Structure-based discovery of CFTR potentiators and inhibitors.

The cystic fibrosis transmembrane conductance regulator (CFTR) is a crucial ion channel whose loss of function leads to cystic fibrosis, whereas its hyperactivation leads to secretory diarrhea. Small molecules that improve CFTR folding (correctors) or function (potentiators) are clinically available. However, the only potentiator, ivacaftor, has suboptimal pharmacokinetics and inhibitors have yet to be clinically developed. Here, we combine molecular docking, electrophysiology, cryo-EM, and medicinal chemistry to identify CFTR modulators. We docked ∼155 million molecules into the potentiator site on CFTR, synthesized 53 test ligands, and used structure-based optimization to identify candidate modulators. This approach uncovered mid-nanomolar potentiators, as well as inhibitors, that bind to the same allosteric site. These molecules represent potential leads for the development of more effective drugs for cystic fibrosis and secretory diarrhea, demonstrating the feasibility of large-scale docking for ion channel drug discovery.

Synthon-based ligand discovery in virtual libraries of over 11 billion compounds.

Structure-based virtual ligand screening is emerging as a key paradigm for early drug discovery owing to the availability of high-resolution target structures1-4 and ultra-large libraries of virtual compounds5,6. However, to keep pace with the rapid growth of virtual libraries, such as readily available for synthesis (REAL) combinatorial libraries7, new approaches to compound screening are needed8,9. Here we introduce a modular synthon-based approach-V-SYNTHES-to perform hierarchical structure-based screening of a REAL Space library of more than 11 billion compounds. V-SYNTHES first identifies the best scaffold-synthon combinations as seeds suitable for further growth, and then iteratively elaborates these seeds to select complete molecules with the best docking scores. This hierarchical combinatorial approach enables the rapid detection of the best-scoring compounds in the gigascale chemical space while performing docking of only a small fraction (<0.1%) of the library compounds. Chemical synthesis and experimental testing of novel cannabinoid antagonists predicted by V-SYNTHES demonstrated a 33% hit rate, including 14 submicromolar ligands, substantially improving over a standard virtual screening of the Enamine REAL diversity subset, which required approximately 100 times more computational resources. Synthesis of selected analogues of the best hits further improved potencies and affinities (best inhibitory constant (Ki) = 0.9 nM) and CB2/CB1 selectivity (50-200-fold). V-SYNTHES was also tested on a kinase target, ROCK1, further supporting its use for lead discovery. The approach is easily scalable for the rapid growth of combinatorial libraries and potentially adaptable to any docking algorithm.

Structures of the σ2 receptor enable docking for bioactive ligand discovery.

The σ2 receptor has attracted intense interest in cancer imaging1, psychiatric disease2, neuropathic pain3-5 and other areas of biology6,7. Here we determined the crystal structure of this receptor in complex with the clinical candidate roluperidone2 and the tool compound PB288. These structures templated a large-scale docking screen of 490 million virtual molecules, of which 484 compounds were synthesized and tested. We identified 127 new chemotypes with affinities superior to 1 µM, 31 of which had affinities superior to 50 nM. The hit rate fell smoothly and monotonically with docking score. We optimized three hits for potency and selectivity, and achieved affinities that ranged from 3 to 48 nM, with up to 250-fold selectivity versus the σ1 receptor. Crystal structures of two ligands bound to the σ2 receptor confirmed the docked poses. To investigate the contribution of the σ2 receptor in pain, two potent σ2-selective ligands and one potent σ1/σ2 non-selective ligand were tested for efficacy in a mouse model of neuropathic pain. All three ligands showed time-dependent decreases in mechanical hypersensitivity in the spared nerve injury model9, suggesting that the σ2 receptor has a role in nociception. This study illustrates the opportunities for rapid discovery of in vivo probes through structure-based screens of ultra large libraries, enabling study of underexplored areas of biology.

Virtual discovery of melatonin receptor ligands to modulate circadian rhythms.

