Derek J. Hook

First-In-Class Small Molecule Inhibitors of the Single-Strand DNA Cytosine Deaminase APOBEC3G

APOBEC3G is a single-stranded DNA cytosine deaminase that comprises part of the innate immune response to viruses and transposons. Although APOBEC3G is the prototype for understanding the larger mammalian polynucleotide deaminase family, no specific chemical inhibitors exist to modulate its activity. High-throughput screening identified 34 compounds that inhibit APOBEC3G catalytic activity. Twenty of 34 small molecules contained catechol moieties, which are known to be sulfhydryl reactive following oxidation to the orthoquinone. Located proximal to the active site, C321 was identified as the binding site for the inhibitors by a combination of mutational screening, structural analysis, and mass spectrometry. Bulkier substitutions C321-to-L, F, Y, or W mimicked chemical inhibition. A strong specificity for APOBEC3G was evident, as most compounds failed to inhibit the related APOBEC3A enzyme or the unrelated enzymes E. coli uracil DNA glycosylase, HIV-1 RNase H, or HIV-1 integrase. Partial, but not complete, sensitivity could be conferred to APOBEC3A by introducing the entire C321 loop from APOBEC3G. Thus, a structural model is presented in which the mechanism of inhibition is both specific and competitive, by binding a pocket adjacent to the APOBEC3G active site, reacting with C321, and blocking access to substrate DNA cytosines.

Approaches to Automating the Dereplication of Bioactive Natural Products—The Key Step in High Throughput Screening of Bioactive Materials From Natural Sources:

The rapid identification of the bioactive component(s) of natural product mixtures in high throughput screening programs has become a critical factor to ensure that this source of diverse chemotypes can compete effectively with chemical compound libraries and combinatorial synthetic efforts. The effective use of automated procedures and databases in the isolation, identification and biological profiling of bioactive compounds will be described. In addition, the potential of new technologies to enhance this process will be discussed as well as the possible reintroduction of TLC as a parallel dereplication method.

High-Throughput Screening for Growth Inhibitors Using a Yeast Model of Familial Paraganglioma

Classical tumor suppressor genes block neoplasia by regulating cell growth and death. A remarkable puzzle is therefore presented by familial paraganglioma (PGL), a neuroendocrine cancer where the tumor suppressor genes encode subunits of succinate dehydrogenase (SDH), an enzyme of the tricarboxylic acid (TCA) cycle of central metabolism. Loss of SDH initiates PGL through mechanisms that remain unclear. Could this metabolic defect provide a novel opportunity for chemotherapy of PGL? We report the results of high throughput screening to identify compounds differentially toxic to SDH mutant cells using a powerful S. cerevisiae (yeast) model of PGL. Screening more than 200,000 compounds identifies 12 compounds that are differentially toxic to SDH-mutant yeast. Interestingly, two of the agents, dequalinium and tetraethylthiuram disulfide (disulfiram), are anti-malarials with the latter reported to be a glycolysis inhibitor. We show that four of the additional hits are potent inhibitors of yeast alcohol dehydrogenase. Because alcohol dehydrogenase regenerates NAD+ in glycolytic cells that lack TCA cycle function, this result raises the possibility that lactate dehydrogenase, which plays the equivalent role in human cells, might be a target of interest for PGL therapy. We confirm that human cells deficient in SDH are differentially sensitive to a lactate dehydrogenase inhibitor.

