Discovery of a Potent and Selective Tyrosine Kinase 2 Inhibitor: TAK-279.

TYK2 is a key mediator of IL12, IL23, and type I interferon signaling, and these cytokines have been implicated in the pathogenesis of multiple inflammatory and autoimmune diseases such as psoriasis, rheumatoid arthritis, lupus, and inflammatory bowel diseases. Supported by compelling data from human genome-wide association studies and clinical results, TYK2 inhibition through small molecules is an attractive therapeutic strategy to treat these diseases. Herein, we report the discovery of a series of highly selective pseudokinase (Janus homology 2, JH2) domain inhibitors of TYK2 enzymatic activity. A computationally enabled design strategy, including the use of FEP+, was instrumental in identifying a pyrazolo-pyrimidine core. We highlight the utility of computational physics-based predictions used to optimize this series of molecules to identify the development candidate 30, a potent, exquisitely selective cellular TYK2 inhibitor that is currently in Phase 2 clinical trials for the treatment of psoriasis and psoriatic arthritis.

Potent and selective TYK2-JH1 inhibitors highly efficacious in rodent model of psoriasis.

TYK2 is a member of the JAK family of kinases and a key mediator of IL-12, IL-23, and type I interferon signaling. These cytokines have been implicated in the pathogenesis of multiple inflammatory and autoimmune diseases such as psoriasis, rheumatoid arthritis, lupus, and inflammatory bowel diseases. Supported by compelling data from human genetic association studies, TYK2 inhibition is an attractive therapeutic strategy for these diseases. Herein, we report the discovery of a series of highly selective catalytic site TYK2 inhibitors designed using FEP+ and structurally enabled design starting from a virtual screen hit. We highlight the structure-based optimization to identify a lead candidate 30, a potent cellular TYK2 inhibitor with excellent selectivity, pharmacokinetic properties, and in vivo efficacy in a mouse psoriasis model.

Inhibition of Acetyl-CoA Carboxylase by Phosphorylation or the Inhibitor ND-654 Suppresses Lipogenesis and Hepatocellular Carcinoma.

The incidence of hepatocellular carcinoma (HCC) is rapidly increasing due to the prevalence of obesity and non-alcoholic fatty liver disease, but the molecular triggers that initiate disease development are not fully understood. We demonstrate that mice with targeted loss-of-function point mutations within the AMP-activated protein kinase (AMPK) phosphorylation sites on acetyl-CoA carboxylase 1 (ACC1 Ser79Ala) and ACC2 (ACC2 Ser212Ala) have increased liver de novo lipogenesis (DNL) and liver lesions. The same mutation in ACC1 also increases DNL and proliferation in human liver cancer cells. Consistent with these findings, a novel, liver-specific ACC inhibitor (ND-654) that mimics the effects of ACC phosphorylation inhibits hepatic DNL and the development of HCC, improving survival of tumor-bearing rats when used alone and in combination with the multi-kinase inhibitor sorafenib. These studies highlight the importance of DNL and dysregulation of AMPK-mediated ACC phosphorylation in accelerating HCC and the potential of ACC inhibitors for treatment.

Anti-leukaemic activity of the TYK2 selective inhibitor NDI-031301 in T-cell acute lymphoblastic leukaemia.

Activation of tyrosine kinase 2 (TYK2) contributes to the aberrant survival of T-cell acute lymphoblastic leukaemia (T-ALL) cells. Here we demonstrate the anti-leukaemic activity of a novel TYK2 inhibitor, NDI-031301. NDI-031301 is a potent and selective inhibitor of TYK2 that induced robust growth inhibition of human T-ALL cell lines. NDI-031301 treatment of human T-ALL cell lines resulted in induction of apoptosis that was not observed with the JAK inhibitors tofacitinib and baricitinib. Further investigation revealed that NDI-031301 treatment uniquely leads to activation of three mitogen-activated protein kinases (MAPKs), resulting in phosphorylation of ERK, SAPK/JNK and p38 MAPK coincident with PARP cleavage. Activation of p38 MAPK occurred within 1 h of NDI-031301 treatment and was responsible for NDI-031301-induced T-ALL cell death, as pharmacological inhibition of p38 MAPK partially rescued apoptosis induced by TYK2 inhibitor. Finally, daily oral administration of NDI-031301 at 100 mg/kg bid to immunodeficient mice engrafted with KOPT-K1 T-ALL cells was well tolerated, and led to decreased tumour burden and a significant survival benefit. These results support selective inhibition of TYK2 as a promising potential therapeutic strategy for T-ALL.

