Development of Orally Efficacious Allosteric Inhibitors of TNFα via Fragment-Based Drug Design.

Tumor necrosis factor α (TNFα) is a soluble cytokine that is directly involved in systemic inflammation through the regulation of the intracellular NF-κB and MAPK signaling pathways. The development of biologic drugs that inhibit TNFα has led to improved clinical outcomes for patients with rheumatoid arthritis and other chronic autoimmune diseases; however, TNFα has proven to be difficult to drug with small molecules. Herein, we present a two-phase, fragment-based drug discovery (FBDD) effort in which we first identified isoquinoline fragments that disrupt TNFα ligand-receptor binding through an allosteric desymmetrization mechanism as observed in high-resolution crystal structures.

Development of a high-content screening assay panel to accelerate mechanism of action studies for oncology research.

Efficient elucidation of the biological mechanism of action of novel compounds remains a major bottleneck in the drug discovery process. To address this need in the area of oncology, we report the development of a multiparametric high-content screening assay panel at the level of single cells to dramatically accelerate understanding the mechanism of action of cell growth-inhibiting compounds on a large scale. Our approach is based on measuring 10 established end points associated with mitochondrial apoptosis, cell cycle disruption, DNA damage, and cellular morphological changes in the same experiment, across three multiparametric assays.

Identification and preliminary characterization of a potent, safe, and orally efficacious inhibitor of acyl-CoA:diacylglycerol acyltransferase 1.

A high-throughput screen against human DGAT-1 led to the identification of a core structure that was subsequently optimized to afford the potent, selective, and orally bioavailable compound 14. Oral administration at doses ≥0.03 mg/kg significantly reduced postprandial triglycerides in mice following an oral lipid challenge.

Fragment-based lead discovery: challenges and opportunities.

Fragment-based lead discovery has undergone remarkable changes over the last 15 years. During this time, the pharmaceutical industry has changed dramatically as well, and continued evolution of the industry is assured. These changes present many challenges but also several opportunities for executing fragment-based drug design.

Identification and characterization of mGlu3 ligands using a high throughput FLIPR assay for detection of agonists, antagonists, and allosteric modulators.

When targeting G-protein coupled receptors (GPCRs) in early stage drug discovery, or for novel targets, the type of ligand most likely to produce the desired therapeutic effect may be unknown. Therefore, it can be desirable to identify potential lead compounds from multiple categories: agonists, antagonists, and allosteric modulators. In this study, we developed a triple addition calcium flux assay using FLIPR Tetra to identify multiple ligand classes for the metabotropic glutamate receptor 3 (mGlu3), using a cell line stably co-expressing the human G-protein-coupled mGlu3 receptor, a promiscuous G-protein (G(α16)), and rat Glast, a glutamate transporter.

Navigating the kinome.

Although it is increasingly being recognized that drug-target interaction networks can be powerful tools for the interrogation of systems biology and the rational design of multitargeted drugs, there is no generalized, statistically validated approach to harmonizing sequence-dependent and pharmacology-dependent networks. Here we demonstrate the creation of a comprehensive kinome interaction network based not only on sequence comparisons but also on multiple pharmacology parameters derived from activity profiling data. The framework described for statistical interpretation of these network connections also enables rigorous investigation of chemotype-specific interaction networks, which is critical for multitargeted drug design.

A unified, probabilistic framework for structure- and ligand-based virtual screening.

We present a probabilistic framework for interpreting structure-based virtual screening that returns a quantitative likelihood of observing bioactivity and can be quantitatively combined with ligand-based screening methods to yield a cumulative prediction that consistently outperforms any single screening metric. The approach has been developed and validated on more than 30 different protein targets. Transforming structure-based in silico screening results into robust probabilities of activity enables the general fusion of multiple structure- and ligand-based approaches and returns a quantitative expectation of success that can be used to prioritize (or deprioritize) further discovery activities.

