Progress towards a public chemogenomic set for protein kinases and a call for contributions.

Protein kinases are highly tractable targets for drug discovery. However, the biological function and therapeutic potential of the majority of the 500+ human protein kinases remains unknown. We have developed physical and virtual collections of small molecule inhibitors, which we call chemogenomic sets, that are designed to inhibit the catalytic function of almost half the human protein kinases. In this manuscript we share our progress towards generation of a comprehensive kinase chemogenomic set (KCGS), release kinome profiling data of a large inhibitor set (Published Kinase Inhibitor Set 2 (PKIS2)), and outline a process through which the community can openly collaborate to create a KCGS that probes the full complement of human protein kinases.

Structure-Based Design of Highly Selective Inhibitors of the CREB Binding Protein Bromodomain.

Chemical probes are required for preclinical target validation to interrogate novel biological targets and pathways. Selective inhibitors of the CREB binding protein (CREBBP)/EP300 bromodomains are required to facilitate the elucidation of biology associated with these important epigenetic targets. Medicinal chemistry optimization that paid particular attention to physiochemical properties delivered chemical probes with desirable potency, selectivity, and permeability attributes. An important feature of the optimization process was the successful application of rational structure-based drug design to address bromodomain selectivity issues (particularly against the structurally related BRD4 protein).

Increasing the Endoplasmic Reticulum Pool of the F508del Allele of the Cystic Fibrosis Transmembrane Conductance Regulator Leads to Greater Folding Correction by Small Molecule Therapeutics.

Small molecules that correct the folding defects and enhance surface localization of the F508del mutation in the Cystic Fibrosis Transmembrane conductance Regulator (CFTR) comprise an important therapeutic strategy for cystic fibrosis lung disease. However, compounds that rescue the F508del mutant protein to wild type (WT) levels have not been identified. In this report, we consider obstacles to obtaining robust and therapeutically relevant levels of F508del CFTR. For example, markedly diminished steady state amounts of F508del CFTR compared to WT CFTR are present in recombinant bronchial epithelial cell lines, even when much higher levels of mutant transcript are present. In human primary airway cells, the paucity of Band B F508del is even more pronounced, although F508del and WT mRNA concentrations are comparable. Therefore, to augment levels of "repairable" F508del CFTR and identify small molecules that then correct this pool, we developed compound library screening protocols based on automated protein detection. First, cell-based imaging measurements were used to semi-quantitatively estimate distribution of F508del CFTR by high content analysis of two-dimensional images. We evaluated ~2,000 known bioactive compounds from the NIH Roadmap Molecular Libraries Small Molecule Repository in a pilot screen and identified agents that increase the F508del protein pool. Second, we analyzed ~10,000 compounds representing diverse chemical scaffolds for effects on total CFTR expression using a multi-plate fluorescence protocol and describe compounds that promote F508del maturation. Together, our findings demonstrate proof of principle that agents identified in this fashion can augment the level of endoplasmic reticulum (ER) resident "Band B" F508del CFTR suitable for pharmacologic correction. As further evidence in support of this strategy, PYR-41-a compound that inhibits the E1 ubiquitin activating enzyme-was shown to synergistically enhance F508del rescue by C18, a small molecule corrector. Our combined results indicate that increasing the levels of ER-localized CFTR available for repair provides a novel route to correct F508del CFTR.

Transcriptional Profiling of a Selective CREB Binding Protein Bromodomain Inhibitor Highlights Therapeutic Opportunities.

Bromodomains are involved in transcriptional regulation through the recognition of acetyl lysine modifications on diverse proteins. Selective pharmacological modulators of bromodomains are lacking, although the largely hydrophobic nature of the pocket makes these modules attractive targets for small-molecule inhibitors. This work describes the structure-based design of a highly selective inhibitor of the CREB binding protein (CBP) bromodomain and its use in cell-based transcriptional profiling experiments. The inhibitor downregulated a number of inflammatory genes in macrophages that were not affected by a selective BET bromodomain inhibitor. In addition, the CBP bromodomain inhibitor modulated the mRNA level of the regulator of G-protein signaling 4 (RGS4) gene in neurons, suggesting a potential therapeutic opportunity for CBP inhibitors in the treatment of neurological disorders.

Fluorine in drug design: a case study with fluoroanisoles.