The neuromodulator melatonin synchronizes circadian rhythms and related physiological functions through the actions of two G-protein-coupled receptors: MT1 and MT2. Circadian release of melatonin at night from the pineal gland activates melatonin receptors in the suprachiasmatic nucleus of the hypothalamus, synchronizing the physiology and behaviour of animals to the light-dark cycle1-4. The two receptors are established drug targets for aligning circadian phase to this cycle in disorders of sleep5,6 and depression1-4,7-9. Despite their importance, few in vivo active MT1-selective ligands have been reported2,8,10-12, hampering both the understanding of circadian biology and the development of targeted therapeutics. Here we docked more than 150 million virtual molecules to an MT1 crystal structure, prioritizing structural fit and chemical novelty. Of these compounds, 38 high-ranking molecules were synthesized and tested, revealing ligands with potencies ranging from 470 picomolar to 6 micromolar. Structure-based optimization led to two selective MT1 inverse agonists-which were topologically unrelated to previously explored chemotypes-that acted as inverse agonists in a mouse model of circadian re-entrainment. Notably, we found that these MT1-selective inverse agonists advanced the phase of the mouse circadian clock by 1.3-1.5 h when given at subjective dusk, an agonist-like effect that was eliminated in MT1- but not in MT2-knockout mice. This study illustrates the opportunities for modulating melatonin receptor biology through MT1-selective ligands and for the discovery of previously undescribed, in vivo active chemotypes from structure-based screens of diverse, ultralarge libraries.

An open-source drug discovery platform enables ultra-large virtual screens.

On average, an approved drug currently costs US$2-3 billion and takes more than 10 years to develop1. In part, this is due to expensive and time-consuming wet-laboratory experiments, poor initial hit compounds and the high attrition rates in the (pre-)clinical phases. Structure-based virtual screening has the potential to mitigate these problems. With structure-based virtual screening, the quality of the hits improves with the number of compounds screened2. However, despite the fact that large databases of compounds exist, the ability to carry out large-scale structure-based virtual screening on computer clusters in an accessible, efficient and flexible manner has remained difficult. Here we describe VirtualFlow, a highly automated and versatile open-source platform with perfect scaling behaviour that is able to prepare and efficiently screen ultra-large libraries of compounds. VirtualFlow is able to use a variety of the most powerful docking programs. Using VirtualFlow, we prepared one of the largest and freely available ready-to-dock ligand libraries, with more than 1.4 billion commercially available molecules. To demonstrate the power of VirtualFlow, we screened more than 1 billion compounds and identified a set of structurally diverse molecules that bind to KEAP1 with submicromolar affinity. One of the lead inhibitors (iKeap1) engages KEAP1 with nanomolar affinity (dissociation constant (Kd) = 114 nM) and disrupts the interaction between KEAP1 and the transcription factor NRF2. This illustrates the potential of VirtualFlow to access vast regions of the chemical space and identify molecules that bind with high affinity to target proteins.

Iterative computational design and crystallographic screening identifies potent inhibitors targeting the Nsp3 macrodomain of SARS-CoV-2.

The nonstructural protein 3 (NSP3) of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) contains a conserved macrodomain enzyme (Mac1) that is critical for pathogenesis and lethality. While small-molecule inhibitors of Mac1 have great therapeutic potential, at the outset of the COVID-19 pandemic, there were no well-validated inhibitors for this protein nor, indeed, the macrodomain enzyme family, making this target a pharmacological orphan. Here, we report the structure-based discovery and development of several different chemical scaffolds exhibiting low- to sub-micromolar affinity for Mac1 through iterations of computer-aided design, structural characterization by ultra-high-resolution protein crystallography, and binding evaluation. Potent scaffolds were designed with in silico fragment linkage and by ultra-large library docking of over 450 million molecules. Both techniques leverage the computational exploration of tangible chemical space and are applicable to other pharmacological orphans. Overall, 160 ligands in 119 different scaffolds were discovered, and 153 Mac1-ligand complex crystal structures were determined, typically to 1 Å resolution or better. Our analyses discovered selective and cell-permeable molecules, unexpected ligand-mediated conformational changes within the active site, and key inhibitor motifs that will template future drug development against Mac1.

Ultra-large library docking for discovering new chemotypes.

Despite intense interest in expanding chemical space, libraries containing hundreds-of-millions to billions of diverse molecules have remained inaccessible. Here we investigate structure-based docking of 170 million make-on-demand compounds from 130 well-characterized reactions. The resulting library is diverse, representing over 10.7 million scaffolds that are otherwise unavailable. For each compound in the library, docking against AmpC ß-lactamase (AmpC) and the D4 dopamine receptor were simulated. From the top-ranking molecules, 44 and 549 compounds were synthesized and tested for interactions with AmpC and the D4 dopamine receptor, respectively. We found a phenolate inhibitor of AmpC, which revealed a group of inhibitors without known precedent. This molecule was optimized to 77 nM, which places it among the most potent non-covalent AmpC inhibitors known. Crystal structures of this and other AmpC inhibitors confirmed the docking predictions. Against the D4 dopamine receptor, hit rates fell almost monotonically with docking score, and a hit-rate versus score curve predicted that the library contained 453,000 ligands for the D4 dopamine receptor. Of 81 new chemotypes discovered, 30 showed submicromolar activity, including a 180-pM subtype-selective agonist of the D4 dopamine receptor.

