Discovery of Pyrido[2,3-b]indole Derivatives with Gram-Negative Activity Targeting Both DNA Gyrase and Topoisomerase IV.

The rise of multidrug resistant (MDR) Gram-negative (GN) pathogens and the decline of available antibiotics that can effectively treat these severe infections are a major threat to modern medicine. Developing novel antibiotics against MDR GN pathogens is particularly difficult as compounds have to permeate the GN double membrane, which has very different physicochemical properties, and have to circumvent a plethora of resistance mechanisms such as multiple efflux pumps and target modifications. The bacterial type II topoisomerases DNA gyrase (GyrA2B2) and Topoisomerase IV (ParC2E2) are highly conserved targets across all bacterial species and validated in the clinic by the fluoroquinolones. Dual inhibitors targeting the ATPase domains (GyrB/ParE) of type II topoisomerases can overcome target-based fluoroquinolone resistance. However, few ATPase inhibitors are active against GN pathogens. In this study, we demonstrated a successful strategy to convert a 2-carboxamide substituted azaindole chemical scaffold with only Gram-positive (GP) activity into a novel series with also potent activity against a range of MDR GN pathogens. By systematically fine-tuning the many physicochemical properties, we identified lead compounds such as 17r with a balanced profile showing potent GN activity, high aqueous solubility, and desirable PK features. Moreover, we showed the bactericidal efficacy of 17r using a neutropenic mouse thigh infection model.

Past, Current, and Future Developments of Therapeutic Agents for Treatment of Chronic Hepatitis B Virus Infection.

For decades, treatment of hepatitis B virus (HBV) infection has been relying on interferon (IFN)-based therapies and nucleoside/nucleotide analogues (NAs) that selectively target the viral polymerase reverse transcriptase (RT) domain and thereby disrupt HBV viral DNA synthesis. We have summarized here the key steps in the HBV viral life cycle, which could potentially be targeted by novel anti-HBV therapeutics. A wide range of next-generation direct antiviral agents (DAAs) with distinct mechanisms of actions are discussed, including entry inhibitors, transcription inhibitors, nucleoside/nucleotide analogues, inhibitors of viral ribonuclease H (RNase H), modulators of viral capsid assembly, inhibitors of HBV surface antigen (HBsAg) secretion, RNA interference (RNAi) gene silencers, antisense oligonucleotides (ASOs), and natural products. Compounds that exert their antiviral activities mainly through host factors and immunomodulation, such as host targeting agents (HTAs), programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) inhibitors, and Toll-like receptor (TLR) agonists, are also discussed. In this Perspective, we hope to provide an overview, albeit by no means being comprehensive, for the recent development of novel therapeutic agents for the treatment of chronic HBV infection, which not only are able to sustainably suppress viral DNA but also aim to achieve functional cure warranted by HBsAg loss and ultimately lead to virus eradication and cure of hepatitis B.

Discovery and Pre-Clinical Characterization of Third-Generation 4-H Heteroaryldihydropyrimidine (HAP) Analogues as Hepatitis B Virus (HBV) Capsid Inhibitors.

Described herein are the discovery and structure-activity relationship (SAR) studies of the third-generation 4-H heteroaryldihydropyrimidines (4-H HAPs) featuring the introduction of a C6 carboxyl group as novel HBV capsid inhibitors. This new series of 4-H HAPs showed improved anti-HBV activity and better drug-like properties compared to the first- and second-generation 4-H HAPs. X-ray crystallographic study of analogue 12 (HAP_R01) with Cp149 Y132A mutant hexamer clearly elucidated the role of C6 carboxyl group played for the increased binding affinity, which formed strong hydrogen bonding interactions with capsid protein and coordinated waters. The representative analogue 10 (HAP_R10) was extensively characterized in vitro (ADMET) and in vivo (mouse PK and PD) and subsequently selected for further development as oral anti-HBV infection agent.

Structure-based assessment of disease-related mutations in human voltage-gated sodium channels.