Discovery and characterization of non-ATP site inhibitors of the mitogen activated protein (MAP) kinases.

Inhibition of protein kinases has validated therapeutic utility for cancer, with at least seven kinase inhibitor drugs on the market. Protein kinase inhibition also has significant potential for a variety of other diseases, including diabetes, pain, cognition, and chronic inflammatory and immunologic diseases. However, as the vast majority of current approaches to kinase inhibition target the highly conserved ATP-binding site, the use of kinase inhibitors in treating nononcology diseases may require great selectivity for the target kinase.

Discovery of a potent and selective Bcl-2 inhibitor using SAR by NMR.

The Bcl-2 family of proteins plays a major role in the regulation of apoptosis, or programmed cell death. Overexpression of the anti-apoptotic members of this family (Bcl-2, Bcl-x(L), and Mcl-1) can render cancer cells resistant to chemotherapeutic agents and therefore these proteins are important targets for the development of new anti-cancer agents. Here we describe the discovery of a potent, highly selective, Bcl-2 inhibitor using SAR by NMR and structure-based drug design which could serve as a starting point for the development of a Bcl-2 selective anti-cancer agent.

Labeled Ligand Displacement: Extending NMR-Based Screening of Protein Targets.

NMR spectroscopy has enjoyed widespread success as a method for screening protein targets, especially in the area of fragment-based drug discovery. However, current methods for NMR-based screening all suffer certain limitations. Two-dimensional methods like "SAR by NMR" require isotopically labeled protein and are limited to proteins less than about 50 kDa.

Rational approaches to targeted polypharmacology: creating and navigating protein-ligand interaction networks.

Many successful drugs bind to and modulate multiple targets in vivo. Successfully navigating protein-ligand polypharmacology will be a crucial and increasingly utilized component of pharmaceutical research. As publicly available databases of ligand activity values continue to grow in size and quality, infrastructure is needed to enable scientists to create and interact with these networks to fuel hypothesis-driven science.

Biochemical and biophysical characterization of unique switch pocket inhibitors of p38α.

Herein we describe the identification and characterization of a class of molecules that are believed to extend into a region of p38 known as the 'switch pocket'. Although these molecules lack a canonical hinge binding motif, they show K(i) values as low as 100 nM against p38. We show that molecules that interact with this region of the protein demonstrate different binding kinetics than a canonical ATP mimetic, as well as a wide range of kinome profiles.

Healthy skepticism: assessing realistic model performance.

Although the development of computational models to aid drug discovery has become an integral part of pharmaceutical research, the application of these models often fails to produce the expected impact on productivity. One reason for this may be that the expected performance of many models is simply not supported by the underlying data, because of often neglected effects of assay and prediction errors on the reliability of the predicted outcome. Another significant challenge to realizing the full potential of computational models is their integration into prospective medicinal chemistry campaigns.

Structural characterization of a soluble amyloid beta-peptide oligomer.

Alzheimer's disease (AD) is a neurodegenerative disorder that is linked to the presence of amyloid beta-peptides that can form insoluble fibrils or soluble oligomeric assemblies. Soluble forms are present in the brains and tissues of Alzheimer's patients, and their presence correlates with disease progression. Long-lived soluble forms can be generated in vitro by using small amounts of aliphatic hydrocarbon chains of detergents or fatty acids in preparations of amyloid beta-peptides.

Kinase-targeted libraries: the design and synthesis of novel, potent, and selective kinase inhibitors.

Protein kinases continue to hold tremendous promise for therapeutic intervention, and the search for novel, safe and efficacious kinase inhibitors has intensified over the past decade. Given that most kinases are readily inhibited by organic small molecules and that a wealth of structural data exists on kinase-inhibitor complexes, there has been almost universal success in the design and identification of potent kinase inhibitors. The issues of non-selectivity and congested IP space, however, present formidable challenges for the successful clinical development of these compounds.

