D3R grand challenge 4: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies.

The Drug Design Data Resource (D3R) aims to identify best practice methods for computer aided drug design through blinded ligand pose prediction and affinity challenges. Herein, we report on the results of Grand Challenge 4 (GC4). GC4 focused on proteins beta secretase 1 and Cathepsin S, and was run in an analogous manner to prior challenges. In Stage 1, participant ability to predict the pose and affinity of BACE1 ligands were assessed. Following the completion of Stage 1, all BACE1 co-crystal structures were released, and Stage 2 tested affinity rankings with co-crystal structures. We provide an analysis of the results and discuss insights into determined best practice methods.

D3R Grand Challenge 3: blind prediction of protein-ligand poses and affinity rankings.

The Drug Design Data Resource aims to test and advance the state of the art in protein-ligand modeling by holding community-wide blinded, prediction challenges. Here, we report on our third major round, Grand Challenge 3 (GC3). Held 2017-2018, GC3 centered on the protein Cathepsin S and the kinases VEGFR2, JAK2, p38-α, TIE2, and ABL1, and included both pose-prediction and affinity-ranking components. GC3 was structured much like the prior challenges GC2015 and GC2. First, Stage 1 tested pose prediction and affinity ranking methods; then all available crystal structures were released, and Stage 2 tested only affinity rankings, now in the context of the available structures. Unique to GC3 was the addition of a Stage 1b self-docking subchallenge, in which the protein coordinates from all of the cocrystal structures used in the cross-docking challenge were released, and participants were asked to predict the pose of CatS ligands using these newly released structures. We provide an overview of the outcomes and discuss insights into trends and best-practices.

Determination of a Focused Mini Kinase Panel for Early Identification of Selective Kinase Inhibitors.

We analyzed an extensive data set of 3000 Janssen kinase inhibitors (spanning some 40 therapeutic projects) profiled at 414 kinases in the DiscoverX KINOME scan to better understand the necessity of using such a full kinase panel versus simply profiling one's compound at a much smaller number of kinases, or mini kinase panel (MKP), to assess its selectivity. To this end, we generated a series of MKPs over a range of sizes and of varying kinase membership using Monte Carlo simulations. By defining the kinase hit index (KHI), we quantified a compound's selectivity based on the number of kinases it hits. We find that certain combinations (rather than a random selection) of kinases can result in a much lower average error. Indeed, we identified a focused MKP with a 45.1% improvement in the average error (compared to random) that yields an overall correlation of R2 = 0.786-0.826 for the KHI compared to the full kinase panel value. Unlike using a full kinase panel, which is both time and cost restrictive, a focused MKP is amenable to the triaging of all early stage compounds. In this way, promiscuous compounds are filtered out early on, leaving the most selective compounds for lead optimization.

Discovery of JNJ-64264681: A Potent and Selective Covalent Inhibitor of Bruton's Tyrosine Kinase.

Bruton's tyrosine kinase (BTK) is a Tec family kinase that plays an essential role in B-cell receptor (BCR) signaling as well as Fcγ receptor signaling in leukocytes. Pharmacological inhibition of BTK has been shown to be effective in treating hematological malignancies and is hypothesized to provide an effective strategy for the treatment of autoimmune diseases such as rheumatoid arthritis and systemic lupus erythematosus. We report the discovery and preclinical properties of JNJ-64264681 (13), a covalent, irreversible BTK inhibitor with potent whole blood activity and exceptional kinome selectivity. JNJ-64264681 demonstrated excellent oral efficacy in both cancer and autoimmune models with sustained in vivo target coverage amenable to once daily dosing and has advanced into human clinical studies to investigate safety and pharmacokinetics.

Pharmacological characterization of 1-(5-chloro-6-(trifluoromethoxy)-1H-benzoimidazol-2-yl)-1H-pyrazole-4-carboxylic acid (JNJ-42041935), a potent and selective hypoxia-inducible factor prolyl hydroxylase inhibitor.

