Discovery of Highly Selective Inhibitors of Calmodulin-Dependent Kinases That Restore Insulin Sensitivity in the Diet-Induced Obesity in Vivo Mouse Model.

Polymorphisms in the region of the calmodulin-dependent kinase isoform D (CaMK1D) gene are associated with increased incidence of diabetes, with the most common polymorphism resulting in increased recognition by transcription factors and increased protein expression. While reducing CaMK1D expression has a potentially beneficial effect on glucose processing in human hepatocytes, there are no known selective inhibitors of CaMK1 kinases that can be used to validate or translate these findings. Here we describe the development of a series of potent, selective, and drug-like CaMK1 inhibitors that are able to provide significant free target cover in mouse models and are therefore useful as in vivo tool compounds. Our results show that a lead compound from this series improves insulin sensitivity and glucose control in the diet-induced obesity mouse model after both acute and chronic administration, providing the first in vivo validation of CaMK1D as a target for diabetes therapeutics.

Novel Antitubercular 6-Dialkylaminopyrimidine Carboxamides from Phenotypic Whole-Cell High Throughput Screening of a SoftFocus Library: Structure-Activity Relationship and Target Identification Studies.

A BioFocus DPI SoftFocus library of ∼35 000 compounds was screened against Mycobacterium tuberculosis (Mtb) in order to identify novel hits with antitubercular activity. The hits were evaluated in biology triage assays to exclude compounds suggested to function via frequently encountered promiscuous mechanisms of action including inhibition of the QcrB subunit of the cytochrome bc1 complex, disruption of cell-wall homeostasis, and DNA damage. Among the hits that passed this screening cascade, a 6-dialkylaminopyrimidine carboxamide series was prioritized for hit to lead optimization. Compounds from this series were active against clinical Mtb strains, while no cross-resistance to conventional antituberculosis drugs was observed. This suggested a novel mechanism of action, which was confirmed by chemoproteomic analysis leading to the identification of BCG_3193 and BCG_3827 as putative targets of the series with unknown function. Initial structure-activity relationship studies have resulted in compounds with moderate to potent antitubercular activity and improved physicochemical properties.

Aminopyrazolo[1,5-a]pyrimidines as potential inhibitors of Mycobacterium tuberculosis: Structure activity relationships and ADME characterization.

Whole-cell high-throughput screening of a diverse SoftFocus library against Mycobacterium tuberculosis (Mtb) generated a novel aminopyrazolo[1,5-a]pyrimidine hit series. The synthesis and structure activity relationship studies identified compounds with potent antimycobacterial activity. The SAR of over 140 compounds shows that the 2-pyridylmethylamine moiety at the C-7 position of the pyrazolopyrimidine scaffold was important for Mtb activity, whereas the C-3 position offered a higher degree of flexibility. The series was also profiled for in vitro cytotoxicity and microsomal metabolic stability as well as physicochemical properties. Consequently liabilities to be addressed in a future lead optimization campaign have been identified.

Strategies for small molecule library design.

Compilation of an appropriate set of compounds is essential for the success of a small molecule screen. When very little is known about the target and when no or few ligands have been identified, the screening file is often made as diverse as possible. When structural information on the target or target family is available or ligands of the target are known, it is more efficient to apply a ligand- or target-focused bias, so as to predominantly screen compounds that can be expected to modulate the target. One way to achieve this is to select subsets of existing collections; another is to specifically design and synthesize libraries focused on a particular target, target family or mechanism of action. Despite the number of success stories, designing such libraries is still challenging and requires specialized knowledge, especially in emerging target areas such as protein-protein interactions (PPI), epigenetics and the ubiquitin proteasome pathway. BioFocus has successfully produced so-called SoftFocus(®) libraries for many years, evolving their targets from kinases to GPCRs and ion channels to difficult targets in the epigenetics and PPI fields. This article outlines several of the principles applied to SoftFocus library design, showcasing successes achieved by BioFocus' clients. In addition, screening results for a comprehensive set of BioFocus' kinase libraries against 20 kinase targets are used to demonstrate the power of the SoftFocus approach in delivering both selective and less-selective compounds and libraries against these targets. Trademarks: BioFocus(®), SoftFocus(®), HDRA™, FieldFocus™, Thematic Analysis™, ThemePair™ and ThemePair Fragment™ are trademarks of Galapagos NV and/or its affiliates.