Anisole and fluoroanisoles display distinct conformational preferences, as evident from a survey of their crystal structures. In addition to altering the free ligand conformation, various degrees of fluorination have a strong impact on physicochemical and pharmacokinetic properties. Analysis of anisole and fluoroanisole matched molecular pairs in the Pfizer corporate database reveals interesting trends: 1) PhOCF3 increases log D by ~1 log unit over PhOCH3 compounds; 2) PhOCF3 shows lower passive permeability despite its higher lipophilicity; and 3) PhOCF3 does not appreciably improve metabolic stability over PhOCH3 . Emerging from the investigation, difluoroanisole (PhOCF2 H) strikes a better balance of properties with noticeable advantages of log D and transcellular permeability over PhOCF3 . Synthetic assessment illustrates that the routes to access difluoroanisoles are often more straightforward than those for trifluoroanisoles. Whereas replacing PhOCH3 with PhOCF3 is a common tactic to optimize ADME properties, our analysis suggests PhOCF2 H may be a more attractive alternative, and greater exploitation of this motif is recommended.

A protein relational database and protein family knowledge bases to facilitate structure-based design analyses.

The Protein Data Bank is the most comprehensive source of experimental macromolecular structures. It can, however, be difficult at times to locate relevant structures with the Protein Data Bank search interface. This is particularly true when searching for complexes containing specific interactions between protein and ligand atoms. Moreover, searching within a family of proteins can be tedious. For example, one cannot search for some conserved residue as residue numbers vary across structures. We describe herein three databases, Protein Relational Database, Kinase Knowledge Base, and Matrix Metalloproteinase Knowledge Base, containing protein structures from the Protein Data Bank. In Protein Relational Database, atom-atom distances between protein and ligand have been precalculated allowing for millisecond retrieval based on atom identity and distance constraints. Ring centroids, centroid-centroid and centroid-atom distances and angles have also been included permitting queries for pi-stacking interactions and other structural motifs involving rings. Other geometric features can be searched through the inclusion of residue pair and triplet distances. In Kinase Knowledge Base and Matrix Metalloproteinase Knowledge Base, the catalytic domains have been aligned into common residue numbering schemes. Thus, by searching across Protein Relational Database and Kinase Knowledge Base, one can easily retrieve structures wherein, for example, a ligand of interest is making contact with the gatekeeper residue.

Development of QSAR models for microsomal stability: identification of good and bad structural features for rat, human and mouse microsomal stability.

High throughput microsomal stability assays have been widely implemented in drug discovery and many companies have accumulated experimental measurements for thousands of compounds. Such datasets have been used to develop in silico models to predict metabolic stability and guide the selection of promising candidates for synthesis. This approach has proven most effective when selecting compounds from proposed virtual libraries prior to synthesis. However, these models are not easily interpretable at the structural level, and thus provide little insight to guide traditional synthetic efforts. We have developed global classification models of rat, mouse and human liver microsomal stability using in-house data. These models were built with FCFP_6 fingerprints using a Naïve Bayesian classifier within Pipeline Pilot. The test sets were correctly classified as stable or unstable with satisfying accuracies of 78, 77 and 75% for rat, human and mouse models, respectively. The prediction confidence was assigned using the Bayesian score to assess the applicability of the models. Using the resulting models, we developed a novel data mining strategy to identify structural features associated with good and bad microsomal stability. We also used this approach to identify structural features which are good for one species but bad for another. With these findings, the structure-metabolism relationships are likely to be understood faster and earlier in drug discovery.

CONFIRM: connecting fragments found in receptor molecules.

A novel algorithm for the connecting of fragment molecules is presented and validated for a number of test systems. Within the CONFIRM (Connecting Fragments Found in Receptor Molecules) approach a pre-prepared library of bridges is searched to extract those which match a search criterion derived from known experimental or computational binding information about fragment molecules within a target binding site. The resulting bridge 'hits' are then connected, in an automated fashion, to the fragments and docked into the target receptor. Docking poses are assessed in terms of root-mean-squared deviation from the known positions of the fragment molecules, as well as docking score should known inhibitors be available. The creation of the bridge library, the full details and novelty of the CONFIRM algorithm, and the general applicability of this approach within the field of fragment-based de novo drug design are discussed.

Trap models and slow dynamics in supercooled liquids.

The predictions of a class of phenomenological trap models of supercooled liquids are tested via computer simulation of a model glass-forming liquid. It is found that a model with a Gaussian distribution of trap energies provides a good description of the landscape dynamics, even at temperatures above T(c), the critical temperature of mode-coupling theory. A scenario is discussed whereby deep traps are composed of collections of inherent structures above T(c) and single inherent structures below T(c). Deviations from the simple Gaussian trap picture are quantified and discussed.