The hypoxia-inducible factor (HIF) prolyl hydroxylase (PHD) enzymes represent novel targets for the treatment of anemia, ulcerative colitis, and ischemic and metabolic disease inter alia. We have identified a novel small-molecule inhibitor of PHD, 1-(5-chloro-6-(trifluoromethoxy)-1H-benzoimidazol-2-yl)-1H-pyrazole-4-carboxylic acid (JNJ-42041935), through structure-based drug design methods. The pharmacology of JNJ-42041935 was investigated in enzyme, cellular, and whole-animal systems and was compared with other compounds described in the literature as PHD inhibitors. JNJ-42041935, was a potent (pK(I) = 7.3-7.9), 2-oxoglutarate competitive, reversible, and selective inhibitor of PHD enzymes. In addition, JNJ-42041935 was used to compare the effect of selective inhibition of PHD to intermittent, high doses (50 µg/kg i.p.) of an exogenous erythropoietin receptor agonist in an inflammation-induced anemia model in rats. JNJ-42041935 (100 µmol/kg, once a day for 14 days) was effective in reversing inflammation-induced anemia, whereas erythropoietin had no effect. The results demonstrate that JNJ-42041935 is a new pharmacological tool, which can be used to investigate PHD inhibition and demonstrate that PHD inhibitors offer great promise for the treatment of inflammation-induced anemia.

Discovery of a Potent and Selective Covalent Inhibitor of Bruton's Tyrosine Kinase with Oral Anti-Inflammatory Activity.

Bruton's tyrosine kinase (BTK) is a cytoplasmic tyrosine kinase that plays a critical role in the activation of B cells, macrophages, and osteoclasts. Given the key role of these cell types in the pathology of autoimmune disorders, BTK inhibitors have the potential to improve treatment outcomes in multiple diseases. Herein, we report the discovery and characterization of a novel potent and selective covalent 4-oxo-4,5-dihydro-3H-1-thia-3,5,8-triazaacenaphthylene-2-carboxamide BTK inhibitor chemotype. Compound 27 irreversibly inhibits BTK by targeting a noncatalytic cysteine residue (Cys481) for covalent bond formation. Compound 27 is characterized by selectivity for BTK, potent in vivo BTK occupancy that is sustained after it is cleared from systemic circulation, and dose-dependent efficacy at reducing joint inflammation in a rat collagen-induced arthritis model.

Diazinones as P2 replacements for pyrazole-based cathepsin S inhibitors.

A pyridazin-4-one fragment 4 (hCatS IC(50)=170 microM) discovered through Tethering was modeled into cathepsin S and predicted to overlap in S2 with the tetrahydropyridinepyrazole core of a previously disclosed series of CatS inhibitors. This fragment served as a template to design pyridazin-3-one 12 (hCatS IC(50)=430 nM), which also incorporates P3 and P5 binding elements. A crystal structure of 12 bound to Cys25Ser CatS led to the synthesis of the potent diazinone isomers 22 (hCatS IC(50)=60 nM) and 27 (hCatS IC(50)=40 nM).

Pyrazole-based cathepsin S inhibitors with arylalkynes as P1 binding elements.

A crystal structure of 1 bound to a Cys25Ser mutant of cathepsin S helped to elucidate the binding mode of a previously disclosed series of pyrazole-based CatS inhibitors and facilitated the design of a new class of arylalkyne analogs. Optimization of the alkyne and tetrahydropyridine portions of the pharmacophore provided potent CatS inhibitors (IC50=40-300 nM), and an X-ray structure of 32 revealed that the arylalkyne moiety binds in the S1 pocket of the enzyme.

Beyond Traditional Structure-Based Drug Design: The Role of Iron Complexation, Strain, and Water in the Binding of Inhibitors for Hypoxia-Inducible Factor Prolyl Hydroxylase 2.

A combination of structure-based drug design and medicinal chemistry efforts led us from benzimidazole-2-carboxamide with modestly active hypoxia-inducible factor prolyl hydroxylase 2 inhibition to certain benzimidazole-2-pyrazole carboxylic acids that were more potent as well as orally efficacious stimulators of erythropoietin secretion in our in vivo mouse model. To better understand the structure-activity relationship, it was necessary to account for (i) the complexation of the ligand with the active site Fe2+, (ii) the strain incurred by the ligand upon binding, and (iii) certain key water interactions identified by a crystal structure analysis. With this more complete computational model, we arrived at an overarching paradigm that accounted for the potency differences between benzimidazole-2-carboxamide and benzimidazole-2-pyrazole carboxylic acid enzyme inhibitors. Moreover, the computational paradigm allowed us to anticipate that the bioisostere replacement strategy (amide → pyrazole), which had shown success in the benzimidazole series, was not generally applicable to other series. This illustrates that to fully reconcile the important ligand-active site interactions for certain targets, one often needs to move beyond traditional structure-based drug design (such as crystallographic analysis, docking, etc.) and appeal to a higher level of computational theory.

Discovery, Optimization, and Evaluation of Potent and Highly Selective PI3Kγ-PI3Kδ Dual Inhibitors.

