline for testing other prediction methods, and differences among the sets are discussed.

Large-scale evaluation of cytochrome P450 2C9 mediated drug interaction potential with machine learning-based consensus modeling.

Cytochrome P450 (CYP) enzymes play an important role in the metabolism of xenobiotics. Since they are connected to drug interactions, screening for potential inhibitors is of utmost importance in drug discovery settings. Our study provides an extensive classification model for P450-drug interactions with one of the most prominent members, the 2C9 isoenzyme. Our model involved the largest set of 45,000 molecules ever used for developing prediction models. The models are based on three different types of descriptors, (a) typical one, two and three dimensional molecular descriptors, (b) chemical and pharmacophore fingerprints and (c) interaction fingerprints with docking scores. Two machine learning algorithms, the boosted tree and the multilayer feedforward of resilient backpropagation network were used and compared based on their performances. The models were validated both internally and using external validation sets. The results showed that the consensus voting technique with custom probability thresholds could provide promising results even in large-scale cases without any restrictions on the applicability domain. Our best model was capable to predict the 2C9 inhibitory activity with the area under the receiver operating characteristic curve (AUC) of 0.85 and 0.84 for the internal and the external test sets, respectively. The chemical space covered with the largest available dataset has reached its limit encompassing publicly available bioactivity data for the 2C9 isoenzyme.