Fragment-Based Drug Discovery of Inhibitors of Phosphopantetheine Adenylyltransferase from Gram-Negative Bacteria.

The discovery and development of new antibiotics capable of curing infections due to multidrug-resistant and pandrug-resistant Gram-negative bacteria are a major challenge with fundamental importance to our global healthcare system. Part of our broad program at Novartis to address this urgent, unmet need includes the search for new agents that inhibit novel bacterial targets. Here we report the discovery and hit-to-lead optimization of new inhibitors of phosphopantetheine adenylyltransferase (PPAT) from Gram-negative bacteria. Utilizing a fragment-based screening approach, we discovered a number of unique scaffolds capable of interacting with the pantetheine site of E. coli PPAT and inhibiting enzymatic activity, including triazolopyrimidinone 6. Structure-based optimization resulted in the identification of two lead compounds as selective, small molecule inhibitors of bacterial PPAT: triazolopyrimidinone 53 and azabenzimidazole 54 efficiently inhibited E. coli and P. aeruginosa PPAT and displayed modest cellular potency against the efflux-deficient E. coli Δ tolC mutant strain.

Identification of N-(4-((1R,3S,5S)-3-Amino-5-methylcyclohexyl)pyridin-3-yl)-6-(2,6-difluorophenyl)-5-fluoropicolinamide (PIM447), a Potent and Selective Proviral Insertion Site of Moloney Murine Leukemia (PIM) 1, 2, and 3 Kinase Inhibitor in Clinical Trials for Hematological Malignancies.

Pan proviral insertion site of Moloney murine leukemia (PIM) 1, 2, and 3 kinase inhibitors have recently begun to be tested in humans to assess whether pan PIM kinase inhibition may provide benefit to cancer patients. Herein, the synthesis, in vitro activity, in vivo activity in an acute myeloid leukemia xenograft model, and preclinical profile of the potent and selective pan PIM kinase inhibitor compound 8 (PIM447) are described. Starting from the reported aminopiperidyl pan PIM kinase inhibitor compound 3, a strategy to improve the microsomal stability was pursued resulting in the identification of potent aminocyclohexyl pan PIM inhibitors with high metabolic stability. From this aminocyclohexyl series, compound 8 entered the clinic in 2012 in multiple myeloma patients and is currently in several phase 1 trials of cancer patients with hematological malignancies.

Optimization of a Dibenzodiazepine Hit to a Potent and Selective Allosteric PAK1 Inhibitor.

The discovery of inhibitors targeting novel allosteric kinase sites is very challenging. Such compounds, however, once identified could offer exquisite levels of selectivity across the kinome. Herein we report our structure-based optimization strategy of a dibenzodiazepine hit 1, discovered in a fragment-based screen, yielding highly potent and selective inhibitors of PAK1 such as 2 and 3. Compound 2 was cocrystallized with PAK1 to confirm binding to an allosteric site and to reveal novel key interactions. Compound 3 modulated PAK1 at the cellular level and due to its selectivity enabled valuable research to interrogate biological functions of the PAK1 kinase.

Large scale meta-analysis of fragment-based screening campaigns: privileged fragments and complementary technologies.

A first step in fragment-based drug discovery (FBDD) often entails a fragment-based screen (FBS) to identify fragment "hits." However, the integration of conflicting results from orthogonal screens remains a challenge. Here we present a meta-analysis of 35 fragment-based campaigns at Novartis, which employed a generic 1400-fragment library against diverse target families using various biophysical and biochemical techniques. By statistically interrogating the multidimensional FBS data, we sought to investigate three questions: (1) What makes a fragment amenable for FBS? (2) How do hits from different fragment screening technologies and target classes compare with each other? (3) What is the best way to pair FBS assay technologies? In doing so, we identified substructures that were privileged for specific target classes, as well as fragments that were privileged for authentic activity against many targets. We also revealed some of the discrepancies between technologies. Finally, we uncovered a simple rule of thumb in screening strategy: when choosing two technologies for a campaign, pairing a biochemical and biophysical screen tends to yield the greatest coverage of authentic hits.

Novel potent and selective inhibitors of p90 ribosomal S6 kinase reveal the heterogeneity of RSK function in MAPK-driven cancers.

UNLABELLED: The p90 ribosomal S6 kinase (RSK) family of serine/threonine kinases is expressed in a variety of cancers and its substrate phosphorylation has been implicated in direct regulation of cell survival, proliferation, and cell polarity. This study characterizes and presents the most selective and potent RSK inhibitors known to date, LJH685 and LJI308. Structural analysis confirms binding of LJH685 to the RSK2 N-terminal kinase ATP-binding site and reveals that the inhibitor adopts an unusual nonplanar conformation that explains its excellent selectivity for RSK family kinases. LJH685 and LJI308 efficiently inhibit RSK activity in vitro and in cells. Furthermore, cellular inhibition of RSK and its phosphorylation of YB1 on Ser102 correlate closely with inhibition of cell growth, but only in an anchorage-independent growth setting, and in a subset of examined cell lines. Thus, RSK inhibition reveals dynamic functional responses among the inhibitor-sensitive cell lines, underscoring the heterogeneous nature of RSK dependence in cancer. IMPLICATIONS: Two novel potent and selective RSK inhibitors will now allow a full assessment of the potential of RSK as a therapeutic target for oncology.

Inside the mind of a medicinal chemist: the role of human bias in compound prioritization during drug discovery.