An electronic density model was developed and used to identify a novel pyrrolotriazinone replacement for a quinazolinone, a commonly used moiety to impart selectivity in inhibitors for PI3Kγ and PI3Kδ. Guided by molecular docking, this new specificity piece was then linked to the hinge-binding region of the inhibitor using a novel cyclic moiety. Further structure-activity relationship optimization around the hinge region led to the discovery of candidate 26, a highly potent and selective PI3Kγ-PI3Kδ dual inhibitor with favorable drug metabolism and pharmacokinetic properties in preclinical species.

Ligand binding efficiency: trends, physical basis, and implications.

Ligand efficiency (i.e., potency/size) has emerged as an important metric in drug discovery. In general, smaller, more efficient ligands are believed to have improved prospects for good drug properties (e.g., bioavailability). Our analysis of thousands of ligands across a variety of targets shows that ligand efficiency is dependent on ligand size with smaller ligands having greater efficiencies, on average, than larger ligands. We propose two primary causes for this size dependence: the inevitable reduction in the quality of fit between ligand and receptor as the ligand becomes larger and more complex and the reduction in accessible ligand surface area on a per atom basis as size increases. These results have far-ranging implications for analysis of high-throughput screening hits, fragment-based approaches to drug discovery, and even computational models of potency.

Dual binding site inhibitors of B-RAF kinase.

Computer aided modeling guided the design of a series of diarylimidazole compounds (11-22) intended to interact with both the ATP and adjacent allosteric binding domains of B-RAF kinase. Their ability to inhibit the function of B-RAF kinase and intracellular ERK1/2 phosphorylation were evaluated.

Lead identification of acetylcholinesterase inhibitors-histamine H3 receptor antagonists from molecular modeling.

Currently, the only clinically effective treatment for Alzheimer's disease (AD) is the use of acetylcholinesterase (AChE) inhibitors. These inhibitors have limited efficacy in that they only treat the symptoms and not the disease itself. Additionally, they often have unpleasant side effects. Here we consider the viability of a single molecule having the actions of both an AChE inhibitor and histamine H(3) receptor antagonist. Both histamine H(3) receptor antagonists and AChE inhibitors improve and augment cholinergic neurotransmission in the cortex. However, whereas an AChE inhibitor will impart its effect everywhere, a histamine H(3) antagonist will raise acetylcholine levels mostly in the brain as its mode of action will primarily be on the central nervous system. Therefore, the combination of both activities in a single molecule could be advantageous. Indeed, studies suggest an appropriate dual-acting compound may offer the desired therapeutic effect with fewer unpleasant side effects [CNS Drugs2004, 18, 827]. Further, recent studies(2) indicate the peripheral anionic site (PAS) of AChE interacts with the beta-amyloid (betaA) peptide. Consequently, a molecule capable of disrupting this interaction may have a significant impact on the production of or the aggregation of betaA. This may result in slowing down the progression of the disease rather than only treating the symptoms as current therapies do. Here, we detail how the use of the available crystal structure information, pharmacophore modeling and docking (automated, manual, classical, and QM/MM) lead to the identification of an AChE inhibitor-histamine H(3) receptor antagonist. Further, based on our models we speculate that this dual-acting compound may interact with the PAS. Such a dual-acting compound may be able to affect the pathology of AD in addition to providing symptomatic relief.

Three-dimensional models of histamine H3 receptor antagonist complexes and their pharmacophore.

Molecular modeling was used to analyze the binding mode and activities of histamine H3 receptor antagonists. A model of the H3 receptor was constructed through homology modeling methods based on the crystal structure of bovine rhodopsin. Known H3 antagonists were interactively docked into the putative antagonist binding pocket and the resultant model was subjected to molecular mechanics energy minimization and molecular dynamics simulations which included a continuum model of the lipid bilayer and intra- and extracellular aqueous environments surrounding the transmembrane helices. The transmembrane helices stayed well embedded in the dielectric slab representing the lipid bilayer and the intra- and extracellular loops remain situated in the aqueous solvent region of the model during molecular dynamics simulations of up to 200 ps in duration. A pharmacophore model was calculated by mapping the features common to three active compounds three-dimensionally in space. The 3D pharmacophore model complements our atomistic receptor/ligand modeling. The H3 antagonist pharmacophore consists of two protonation sites (i.e. basic centers) connected by a central aromatic ring or hydrophobic region. These two basic sites can simultaneously interact with Asp 114 (3.32) in helix III and a Glu 206 (5.46) in helix V which are believed to be the key residues that histamine interacts with to stabilize the receptor in the active state. The interaction with Glu 206 is consistent with the enhanced activity resulting from the additional basic site. In addition to these two salt bridging interactions, the central region of these antagonists contains a lipophilic group, usually an aromatic ring, that is found to interact with several nearby hydrophobic side chains. The picture of antagonist binding provided by these models is consistent with earlier pharmacophore models for H3 antagonists with some exceptions.