Voltage-gated sodium (Nav) channels are essential for the rapid upstroke of action potentials and the propagation of electrical signals in nerves and muscles. Defects of Nav channels are associated with a variety of channelopathies. More than 1000 disease-related mutations have been identified in Nav channels, with Nav1.1 and Nav1.5 each harboring more than 400 mutations. Nav channels represent major targets for a wide array of neurotoxins and drugs. Atomic structures of Nav channels are required to understand their function and disease mechanisms. The recently determined atomic structure of the rabbit voltage-gated calcium (Cav) channel Cav1.1 provides a template for homology-based structural modeling of the evolutionarily related Nav channels. In this Resource article, we summarized all the reported disease-related mutations in human Nav channels, generated a homologous model of human Nav1.7, and structurally mapped disease-associated mutations. Before the determination of structures of human Nav channels, the analysis presented here serves as the base framework for mechanistic investigation of Nav channelopathies and for potential structure-based drug discovery.

PROTEIN STRUCTURE. Crystal structure of a mycobacterial Insig homolog provides insight into how these sensors monitor sterol levels.

Insulin-induced gene 1 (Insig-1) and Insig-2 are endoplasmic reticulum membrane-embedded sterol sensors that regulate the cellular accumulation of sterols. Despite their physiological importance, the structural information on Insigs remains limited. Here we report the high-resolution structures of MvINS, an Insig homolog from Mycobacterium vanbaalenii. MvINS exists as a homotrimer. Each protomer comprises six transmembrane segments (TMs), with TM3 and TM4 contributing to homotrimerization. The six TMs enclose a V-shaped cavity that can accommodate a diacylglycerol molecule. A homology-based structural model of human Insig-2, together with biochemical characterizations, suggest that the central cavity of Insig-2 accommodates 25-hydroxycholesterol, whereas TM3 and TM4 engage in Scap binding. These analyses provide an important framework for further functional and mechanistic understanding of Insig proteins and the sterol regulatory element-binding protein pathway.

Structure-Based Design and Synthesis of Potent Cyclic Peptides Inhibiting the YAP-TEAD Protein-Protein Interaction.

The YAP-TEAD protein-protein interaction (PPI) mediates the oncogenic function of YAP, and inhibitors of this PPI have potential usage in treatment of YAP-involved cancers. Here we report the design and synthesis of potent cyclic peptide inhibitors of the YAP-TEAD interaction. A truncation study of YAP interface 3 peptide identified YAP(84-100) as a weak peptide inhibitor (IC50 = 37 µM), and an alanine scan revealed a beneficial mutation, D94A. Subsequent replacement of a native cation-π interaction with an optimized disulfide bridge for conformational constraint and synergistic effect between macrocyclization and modification at positions 91 and 93 greatly boosted inhibitory activity. Peptide 17 was identified with an IC50 of 25 nM, and the binding affinity (K d = 15 nM) of this 17mer peptide to TEAD1 proved to be stronger than YAP(50-171) (K d = 40 nM).

Discovery and characterization of novel, potent, and selective cytochrome P450 2J2 inhibitors.

Cytochrome P450 (CYP) 2J2 is one of the human CYPs involved in phase I xenobiotics metabolism. It is mainly expressed in extrahepatic tissues, including intestine and cardiovascular systems. The general role of CYP2J2 in drug metabolism is not yet fully understood, and the recent discovery that CYP2J2 can metabolize a wide range of structurally diverse drugs and its primary distribution in the intestine suggest its potentially indispensable role in first-pass intestinal metabolism and involvement in drug-drug interaction. To fully characterize its role in drug metabolism, selective and potent inhibitors of CYP2J2 are necessary tools. In the current study, 69 known drugs were screened for the inhibition of CYP2J2, and we discovered a number of marketed drugs as potent and selective CYP2J2 inhibitors. In particular, telmisartan and flunarizine have CYP2J2 inhibition IC(50) values of 0.42 µM and 0.94 µM, respectively, which are at least 10-fold more selective against all other major metabolizing CYPs; moreover, they are not substrates of CYP2J2 and show no time-dependent inhibition toward this CYP. The results of enzyme kinetics studies, supported by molecular modeling, have also elucidated that telmisartan is a mixed-type inhibitor, and flunarizine competitively inhibits CYP2J2. The K(i) for telmisartan is 0.19 µM, with an α value, an indicator of the type of inhibition mechanism, of 2.80, and flunarizine has a K(i) value of 0.13 µM. These newly discovered CYP2J2 inhibitors can be potentially used as a tool to study CYP2J2 in drug metabolism and interaction in a clinical setting.