An experiment on the impact of a neonicotinoid pesticide on honeybees: the value of a formal analysis of the data.

BACKGROUND: We assess the analysis of the data resulting from a field experiment conducted by Pilling et al. (PLoS ONE. doi: 10.1371/journal.pone.0077193, 5) on the potential effects of thiamethoxam on honeybees. The experiment had low levels of replication, so Pilling et al. concluded that formal statistical analysis would be misleading. This would be true if such an analysis merely comprised tests of statistical significance and if the investigators concluded that lack of significance meant little or no effect. However, an analysis that includes estimation of the size of any effects-with confidence limits-allows one to reach conclusions that are not misleading and that produce useful insights. MAIN BODY: For the data of Pilling et al., we use straightforward statistical analysis to show that the confidence limits are generally so wide that any effects of thiamethoxam could have been large without being statistically significant. Instead of formal analysis, Pilling et al. simply inspected the data and concluded that they provided no evidence of detrimental effects and from this that thiamethoxam poses a "low risk" to bees. CONCLUSIONS: Conclusions derived from the inspection of the data were not just misleading in this case but also are unacceptable in principle, for if data are inadequate for a formal analysis (or only good enough to provide estimates with wide confidence intervals), then they are bound to be inadequate as a basis for reaching any sound conclusions. Given that the data in this case are largely uninformative with respect to the treatment effect, any conclusions reached from such informal approaches can do little more than reflect the prior beliefs of those involved.

A novel inhibitor of active protein kinase G attenuates chronic inflammatory and osteoarthritic pain.

Activating PKG-1α induces a long-term hyperexcitability (LTH) in nociceptive neurons. Since the LTH correlates directly with chronic pain in many animal models, we tested the hypothesis that inhibiting PKG-1α would attenuate LTH-mediated pain. We first synthesized and characterized compound N46 (N-((3R,4R)-4-(4-(2-fluoro-3-methoxy-6-propoxybenzoyl)benzamido)pyrrolidin-3-yl)-1H-indazole-5-carboxamide). N46 inhibits PKG-1α with an IC50 of 7.5 nmol, was highly selective when tested against a panel of 274 kinases, and tissue distribution studies indicate that it does not enter the CNS. To evaluate its antinociceptive potential, we used 2 animal models in which the pain involves both activated PKG-1α and LTH. Injecting complete Freund's adjuvant (CFA) into the rat hind paw causes a thermal hyperalgesia that was significantly attenuated 24 hours after a single intravenous injection of N46. Next, we used a rat model of osteoarthritic knee joint pain and found that a single intra-articular injection of N46 alleviated the pain 14 days after the pain was established and the relief lasted for 7 days. Thermal hyperalgesia and osteoarthritic pain are also associated with the activation of the capsaicin-activated transient receptor protein vanilloid-1 (TRPV1) channel. We show that capsaicin activates PKG-1α in nerves and that a subcutaneous delivery of N46 attenuated the mechanical and thermal hypersensitivity elicited by exposure to capsaicin. Thus, PKG-1α appears to be downstream of the transient receptor protein vanilloid-1. Our studies provide proof of concept in animal models that a PKG-1α antagonist has a powerful antinociceptive effect on persistent, already existing inflammatory pain. They further suggest that N46 is a valid chemotype for the further development of such antagonists.

Accelerating drug discovery through tight integration of expert molecular design and predictive scoring.