Medicinal chemists' "intuition" is critical for success in modern drug discovery. Early in the discovery process, chemists select a subset of compounds for further research, often from many viable candidates. These decisions determine the success of a discovery campaign, and ultimately what kind of drugs are developed and marketed to the public. Surprisingly little is known about the cognitive aspects of chemists' decision-making when they prioritize compounds. We investigate 1) how and to what extent chemists simplify the problem of identifying promising compounds, 2) whether chemists agree with each other about the criteria used for such decisions, and 3) how accurately chemists report the criteria they use for these decisions. Chemists were surveyed and asked to select chemical fragments that they would be willing to develop into a lead compound from a set of ~4,000 available fragments. Based on each chemist's selections, computational classifiers were built to model each chemist's selection strategy. Results suggest that chemists greatly simplified the problem, typically using only 1-2 of many possible parameters when making their selections. Although chemists tended to use the same parameters to select compounds, differing value preferences for these parameters led to an overall lack of consensus in compound selections. Moreover, what little agreement there was among the chemists was largely in what fragments were undesirable. Furthermore, chemists were often unaware of the parameters (such as compound size) which were statistically significant in their selections, and overestimated the number of parameters they employed. A critical evaluation of the problem space faced by medicinal chemists and cognitive models of categorization were especially useful in understanding the low consensus between chemists.

Retrospective docking study of PDE4B ligands and an analysis of the behavior of selected scoring functions.

Scoring forms a major obstacle to the success of any docking study. In general, fast scoring functions perform poorly when used to determine the relative affinity of ligands for their receptors. In this study, the objective was not to rank compounds with confidence but simply to identify a scoring method which could provide a 4-fold hit enrichment in a screening sample over random selection. To this end, LigandFit, a fast shape matching docking algorithm, was used to dock a variety of known inhibitors of type 4 phosphodiesterase (PDE4B) into its binding site determined crystallographically for a series of pyrazolopyridine inhibitors. The success of identifying good poses with this technique was explored through RMSD comparisons with 19 known inhibitors for which crystallographic structures were available. The effectiveness of five scoring functions (PMF, JAIN, PLP2, LigScore2, and DockScore) was then evaluated through consideration of the success in enriching the top ranked fractions of nine artificial databases, constructed by seeding 1980 inactive ligands (pIC50 < 5) with 20 randomly selected inhibitors (pIC50 > 6.5). PMF and JAIN showed high average enrichment factors (greater than 4 times) in the top 5-10% of the ranked databases. Rank-based consensus scoring was then investigated, and the rational combination of 3 scoring functions resulted in more robust scoring schemes with (cScore)-DPmJ (consensus score of DockScore, PMF, and JAIN) and (cScore)-PPmJ (PLP2, PMF, and JAIN) yielding particularly good results. These cScores are believed to be of greater general application. Finally, the analysis of the behavior of the scoring functions across different chemotypes uncovered the inherent bias of the docking and scoring toward compounds in the same structural family as that employed for the crystal structure, suggesting the need to use multiple versions of the binding site for more successful virtual screening strategies.

Molecular modeling in cysteine protease inhibitor design.

The application of various molecular modeling techniques has been recently reported in the design of several new cysteine protease inhibitors. Computational chemistry techniques have been used to understand and predict enzyme-inhibitor interactions and also to study enzyme mechanism and inhibitor reactivity. This review focuses on examples that use structure-based design or reflect cysteine proteases as a target class. In several cases X-ray crystallography and molecular modeling have significantly facilitated the inhibitor design process. Cysteine proteases can present extra challenges in molecular modeling, due to the covalent binding modes and the reactive nature of many of the inhibitors. We also discuss some of the key challenges in developing new tools to evaluate these properties and help in making informed decisions about new templates and leads.

Antihydrophobic solvent effects: an experimental probe for the hydrophobic contribution to enzyme-inhibitor binding.

The hydrophobic component to the binding affinities of one acyclic phosphinate (4) and three macrocyclic phosphonamidate inhibitors (1-3) to the zinc peptidase thermolysin was probed by varying the solvent composition. Increasing the percentage of ethanol in the buffer solution over the range 0-9% increases the inhibition constants, K(i), by up to an order of magnitude. This approach represents an experimental method for distinguishing solvation from conformational or other effects on protein-ligand binding. The size of the "antihydrophobic effect" is correlated with the amount of hydrophobic surface area sequestered from solvent on association of the inhibitor and enzyme, although it is attenuated from that calculated from the surface tension of ethanol-water mixtures. The results are consistent with the Lum-Chandler-Weeks explanation for the size dependence of the hydrophobic effect.

Origins of Stereoselectivity in the Corey-Chaykovsky Reaction. Insights from Quantum Chemistry.

Reaction pathways of the Corey-Chaykovsky epoxidation reaction have been compared quantum chemically. Of the concerted, torsional rotation and anti addition pathways the latter two were found to be favored both in the gas phase and in CH(2)Cl(2) in a model system. Several theoretically previously uncharacterized stationary points were located, and selective solvent effects were observed. On the anti addition pathway the C-C bond formation transition state A, suitably substituted to allow comparison with published experimental data, was able to predict both the absolute stereochemistry of the main product and, qualitatively, the distribution of its other stereoisomers. The quantum chemical protocol reported here is useful in designing new sulfides for the Corey-Chaykovsky reaction.