Challenges for chemistry in Ukraine after the war: Ukrainian science requires rebuilding and support.

The unprovoked Russian invasion has created considerable challenges for Ukrainian science. In this article, we discuss actions needed to support and rebuild Ukrainian science and educational systems. The proposed actions take into account past Ukrainian scientific achievements including developments in organic chemistry.

SNAr or Sulfonylation? Chemoselective Amination of Halo(het)arene Sulfonyl Halides for Synthetic Applications and Ultralarge Compound Library Design.

The chemoselectivity of halo(het)arene sulfonyl halide aminations is studied thoroughly under parallel synthesis conditions, and the scope and limitations of the method are established. It is shown that SNAr-reactive sulfonyl halides typically undergo sulfonamide synthesis during the first step; the second amination is also possible provided that the SNAr-active center is sufficiently reactive. On the contrary, sulfonyl fluorides bearing an arylating moiety undergo selective transformation at the latter reactive center under proper control. Further sulfur-fluoride exchange (SuFEx) is also possible, which can be especially valuable for some sulfonyl halide classes. The developed two-step parallel double amination protocol provides access to a 6.67-billion compound synthetically tractable REAL-type chemical space (76% expected synthesis success rate).

Novel Fragment Inhibitors of PYCR1 from Docking-Guided X-ray Crystallography.

The proline biosynthetic enzyme Δ1-pyrroline-5-carboxylate (P5C) reductase 1 (PYCR1) is one of the most consistently upregulated enzymes across multiple cancer types and central to the metabolic rewiring of cancer cells. Herein, we describe a fragment-based, structure-first approach to the discovery of PYCR1 inhibitors. Thirty-seven fragment-like carboxylic acids in the molecular weight range of 143-289 Da were selected from docking and then screened using X-ray crystallography as the primary assay. Strong electron density was observed for eight compounds, corresponding to a crystallographic hit rate of 22%. The fragments are novel compared to existing proline analog inhibitors in that they block both the P5C substrate pocket and the NAD(P)H binding site. Four hits showed inhibition of PYCR1 in kinetic assays, and one has lower apparent IC50 than the current best proline analog inhibitor. These results show proof-of-concept for our inhibitor discovery approach and provide a basis for fragment-to-lead optimization.

Generation of multimillion chemical space based on the parallel Groebke-Blackburn-Bienaymé reaction.

Parallel Groebke-Blackburn-Bienaymé reaction was evaluated as a source of multimillion chemically accessible chemical space. Two most popular classical protocols involving the use of Sc(OTf)3 and TsOH as the catalysts were tested on a broad substrate scope, and prevalence of the first method was clearly demonstrated. Furthermore, the scope and limitations of the procedure were established. A model 790-member library was obtained with 85% synthesis success rate. These results were used to generate a 271-Mln. readily accessible (REAL) heterocyclic chemical space mostly containing unique chemotypes, which was confirmed by comparative analysis with commercially available compound collections. Meanwhile, this chemical space contained 432 compounds that already showed biological activity according to the ChEMBL database.

Advancing molecular graphs with descriptors for the prediction of chemical reaction yields.

Chemical yield is the percentage of the reactants converted to the desired products. Chemists use predictive algorithms to select high-yielding reactions and score synthesis routes, saving time and reagents. This study suggests a novel graph neural network architecture for chemical yield prediction. The network combines structural information about participants of the transformation as well as molecular and reaction-level descriptors. It works with incomplete chemical reactions and generates reactants-product atom mapping. We show that the network benefits from advanced information by comparing it with several machine learning models and molecular representations. Models included logistic regression, support vector machine, CatBoost, and Bidirectional Encoder Representations from Transformers. Molecular representations included extended-connectivity fingerprints, Morgan fingerprints, SMILESVec embeddings, and textual. Classification and regression objectives were assessed for each model and feature set. The goal of each classification model was to separate zero- and non-zero-yielding reactions. The models were trained and evaluated on a proprietary dataset of 10 reaction types. Also, the models were benchmarked on two public single reaction type datasets. The study was supplemented with analysis of data, results, and errors, as well as the impact of steric factors, side reactions, isolation, and purification efficiency. The supplementary code is available at https://github.com/SoftServeInc/yield-paper.