Molecular determinants of species-specific activation or blockade of TRPA1 channels.

TRPA1 is an excitatory, nonselective cation channel implicated in somatosensory function, pain, and neurogenic inflammation. Through covalent modification of cysteine and lysine residues, TRPA1 can be activated by electrophilic compounds, including active ingredients of pungent natural products (e.g.

Application of belief theory to similarity data fusion for use in analog searching and lead hopping.

A wide variety of computational algorithms have been developed that strive to capture the chemical similarity between two compounds for use in virtual screening and lead discovery. One limitation of such approaches is that, while a returned similarity value reflects the perceived degree of relatedness between any two compounds, there is no direct correlation between this value and the expectation or confidence that any two molecules will in fact be equally active. A lack of a common framework for interpretation of similarity measures also confounds the reliable fusion of information from different algorithms.

Scaffold oriented synthesis. Part 2: Design, synthesis and biological evaluation of pyrimido-diazepines as receptor tyrosine kinase inhibitors.

We report the discovery of the pyrimido-diazepine scaffolds as novel adenine mimics. Structure-based design led to the discovery of analogs with potent inhibitory activity against receptor tyrosine kinases, such as KDR, Flt3 and c-Kit. Compound 14 exhibited low nanomolar KDR enzymatic and cellular potencies (IC(50)=9 and 52 nM, respectively).

Statistical analysis of the effects of common chemical substituents on ligand potency.

The results of a statistical analysis of more than 84,000 compounds from lead optimization programs against 30 different protein targets is presented, with a focus on the effects that different chemical substituents have on compound potency. It is observed that the potency changes induced by most chemical groups follows a nearly normal distribution centered near zero (i.e.

Toxicological evaluation of thiol-reactive compounds identified using a la assay to detect reactive molecules by nuclear magnetic resonance.

We have recently reported on the development of a La assay to detect reactive molecules by nuclear magnetic resonance (ALARM NMR) to detect reactive false positive hits from high-throughput screening, in which we observed a surprisingly large number of compounds that can oxidize or form covalent adducts with protein thiols groups. In the vast majority of these cases, the covalent interactions are largely nonspecific (e.g.

Solution structure and calcium-binding properties of EF-hands 3 and 4 of calsenilin.

Calsenilin is a member of the recoverin branch of the EF-hand superfamily that is reported to interact with presenilins, regulate prodynorphin gene expression, modulate voltage-gated Kv4 potassium channel function, and bind to neurotoxins. Calsenilin is a Ca+2-binding protein and plays an important role in calcium signaling. Despite its importance in numerous neurological functions, the structure of this protein has not been reported.

Discovery and design of novel HSP90 inhibitors using multiple fragment-based design strategies.

The molecular chaperone HSP90 has been shown to facilitate cancer cell survival by stabilizing key proteins responsible for a malignant phenotype. We report here the results of parallel fragment-based drug design approaches in the design of novel HSP90 inhibitors. Initial aminopyrimidine leads were elaborated using high-throughput organic synthesis to yield nanomolar inhibitors of the enzyme.

From bacterial genomes to novel antibacterial agents: discovery, characterization, and antibacterial activity of compounds that bind to HI0065 (YjeE) from Haemophilus influenzae.

As part of a fully integrated and comprehensive strategy to discover novel antibacterial agents, NMR- and mass spectrometry-based affinity selection screens were performed to identify compounds that bind to protein targets uniquely found in bacteria and encoded by genes essential for microbial viability. A biphenyl acid lead series emerged from an NMR-based screen with the Haemophilus influenzae protein HI0065, a member of a family of probable ATP-binding proteins found exclusively in eubacteria. The structure-activity relationships developed around the NMR-derived biphenyl acid lead were consistent with on-target antibacterial activity as the Staphylococcus aureus antibacterial activity of the series correlated extremely well with binding affinity to HI0065, while the correlation of binding affinity with B-cell cytotoxicity was relatively poor.