Modeling protein-ligand interactions has been a central goal of computational chemistry for many years. We here review recent progress toward this goal, and highlight the role free energy calculation methods and computational solvent analysis techniques are now having in drug discovery. We further describe recent use of these methodologies to advance two separate drug discovery programs targeting acetyl-CoA carboxylase and tyrosine kinase 2. These examples suggest that tight integration of sophisticated chemistry teams with state-of-the-art computational methods can dramatically improve the efficiency of small molecule drug discovery.

Multiconformation, Density Functional Theory-Based pKa Prediction in Application to Large, Flexible Organic Molecules with Diverse Functional Groups.

We consider the conformational flexibility of molecules and its implications for micro- and macro-pKa. The corresponding formulas are derived and discussed against the background of a comprehensive scientific and algorithmic description of the latest version of our computer program Jaguar pKa, a density functional theory-based pKa predictor, which is now capable of acting on multiple conformations explicitly. Jaguar pKa is essentially a complex computational workflow incorporating research and technologies from the fields of cheminformatics, molecular mechanics, quantum mechanics, and implicit solvation models. The workflow also makes use of automatically applied empirical corrections which account for the systematic errors resulting from the neglect of explicit solvent interactions in the algorithm's implicit solvent model. Applications of our program to large, flexible organic molecules representing several classes of functional groups are shown, with a particular emphasis in illustrations laid on drug-like molecules. It is demonstrated that a combination of aggressive conformational search and an explicit consideration of multiple conformations nearly eliminates the dependence of results on the initially chosen conformation. In certain cases this leads to unprecedented accuracy, which is sufficient for distinguishing stereoisomers that have slightly different pKa values. An application of Jaguar pKa to proton sponges, the pKa of which are strongly influenced by steric effects, showcases the advantages that pKa predictors based on quantum mechanical calculations have over similar empirical programs.

Inhibition of acetyl-CoA carboxylase suppresses fatty acid synthesis and tumor growth of non-small-cell lung cancer in preclinical models.

Continuous de novo fatty acid synthesis is a common feature of cancer that is required to meet the biosynthetic demands of a growing tumor. This process is controlled by the rate-limiting enzyme acetyl-CoA carboxylase (ACC), an attractive but traditionally intractable drug target. Here we provide genetic and pharmacological evidence that in preclinical models ACC is required to maintain the de novo fatty acid synthesis needed for growth and viability of non-small-cell lung cancer (NSCLC) cells. We describe the ability of ND-646-an allosteric inhibitor of the ACC enzymes ACC1 and ACC2 that prevents ACC subunit dimerization-to suppress fatty acid synthesis in vitro and in vivo. Chronic ND-646 treatment of xenograft and genetically engineered mouse models of NSCLC inhibited tumor growth. When administered as a single agent or in combination with the standard-of-care drug carboplatin, ND-646 markedly suppressed lung tumor growth in the Kras;Trp53-/- (also known as KRAS p53) and Kras;Stk11-/- (also known as KRAS Lkb1) mouse models of NSCLC. These findings demonstrate that ACC mediates a metabolic liability of NSCLC and that ACC inhibition by ND-646 is detrimental to NSCLC growth, supporting further examination of the use of ACC inhibitors in oncology.

WScore: A Flexible and Accurate Treatment of Explicit Water Molecules in Ligand-Receptor Docking.

We have developed a new methodology for protein-ligand docking and scoring, WScore, incorporating a flexible description of explicit water molecules. The locations and thermodynamics of the waters are derived from a WaterMap molecular dynamics simulation. The water structure is employed to provide an atomic level description of ligand and protein desolvation. WScore also contains a detailed model for localized ligand and protein strain energy and integrates an MM-GBSA scoring component with these terms to assess delocalized strain of the complex. Ensemble docking is used to take into account induced fit effects on the receptor conformation, and protein reorganization free energies are assigned via fitting to experimental data. The performance of the method is evaluated for pose prediction, rank ordering of self-docked complexes, and enrichment in virtual screening, using a large data set of PDB complexes and compared with the Glide SP and Glide XP models; significant improvements are obtained.