Mitogen-activated protein kinase-activated protein kinase 2 (MAPKAP-K2) as an antiinflammatory target: discovery and in vivo activity of selective pyrazolo[1,5-a]pyrimidine inhibitors using a focused library and structure-based optimization approach.

A novel class of mitogen-activated protein kinase-activated protein kinase 2 (MAPKAP-K2) inhibitors was discovered through screening a kinase-focused library. A homology model of MAPKAP-K2 was generated and used to guide the initial SAR studies and to rationalize the observed selectivity over CDK2. An X-ray crystal structure of a compound from the active series bound to crystalline MAPKAP-K2 confirmed the predicted binding mode. This has enabled the discovery of a series of pyrazolo[1,5-a]pyrimidine derivatives showing good in vitro cellular potency as anti-TNF-α agents and in vivo efficacy in a mouse model of endotoxin shock.

The design and application of target-focused compound libraries.

Target-focused compound libraries are collections of compounds which are designed to interact with an individual protein target or, frequently, a family of related targets (such as kinases, voltage-gated ion channels, serine/cysteine proteases). They are used for screening against therapeutic targets in order to find hit compounds that might be further developed into drugs. The design of such libraries generally utilizes structural information about the target or family of interest. In the absence of such structural information, a chemogenomic model that incorporates sequence and mutagenesis data to predict the properties of the binding site can be employed. A third option, usually pursued when no structural data are available, utilizes knowledge of the ligands of the target from which focused libraries can be developed via scaffold hopping. Consequently, the methods used for the design of target-focused libraries vary according to the quantity and quality of structural or ligand data that is available for each target family. This article describes examples of each of these design approaches and illustrates them with case studies, which highlight some of the issues and successes observed when screening target-focused libraries.

How large does a compound screening collection need to be?

Increasingly, chemical libraries are being produced which are focused on a biological target or group of related targets, rather than simply being constructed in a combinatorial fashion. A screening collection compiled from such libraries will contain multiple analogues of a number of discrete series of compounds. The question arises as to how many analogues are necessary to represent each series in order to ensure that an active series will be identified. Based on a simple probabilistic argument and supported by in-house screening data, guidelines are given for the number of compounds necessary to achieve a "hit", or series of hits, at various levels of certainty. Obtaining more than one hit from the same series is useful since this gives early acquisition of SAR (structure-activity relationship) and confirms a hit is not a singleton. We show that screening collections composed of only small numbers of analogues of each series are sub-optimal for SAR acquisition. Based on these studies, we recommend a minimum series size of about 200 compounds. This gives a high probability of confirmatory SAR (i.e. at least two hits from the same series). More substantial early SAR (at least 5 hits from the same series) can be gained by using series of about 650 compounds each. With this level of information being generated, more accurate assessment of the likely success of the series in hit-to-lead and later stage development becomes possible.

Chemogenomics: structuring the drug discovery process to gene families.

In the post-genomic era, if all proteins in a gene family can putatively be identified, how can drug discovery effectively tackle so many novel targets that might lack structural and small-molecule inhibitory data? In response, chemogenomics, a new approach that guides drug discovery based on gene families, has been developed. By integrating all information available within a protein family (sequence, SAR data, protein structure), chemogenomics can efficiently enable cross-SAR exploitation, directed compound selection and early identification of optimum selectivity panel members. This review examines recent developments in chemogenomics technologies and illustrates their predictive capabilities with successful examples from two of the major protein families: protein kinases and G-protein-coupled receptors.

Bringing kinases into focus: efficient drug design through the use of chemogenomic toolkits.

The study of protein target families, as opposed to single targets, has become a very powerful tool in chemogenomics-led drug discovery. By integrating comprehensive chemoinformatics and bioinformatics databases with customised analytical tools, a 'Toolkit' approach for the target family is possible, thus allowing predictions of the ligand class, affinity, selectivity and likely off-target issues to be made for the guidance of the medicinal chemist. In this review, we highlight the development and application of the Toolkit approach to the protein kinase superfamily, drawing on examples from lead optimisation studies and the design of focused libraries for lead discovery.