A Prospective Virtual Screening Study: Enriching Hit Rates and Designing Focus Libraries To Find Inhibitors of PI3Kδ and PI3Kγ.

Here, we report a high-throughput virtual screening (HTVS) study using phosphoinositide 3-kinase (both PI3Kγ and PI3Kδ). Our initial HTVS results of the Janssen corporate database identified small focused libraries with hit rates at 50% inhibition showing a 50-fold increase over those from a HTS (high-throughput screen). Further, applying constraints based on "chemically intuitive" hydrogen bonds and/or positional requirements resulted in a substantial improvement in the hit rates (versus no constraints) and reduced docking time. While we find that docking scoring functions are not capable of providing a reliable relative ranking of a set of compounds, a prioritization of groups of compounds (e.g., low, medium, and high) does emerge, which allows for the chemistry efforts to be quickly focused on the most viable candidates. Thus, this illustrates that it is not always necessary to have a high correlation between a computational score and the experimental data to impact the drug discovery process.

A Web-based chemoinformatics system for drug discovery.

One of the key questions that must be addressed when implementing a chemoinformatics system is whether the tools will be designed for use by the expert user or by the "bench scientist." This decision can impact not only the style of tools that are rolled out, but is also a factor in terms of how these tools are delivered to the end users. The system that we outline here was designed for use by the non-expert user. As such, the tools that we discuss are in many cases simplified versions of some common algorithms used in chemoinformatics. In addition, the focus is on how to distribute these tools using a web-services interface, which greatly simplifies delivering new protocols to the end user.

Benzimidazole-2-pyrazole HIF Prolyl 4-Hydroxylase Inhibitors as Oral Erythropoietin Secretagogues.

HIF prolyl 4-hydroxylases (PHD) are a family of enzymes that mediate key physiological responses to hypoxia by modulating the levels of hypoxia inducible factor 1-α (HIF1α). Certain benzimidazole-2-pyrazole carboxylates were discovered to be PHD2 inhibitors using ligand- and structure-based methods and found to be potent, orally efficacious stimulators of erythropoietin secretion in vivo.

Ligand efficiency and fragment-based drug discovery.

The use of fragment-based drug discovery (FBDD) has increased in recent years since it is more likely to produce a better optimized compound of lower molecular weight. Ligand efficiency (LE) has become important for assessing fragments, HTS hits, and resulting optimized ligands. LE is useful for comparing ligands of equal molecular weight, but is ineffective for comparisons of ligands of differing molecular weight. LE has a strong dependence on molecular size, which has led us to develop a size-independent efficiency score termed fit quality. Evaluating FBDD examples from the literature using LE and fit quality, we find that, in general, the LEs of starting fragments are greater than those of larger, more elaborated, structures. Fit quality scores, however, tend to improve upon optimization of the fragments.

Identification of a potent, selective, and orally active leukotriene a4 hydrolase inhibitor with anti-inflammatory activity.

LTA 4H is a ubiquitously distributed 69 kDa zinc-containing cytosolic enzyme with both hydrolase and aminopeptidase activity. As a hydrolase, LTA 4H stereospecifically catalyzes the transformation of the unstable epoxide LTA 4 to the diol LTB 4, a potent chemoattractant and activator of neutrophils and a chemoattractant of eosinophils, macrophages, mast cells, and T cells. Inhibiting the formation of LTB 4 is expected to be beneficial in the treatment of inflammatory diseases such as inflammatory bowel disease (IBD), asthma, and atherosclerosis. We developed a pharmacophore model using a known inhibitor manually docked into the active site of LTA 4H to identify a subset of compounds for screening. From this work we identified a series of benzoxazole, benzthiazole, and benzimidazole inhibitors. SAR studies resulted in the identification of several potent inhibitors with an appropriate cross-reactivity profile and excellent PK/PD properties. Our efforts focused on further profiling JNJ 27265732, which showed encouraging efficacy in a disease model relevant to IBD.

The role of molecular size in ligand efficiency.

Ligand efficiency is a simple metric for assessing whether a ligand derives its potency from optimal fit with the protein target or simply by virtue of making many contacts. Comparison of protein-ligand binding affinities for over 8000 ligands with 28 protein targets shows conclusively that the average ligand binding affinities are not linear with molecular size. It is therefore important to scale ligand efficiencies by the size of the ligand, particularly where small ligands (e.g., fragments) are involved. We propose a simple 'fit quality' metric that removes this dependence.