Acetyl-CoA carboxylase inhibition by ND-630 reduces hepatic steatosis, improves insulin sensitivity, and modulates dyslipidemia in rats.

Simultaneous inhibition of the acetyl-CoA carboxylase (ACC) isozymes ACC1 and ACC2 results in concomitant inhibition of fatty acid synthesis and stimulation of fatty acid oxidation and may favorably affect the morbidity and mortality associated with obesity, diabetes, and fatty liver disease. Using structure-based drug design, we have identified a series of potent allosteric protein-protein interaction inhibitors, exemplified by ND-630, that interact within the ACC phosphopeptide acceptor and dimerization site to prevent dimerization and inhibit the enzymatic activity of both ACC isozymes, reduce fatty acid synthesis and stimulate fatty acid oxidation in cultured cells and in animals, and exhibit favorable drug-like properties. When administered chronically to rats with diet-induced obesity, ND-630 reduces hepatic steatosis, improves insulin sensitivity, reduces weight gain without affecting food intake, and favorably affects dyslipidemia. When administered chronically to Zucker diabetic fatty rats, ND-630 reduces hepatic steatosis, improves glucose-stimulated insulin secretion, and reduces hemoglobin A1c (0.9% reduction). Together, these data suggest that ACC inhibition by representatives of this series may be useful in treating a variety of metabolic disorders, including metabolic syndrome, type 2 diabetes mellitus, and fatty liver disease.

Accurate and reliable prediction of relative ligand binding potency in prospective drug discovery by way of a modern free-energy calculation protocol and force field.

Designing tight-binding ligands is a primary objective of small-molecule drug discovery. Over the past few decades, free-energy calculations have benefited from improved force fields and sampling algorithms, as well as the advent of low-cost parallel computing. However, it has proven to be challenging to reliably achieve the level of accuracy that would be needed to guide lead optimization (∼5× in binding affinity) for a wide range of ligands and protein targets. Not surprisingly, widespread commercial application of free-energy simulations has been limited due to the lack of large-scale validation coupled with the technical challenges traditionally associated with running these types of calculations. Here, we report an approach that achieves an unprecedented level of accuracy across a broad range of target classes and ligands, with retrospective results encompassing 200 ligands and a wide variety of chemical perturbations, many of which involve significant changes in ligand chemical structures. In addition, we have applied the method in prospective drug discovery projects and found a significant improvement in the quality of the compounds synthesized that have been predicted to be potent. Compounds predicted to be potent by this approach have a substantial reduction in false positives relative to compounds synthesized on the basis of other computational or medicinal chemistry approaches. Furthermore, the results are consistent with those obtained from our retrospective studies, demonstrating the robustness and broad range of applicability of this approach, which can be used to drive decisions in lead optimization.

MEASUREMENT WITHOUT THEORY, ONCE AGAIN.

Bailey and Collins (2011) argue that Greenwood, Seshadri, and Vandenbroucke's (2005) hypothesis that the baby boom was partly due to a burst of productivity in the household sector is not supported by evidence. This conclusion is based on regression results showing that appliance ownership is negatively correlated with fertility. They also argue that the Amish, who limit the use of modern technology, had a baby boom. First, it is demonstrated that a negative correlation between appliance ownership and fertility can arise naturally in Greenwood, Seshadri, and Vandenbroucke's model. Second, evidence is presented casting doubt on the presumed technology phobia of the Amish.

Docking covalent inhibitors: a parameter free approach to pose prediction and scoring.