ZINC-22─A Free Multi-Billion-Scale Database of Tangible Compounds for Ligand Discovery.

Purchasable chemical space has grown rapidly into the tens of billions of molecules, providing unprecedented opportunities for ligand discovery but straining the tools that might exploit these molecules at scale. We have therefore developed ZINC-22, a database of commercially accessible small molecules derived from multi-billion-scale make-on-demand libraries. The new database and tools enable analog searching in this vast new space via a facile GUI, CartBlanche, drawing on similarity methods that scale sublinearly in the number of molecules. The new library also uses data organization methods, enabling rapid lookup of molecules and their physical properties, including conformations, partial atomic charges, c Log P values, and solvation energies, all crucial for molecule docking, which had become slow with older database organizations in previous versions of ZINC. As the libraries have continued to grow, we have been interested in finding whether molecular diversity has suffered, for instance, because certain scaffolds have come to dominate via easy analoging. This has not occurred thus far, and chemical diversity continues to grow with database size, with a log increase in Bemis-Murcko scaffolds for every two-log unit increase in database size. Most new scaffolds come from compounds with the highest heavy atom count. Finally, we consider the implications for databases like ZINC as the libraries grow toward and beyond the trillion-molecule range. ZINC is freely available to everyone and may be accessed at cartblanche22.docking.org, via Globus, and in the Amazon AWS and Oracle OCI clouds.

105 K Wide Room Temperature Spin Transition Memory Due to a Supramolecular Latch Mechanism.

Little is known about the mechanisms behind the bistability (memory) of molecular spin transition compounds over broad temperature ranges (>100 K). To address this point, we report on a new discrete FeII neutral complex [FeIIL2]0 (1) based on a novel asymmetric tridentate ligand 2-(5-(3-methoxy-4H-1,2,4-triazol-3-yl)-6-(1H-pyrazol-1-yl))pyridine (L). Due to the asymmetric cone-shaped form, in the lattice, the formed complex molecules stack into a one-dimensional (1D) supramolecular chain. In the case of the rectangular supramolecular arrangement of chains in methanolates 1-A and 1-B (both orthorhombic, Pbcn) differing, respectively, by bent and extended spatial conformations of the 3-methoxy groups (3MeO), a moderate cooperativity is observed. In contrast, the hexagonal-like arrangement of supramolecular chains in polymorph 1-C (monoclinic, P21/c) results in steric coupling of the transforming complex species with the peripheral flipping 3MeO group. The group acts as a supramolecular latch, locking the huge geometric distortion of complex 1 and in turn the trigonal distortion of the central FeII ion in the high-spin state, thereby keeping it from the transition to the low-spin state over a large thermal range. Analysis of the crystal packing of 1-C reveals significantly changing patterns of close intermolecular interactions on going between the phases substantiated by the energy framework analysis. The detected supramolecular mechanism leads to a record-setting robust 105 K wide hysteresis spanning the room temperature region and an atypically large TLIESST relaxation value of 104 K of the photoexcited high-spin state. This work highlights a viable pathway toward a new generation of cleverly designed molecular memory materials.

A Close-up Look at the Chemical Space of Commercially Available Building Blocks for Medicinal Chemistry.

The ability to efficiently synthesize desired compounds can be a limiting factor for chemical space exploration in drug discovery. This ability is conditioned not only by the existence of well-studied synthetic protocols but also by the availability of corresponding reagents, so-called building blocks (BBs). In this work, we present a detailed analysis of the chemical space of 400 000 purchasable BBs. The chemical space was defined by corresponding synthons─fragments contributed to the final molecules upon reaction. They allow an analysis of BB physicochemical properties and diversity, unbiased by the leaving and protective groups in actual reagents. The main classes of BBs were analyzed in terms of their availability, rule-of-two-defined quality, and diversity. Available BBs were eventually compared to a reference set of biologically relevant synthons derived from ChEMBL fragmentation, in order to illustrate how well they cover the actual medicinal chemistry needs. This was performed on a newly constructed universal generative topographic map of synthon chemical space that enables visualization of both libraries and analysis of their overlapped and library-specific regions.

One-pot parallel synthesis of 1,3,5-trisubstituted 1,2,4-triazoles.