AMP-activated protein kinase undergoes nucleotide-dependent conformational changes.

The energy sensor AMP-activated protein kinase (AMPK) is a heterotrimeric complex that is allosterically activated by AMP binding to the γ subunit. Cocrystal structures of the mammalian AMPK core reveal occlusion of nucleotide-binding site 3 of the γ subunit in the presence of ATP. However, site 3 is occupied in the presence of AMP. Mutagenesis studies indicate that sites 3 and 4 are important for AMPK allosteric activation.

The molecular basis of ABA-independent inhibition of PP2Cs by a subclass of PYL proteins.

PYR1/PYL/RCAR proteins (PYLs) are confirmed abscisic acid (ABA) receptors, which inhibit protein phosphatase 2C (PP2C) upon binding to ABA. Arabidopsis thaliana has 14 PYLs, yet their functional distinction remains unclear. Here, we report systematic biochemical characterization of PYLs. A subclass of PYLs, represented by PYL10, inhibited PP2C in the absence of any ligand. Crystal structures of PYL10, both in the free form and in the HAB1 (PP2C)-bound state, revealed the structural basis for its constitutive activity. Structural-guided biochemical analyses revealed that ABA-independent inhibition of PP2C requires the PYLs to exist in a monomeric state. In addition, the residues guarding the entrance to the ligand-binding pocket of these PYLs should be bulky and hydrophobic. Based on these principles, we were able to generate monomeric PYL2 variants that gained constitutive inhibitory effect on PP2Cs. These findings provide an important framework for understanding the complex regulation of ABA signaling by PYL proteins.

In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.

The growing resistance to current first-line antimalarial drugs represents a major health challenge. To facilitate the discovery of new antimalarials, we have implemented an efficient and robust high-throughput cell-based screen (1,536-well format) based on proliferation of Plasmodium falciparum (Pf) in erythrocytes. From a screen of approximately 1.7 million compounds, we identified a diverse collection of approximately 6,000 small molecules comprised of >530 distinct scaffolds, all of which show potent antimalarial activity (<1.25 microM). Most known antimalarials were identified in this screen, thus validating our approach. In addition, we identified many novel chemical scaffolds, which likely act through both known and novel pathways. We further show that in some cases the mechanism of action of these antimalarials can be determined by in silico compound activity profiling. This method uses large datasets from unrelated cellular and biochemical screens and the guilt-by-association principle to predict which cellular pathway and/or protein target is being inhibited by select compounds. In addition, the screening method has the potential to provide the malaria community with many new starting points for the development of biological probes and drugs with novel antiparasitic activities.

In silico discovery of transcription regulatory elements in Plasmodium falciparum.

BACKGROUND: With the sequence of the Plasmodium falciparum genome and several global mRNA and protein life cycle expression profiling projects now completed, elucidating the underlying networks of transcriptional control important for the progression of the parasite life cycle is highly pertinent to the development of new anti-malarials. To date, relatively little is known regarding the specific mechanisms the parasite employs to regulate gene expression at the mRNA level, with studies of the P. falciparum genome sequence having revealed few cis-regulatory elements and associated transcription factors. Although it is possible the parasite may evoke mechanisms of transcriptional control drastically different from those used by other eukaryotic organisms, the extreme AT-rich nature of P. falciparum intergenic regions (approximately 90% AT) presents significant challenges to in silico cis-regulatory element discovery. RESULTS: We have developed an algorithm called Gene Enrichment Motif Searching (GEMS) that uses a hypergeometric-based scoring function and a position-weight matrix optimization routine to identify with high-confidence regulatory elements in the nucleotide-biased and repeat sequence-rich P. falciparum genome. When applied to promoter regions of genes contained within 21 co-expression gene clusters generated from P. falciparum life cycle microarray data using the semi-supervised clustering algorithm Ontology-based Pattern Identification, GEMS identified 34 putative cis-regulatory elements associated with a variety of parasite processes including sexual development, cell invasion, antigenic variation and protein biosynthesis. Among these candidates were novel motifs, as well as many of the elements for which biological experimental evidence already exists in the Plasmodium literature. To provide evidence for the biological relevance of a cell invasion-related element predicted by GEMS, reporter gene and electrophoretic mobility shift assays were conducted. CONCLUSION: This GEMS analysis demonstrates that in silico regulatory element discovery can be successfully applied to challenging repeat-sequence-rich, base-biased genomes such as that of P. falciparum. The fact that regulatory elements were predicted from a diverse range of functional gene clusters supports the hypothesis that cis-regulatory elements play a role in the transcriptional control of many P. falciparum biological processes. The putative regulatory elements described represent promising candidates for future biological investigation into the underlying transcriptional control mechanisms of gene regulation in malaria parasites.