Although many popular docking programs include a facility to account for covalent ligands, large-scale systematic docking validation studies of covalent inhibitors have been sparse. In this paper, we present the development and validation of a novel approach for docking and scoring covalent inhibitors, which consists of conventional noncovalent docking, heuristic formation of the covalent attachment point, and structural refinement of the protein-ligand complex. This approach combines the strengths of the docking program Glide and the protein structure modeling program Prime and does not require any parameter fitting for the study of additional covalent reaction types. We first test this method by predicting the native binding geometry of 38 covalently bound complexes. The average RMSD of the predicted poses is 1.52 Å, and 76% of test set inhibitors have an RMSD of less than 2.0 Å. In addition, the apparent affinity score constructed herein is tested on a virtual screening study and the characterization of the SAR properties of two different series of congeneric compounds with satisfactory success.

Crystal structure and pharmacological characterization of a novel N-methyl-D-aspartate (NMDA) receptor antagonist at the GluN1 glycine binding site.

NMDA receptors are ligand-gated ion channels that mediate excitatory neurotransmission in the brain. They are tetrameric complexes composed of glycine-binding GluN1 and GluN3 subunits together with glutamate-binding GluN2 subunits. Subunit-selective antagonists that discriminate between the glycine sites of GluN1 and GluN3 subunits would be valuable pharmacological tools for studies on the function and physiological roles of NMDA receptor subtypes. In a virtual screening for antagonists that exploit differences in the orthosteric binding site of GluN1 and GluN3 subunits, we identified a novel glycine site antagonist, 1-thioxo-1,2-dihydro-[1,2,4]triazolo[4,3-a]quinoxalin-4(5H)-one (TK40). Here, we show by Schild analysis that TK40 is a potent competitive antagonist with Kb values of 21-63 nM at the GluN1 glycine-binding site of the four recombinant GluN1/N2A-D receptors. In addition, TK40 displayed >100-fold selectivity for GluN1/N2 NMDA receptors over GluN3A- and GluN3B-containing NMDA receptors and no appreciable effects at AMPA receptors. Binding experiments on rat brain membranes and the purified GluN1 ligand-binding domain using glycine site GluN1 radioligands further confirmed the competitive interaction and high potency. To delineate the binding mechanism, we have solved the crystal structure of the GluN1 ligand-binding domain in complex with TK40 and show that TK40 binds to the orthosteric binding site of the GluN1 subunit with a binding mode that was also predicted by virtual screening. Furthermore, the structure reveals that the imino acetamido group of TK40 acts as an α-amino acid bioisostere, which could be of importance in bioisosteric replacement strategies for future ligand design.

Structure-based discovery of antagonists for GluN3-containing N-methyl-D-aspartate receptors.

NMDA receptors are ligand-gated ion channels that assemble into tetrameric receptor complexes composed of glycine-binding GluN1 and GluN3 subunits (GluN3A-B) and glutamate-binding GluN2 subunits (GluN2A-D). NMDA receptors can assemble as GluN1/N2 receptors and as GluN3-containing NMDA receptors, which are either glutamate/glycine-activated triheteromeric GluN1/N2/N3 receptors or glycine-activated diheteromeric GluN1/N3 receptors. The glycine-binding GluN1 and GluN3 subunits display strikingly different pharmacological selectivity profiles. However, the pharmacological characterization of GluN3-containing receptors has been hampered by the lack of methods and pharmacological tools to study GluN3 subunit pharmacology in isolation. Here, we have developed a method to study the pharmacology of GluN3 subunits in recombinant diheteromeric GluN1/N3 receptors by mutating the orthosteric ligand-binding pocket in GluN1. This method is suitable for performing compound screening and characterization of structure-activity relationship studies on GluN3 ligands. We have performed a virtual screen of the orthosteric binding site of GluN3A in the search for antagonists with selectivity for GluN3 subunits. In the subsequent pharmacological evaluation of 99 selected compounds, we identified 6-hydroxy-[1,2,5]oxadiazolo[3,4-b]pyrazin-5(4H)-one (TK80) a novel competitive antagonist with preference for the GluN3B subunit. Serendipitously, we also identified [2-hydroxy-5-((4-(pyridin-3-yl)thiazol-2-yl)amino]benzoic acid (TK13) and 4-(2,4-dichlorobenzoyl)-1H-pyrrole-2-carboxylic acid (TK30), two novel non-competitive GluN3 antagonists. These findings demonstrate that structural differences between the orthosteric binding site of GluN3 and GluN1 can be exploited to generate selective ligands.