An implementation of the three-component one-pot approach to unsymmetrical 1,3,5-trisubstituted-1,2,4-triazoles into combinatorial chemistry is described. The procedure is based on the coupling of amidines with carboxylic acids and subsequent cyclization with hydrazines. After the preliminary assessment of the reagent scope, the method had 81% success rate in parallel synthesis. It was shown that over a billion-sized chemical space of readily accessible ("REAL") compounds may be generated based on the proposed methodology. Analysis of physicochemical parameters shows that the library contains significant fractions of both drug-like and "beyond-rule-of-five" members. More than 10 million of accessible compounds meet the strictest lead-likeness criteria. Additionally, 195 Mln of sp3-enriched compounds can be produced. This makes the proposed approach a valuable tool in medicinal chemistry.

Synthesis of α-substituted 2-(1H-1,2,4-triazol-3-yl)acetates and 5-amino-2,4-dihydro-3H-pyrazol-3-ones via the Pinner strategy.

A series of 2-(1H-1,2,4-triazol-3-yl)acetates, as well as 4-mono- and 4,4-disubstituted 5-amino-2,4-dihydro-3H-pyrazol-3-ones (including spirocyclic derivatives) have been synthesized using the Pinner reaction strategy. α-Mono- and α,α-disubstituted ethyl cyanoacetates were converted into the corresponding carboxyimidate salts that served as the key intermediates. Their further reaction with formylhydrazide or hydrazine hydrate provided triazolylacetates or aminopyrazolones (including spirocyclic derivatives), depending on the structure of the starting Pinner salt and the nature of the nucleophile. The scope and limitations of the developed synthetic method have been established.

Synthesis of spirocyclic ß- and γ-sultams by one-pot reductive cyclization of cyanoalkylsulfonyl fluorides.

One-pot intramolecular cyclization of novel sp3-enriched cyanoalkylsulfonyl fluorides into spirocyclic ß- or γ-sultams is disclosed. The method relies on nitrile group reduction followed by sulfonylation of amino group thus formed upon mild conditions (NaBH4, NiCl2·6H2O in MeOH). Cyclization proceeds smoothly with considerable efficiency (48-84%, 10 examples) on up to 30 g scale. The cyanoalkylsulfonyl fluoride intermediates can be obtained via S-nucleophilic substitution in ß-functionalized alkanenitriles or double alkylation of α-alkylthioacetonitrile, followed by oxidative chlorination with Cl2 and further reaction with KHF2. The title mono- and bifunctional sultams are advanced sp3-enriched building blocks for drug discovery and organic synthesis providing novel substitution patterns and frameworks mimicking saturated nitrogen heterocycles such as pyrrolidine/pyrrolidone.

ZINC20-A Free Ultralarge-Scale Chemical Database for Ligand Discovery.

Identifying and purchasing new small molecules to test in biological assays are enabling for ligand discovery, but as purchasable chemical space continues to grow into the tens of billions based on inexpensive make-on-demand compounds, simply searching this space becomes a major challenge. We have therefore developed ZINC20, a new version of ZINC with two major new features: billions of new molecules and new methods to search them. As a fully enumerated database, ZINC can be searched precisely using explicit atomic-level graph-based methods, such as SmallWorld for similarity and Arthor for pattern and substructure search, as well as 3D methods such as docking. Analysis of the new make-on-demand compound sets by these and related tools reveals startling features. For instance, over 97% of the core Bemis-Murcko scaffolds in make-on-demand libraries are unavailable from "in-stock" collections. Correspondingly, the number of new Bemis-Murcko scaffolds is rising almost as a linear fraction of the elaborated molecules. Thus, an 88-fold increase in the number of molecules in the make-on-demand versus the in-stock sets is built upon a 16-fold increase in the number of Bemis-Murcko scaffolds. The make-on-demand library is also more structurally diverse than physical libraries, with a massive increase in disc- and sphere-like shaped molecules. The new system is freely available at zinc20.docking.org.

Regioselective Synthesis of Functionalized 3- or 5-Fluoroalkyl Isoxazoles and Pyrazoles from Fluoroalkyl Ynones and Binucleophiles.

A facile synthetic route toward either 3- or 5-fluoroalkyl-substituted isoxazoles or pyrazoles containing an additional functionalization site was developed and applied on a multigram scale. The elaborated approach extends the scope of fluoroalkyl substituents for introduction into the heterocyclic moiety, and uses convenient transformations of the side chain for incorporation of fluoroalkyl-substituted azoles into the structures of biologically active molecules. The utility of the obtained building blocks for isosteric replacement of alkyl-substituted isoxazole and pyrazole was shown by the synthesis of fluorinated Isocarboxazid and Mepiprazole analogues.