A probability-based approach for the analysis of large-scale RNAi screens.

We describe a statistical analysis methodology designed to minimize the impact of off-target activities upon large-scale RNA interference (RNAi) screens in mammalian cells. Application of this approach enhances reconfirmation rates and facilitates the experimental validation of new gene activities through the probability-based identification of multiple distinct and active small interfering RNAs (siRNAs) targeting the same gene. We further extend this approach to establish that the optimal redundancy for efficacious RNAi collections is between 4-6 siRNAs per gene.

Large-scale annotation of small-molecule libraries using public databases.

While many large publicly accessible databases provide excellent annotation for biological macromolecules, the same is not true for small chemical compounds. Commercial data sources also fail to encompass an annotation interface for large numbers of compounds and tend to be cost prohibitive to be widely available to biomedical researchers. Therefore, using annotation information for the selection of lead compounds from a modern day high-throughput screening (HTS) campaign presently occurs only under a very limited scale. The recent rapid expansion of the NIH PubChem database provides an opportunity to link existing biological databases with compound catalogs and provides relevant information that potentially could improve the information garnered from large-scale screening efforts. Using the 2.5 million compound collection at the Genomics Institute of the Novartis Research Foundation (GNF) as a model, we determined that approximately 4% of the library contained compounds with potential annotation in such databases as PubChem and the World Drug Index (WDI) as well as related databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and ChemIDplus. Furthermore, the exact structure match analysis showed 32% of GNF compounds can be linked to third party databases via PubChem. We also showed annotations such as MeSH (medical subject headings) terms can be applied to in-house HTS databases in identifying signature biological inhibition profiles of interest as well as expediting the assay validation process. The automated annotation of thousands of screening hits in batch is becoming feasible and has the potential to play an essential role in the hit-to-lead decision making process.

Study of gene function based on spatial co-expression in a high-resolution mouse brain atlas.

BACKGROUND: The Allen Brain Atlas (ABA) project systematically profiles three-dimensional high-resolution gene expression in postnatal mouse brains for thousands of genes. By unveiling gene behaviors at both the cellular and molecular levels, ABA is becoming a unique and comprehensive neuroscience data source for decoding enigmatic biological processes in the brain. Given the unprecedented volume and complexity of the in situ hybridization image data, data mining in this area is extremely challenging. Currently, the ABA database mainly serves as an online reference for visual inspection of individual genes; the underlying rich information of this large data set is yet to be explored by novel computational tools. In this proof-of-concept study, we studied the hypothesis that genes sharing similar three-dimensional expression profiles in the mouse brain are likely to share similar biological functions. RESULTS: In order to address the pattern comparison challenge when analyzing the ABA database, we developed a robust image filtering method, dubbed histogram-row-column (HRC) algorithm. We demonstrated how the HRC algorithm offers the sensitivity of identifying a manageable number of gene pairs based on automatic pattern searching from an original large brain image collection. This tool enables us to quickly identify genes of similar in situ hybridization patterns in a semi-automatic fashion and consequently allows us to discover several gene expression patterns with expression neighborhoods containing genes of similar functional categories. CONCLUSION: Given a query brain image, HRC is a fully automated algorithm that is able to quickly mine vast number of brain images and identify a manageable subset of genes that potentially shares similar spatial co-distribution patterns for further visual inspection. A three-dimensional in situ hybridization pattern, if statistically significant, could serve as a fingerprint of certain gene function. Databases such as ABA provide valuable data source for characterizing brain-related gene functions when armed with powerful image querying tools like HRC.