Docking performance of the glide program as evaluated on the Astex and DUD datasets: a complete set of glide SP results and selected results for a new scoring function integrating WaterMap and glide.

Glide SP mode enrichment results for two preparations of the DUD dataset and native ligand docking RMSDs for two preparations of the Astex dataset are presented. Following a best-practices preparation scheme, an average RMSD of 1.140 Å for native ligand docking with Glide SP is computed. Following the same best-practices preparation scheme for the DUD dataset an average area under the ROC curve (AUC) of 0.80 and average early enrichment via the ROC (0.1 %) metric of 0.12 were observed. 74 and 56 % of the 39 best-practices prepared targets showed AUC over 0.7 and 0.8, respectively. Average AUC was greater than 0.7 for all best-practices protein families demonstrating consistent enrichment performance across a broad range of proteins and ligand chemotypes. In both Astex and DUD datasets, docking performance is significantly improved employing a best-practices preparation scheme over using minimally-prepared structures from the PDB. Enrichment results for WScore, a new scoring function and sampling methodology integrating WaterMap and Glide, are presented for four DUD targets, hivrt, hsp90, cdk2, and fxa. WScore performance in early enrichment is consistently strong and all systems examined show AUC > 0.9 and superior early enrichment to DUD best-practices Glide SP results.

Structure-based identification and neutralization mechanism of tyrosine sulfate mimetics that inhibit HIV-1 entry.

Tyrosine sulfate-mediated interactions play an important role in HIV-1 entry. After engaging the CD4 receptor at the cell surface, the HIV-1 gp120 glycoprotein binds to the CCR5 co-receptor via an interaction that requires two tyrosine sulfates, at positions 10 and 14 in the CCR5-N terminus. Building on previous structure determinations of this interaction, here we report the targeting of these tyrosine sulfate binding sites for drug design through in silico screening of small molecule libraries, identification of lead compounds, and characterization of biological activity. A class of tyrosine sulfate-mimicking small molecules containing a "phenyl sulfonate-linker-aromatic" motif was identified that specifically inhibited binding of gp120 to the CCR5-N terminus as well as to sulfated antibodies that recognize the co-receptor binding region on gp120. The most potent of these compounds bound gp120 with low micromolar affinity and its CD4-induced conformation with K(D)'s as tight as ∼50 nM. Neutralization experiments suggested the targeted site to be conformationally inaccessible prior to CD4 engagement. Primary HIV-1 isolates were weakly neutralized, preincubation with soluble CD4 enhanced neutralization, and engineered isolates with increased dependence on the N terminus of CCR5 or with reduced conformational barriers were neutralized with IC(50) values as low as ∼1 µM. These results reveal the potential of targeting the tyrosine sulfate interactions of HIV-1 and provide insight into how mechanistic barriers, evolved by HIV-1 to evade antibody recognition, also restrict small-molecule-mediated neutralization.

Glutamate receptor agonists: stereochemical aspects.

The neurotransmitter (S)-glutamate [(S)-Glu] is responsible for most of the excitatory neurotransmission in the central nervous system. The effect of (S)-Glu is mediated by both ionotropic and metabotropic receptors. Glutamate receptor agonists are generally α-amino acids with one or more stereogenic centers due to strict requirements in the agonist binding pocket of the activated state of the receptor. By contrast, there are many examples of achiral competitive antagonists. The present review addresses how stereochemistry affects the activity of glutamate receptor ligands. The review focuses mainly on agonists and discusses stereochemical and conformational considerations as well as biostructural knowledge of the agonist binding pockets, which is useful in the design of glutamate receptor agonists. Examples are chosen to demonstrate how stereochemistry not only determines how the agonist binding pocket is filled, but also how it affects the conformational space of the ligand and in this way restricts the recognition of various glutamate receptors, ultimately leading to selectivity.