Learning from the data: mining of large high-throughput screening databases.

High-throughput screening (HTS) campaigns in pharmaceutical companies have accumulated a large amount of data for several million compounds over a couple of hundred assays. Despite the general awareness that rich information is hidden inside the vast amount of data, little has been reported for a systematic data mining method that can reliably extract relevant knowledge of interest for chemists and biologists. We developed a data mining approach based on an algorithm called ontology-based pattern identification (OPI) and applied it to our in-house HTS database. We identified nearly 1500 scaffold families with statistically significant structure-HTS activity profile relationships. Among them, dozens of scaffolds were characterized as leading to artifactual results stemming from the screening technology employed, such as assay format and/or readout. Four types of compound scaffolds can be characterized based on this data mining effort: tumor cytotoxic, general toxic, potential reporter gene assay artifact, and target family specific. The OPI-based data mining approach can reliably identify compounds that are not only structurally similar but also share statistically significant biological activity profiles. Statistical tests such as Kruskal-Wallis test and analysis of variance (ANOVA) can then be applied to the discovered scaffolds for effective assignment of relevant biological information. The scaffolds identified by our HTS data mining efforts are an invaluable resource for designing SAR-robust diversity libraries, generating in silico biological annotations of compounds on a scaffold basis, and providing novel target family specific scaffolds for focused compound library design.

An efficient rapid system for profiling the cellular activities of molecular libraries.

Rapid quantitative methods for characterizing small molecules, peptides, proteins, or RNAs in a broad array of cellular assays would allow one to discover new biological activities associated with these molecules and also provide a more comprehensive profile of drug candidates early in the drug development process. Here we describe a robotic system, termed the automated compound profiler, capable of both propagating a large number of cell lines in parallel and assaying large collections of molecules simultaneously against a matrix of cellular assays in a highly reproducible manner. To illustrate its utility, we have characterized a set of 1,400 kinase inhibitors in a panel of 35 activated tyrosine-kinase-dependent cellular assays in dose-response format in a single experiment. Analysis of the resulting multidimensional dataset revealed subclusters of both inhibitors and kinases with closely correlated activities. The approach also identified activities for the p38 inhibitor BIRB796 and the dual src/abl inhibitor BMS-354825 and exposed the expected side activities for Glivec/STI571, including cellular inhibition of c-kit and platelet-derived growth factor receptor. This methodology provides a powerful tool for unraveling the cellular biology and molecular pharmacology of both naturally occurring and synthetic chemical diversity.

Profiling the kinome for drug discovery.

The human kinome is made up of 518 distinctive serine/threonine and tyrosine kinases, which are key components of virtually every mammalian signal transduction pathway. Consequently, kinases provide a compelling target family for the development of small molecule inhibitors, which could be used as tools to delineate the mechanism of action for biological processes and potentially be used as therapeutics to treat human diseases such as cancer. A myriad of recent technological advances have accelerated our understanding of kinome function, its relationship to tumorigenic development, and have contributed to the progression of small molecule kinase inhibitors into the clinic. Essential to the continued growth of the field are informatics tools that can assist in interpreting disparate and voluminous data sets and correctly guide decision making processes. These advances are expected to have a dramatic impact on kinase drug development and clinical diagnoses and treatment in the near future.:

Novel statistical approach for primary high-throughput screening hit selection.

The standard activity threshold-based method (the "top X" approach), currently widely used in the high-throughput screening (HTS) data analysis, is ineffective at identifying good-quality hits. We have proposed a novel knowledge-based statistical approach, driven by the hidden structure-activity relationship (SAR) within a screening library, for primary hit selection. Application to an in-house ultrahigh-throughput screening (uHTS) campaign has demonstrated it can directly identify active scaffolds containing valuable SAR information with a greatly improved confirmation rate compared to the standard "top X" method (from 55% to 85%). This approach may help produce high-quality leads and expedite the hit-to-lead process in drug discovery.