Human Adenine Nucleotide Translocase (ANT) Modulators Identified by High-Throughput Screening of Transgenic Yeast

Transport of ADP and ATP across mitochondria is one of the primary points of regulation to maintain cellular energy homeostasis. This process is mainly mediated by adenine nucleotide translocase (ANT) located on the mitochondrial inner membrane. There are four human ANT isoforms, each having a unique tissue-specific expression pattern and biological function, highlighting their potential as drug targets for diverse clinical indications, including male contraception and cancer. In this study, we present a novel yeast-based high-throughput screening (HTS) strategy to identify compounds inhibiting the function of ANT. Yeast strains generated by deletion of endogenous proteins with ANT activity followed by insertion of individual human ANT isoforms are sensitive to cell-permeable ANT inhibitors, which reduce proliferation. Screening hits identified in the yeast proliferation assay were characterized in ADP/ATP exchange assays employing recombinant ANT isoforms expressed in isolated yeast mitochondria and Lactococcus lactis as well as by oxygen consumption rate in mammalian cells. Using this approach, closantel and CD437 were identified as broad-spectrum ANT inhibitors, whereas leelamine was found to be a modulator of ANT function. This yeast “knock-out/knock-in” screening strategy is applicable to a broad range of essential molecular targets that are required for yeast survival.

The Fungal Sexual Pheromone Sirenin Activates the Human CatSper Channel Complex

The basal fungus Allomyces macrogynus (A. macrogynus) produces motile male gametes displaying well-studied chemotaxis toward their female counterparts. This chemotaxis is driven by sirenin, a sexual pheromone released by the female gametes. The pheromone evokes a large calcium influx in the motile gametes, which could proceed through the cation channel of sperm (CatSper) complex. Herein, we report the total synthesis of sirenin in 10 steps and 8% overall yield and show that the synthetic pheromone activates the CatSper channel complex, indicated by a concentration-dependent increase in intracellular calcium in human sperm. Sirenin activation of the CatSper channel was confirmed using whole-cell patch clamp electrophysiology with human sperm. Based on this proficient synthetic route and confirmed activation of CatSper, analogues of sirenin can be designed as blockers of the CatSper channel that could provide male contraceptive agents.

Synthesis of Arylazide- and Diazirine-Containing CrAsH-EDT2 Photoaffinity Probes.

Two photo‐crosslinking biarsenical (CrAsH‐EDT2)‐modified probes were synthesized that are expected to be useful tools for tetracysteine‐labeled proteins to facilitate the co‐affinity purification of their DNA binding sequences and interacting proteins. In addition, improvements for the synthesis of CrAsH‐EDT2 and N1‐(4‐azido‐2‐nitrophenyl)hexane‐1,6‐diamine are reported. Both photoprobes effectively entered HeLa cells (and the nucleus) and were dependent on the tetracysteine motif in recombinant DMRT1 (doublesex and Mab3‐related transcription factor) to induce fluorescence, suggesting that their crosslinking abilities can be exploited for the identification of nucleic acids and proteins associated with a protein of interest.

Synthesis of Arylazide- and Diazirine-Containing CrAsH-EDT2 Photoaffinity Probes: Unfortunately, in the article.

Arch. Pharm. Chem. Life Sci. 2016, 349 (4), 233–241 DOI: 10.1002/ardp.201500440 the structure of compound 1 was misrepresented: The azido group of azide-TRAP (1) should be at C-4 rather than at C-5, as reported previously. The correct structure of azide-TRAP (1) in Figure 1, Scheme 1, and the Table of Content graphics is as follows: Arch. Pharm. Chem. Life Sci. 2016, 349, 572–572 Archiv der Pharmazie ARCH PHARM

Functional Protein Microarrays in Drug Discovery

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Book Review: In Silico Technologies in Drug Target Identification and Validation

This book provides an introduction to some of the in silico tools used for drug target identification and validation and should be useful to those who need an overview of the processes involved. It provides a road map to readers to enable exploration in depth in specific areas of interest. The book has 20 chapters, grouped into an introductory chapter and 4 sections of loosely related topics: target identification, target validation, recent trends, and computational infrastructure. Chapter 1, “Introduction,” provides a broad overview of the history and development of the applications of computational techniques to target identification and validation and outlines the organization and purpose of the book. The 1st section, “Target Identification,” addresses pattern matching, functional annotation, polymorphisms, and mining gene expression data and comprises chapters 2 through 5. In this section, chapter 2 deals with pattern matching and is a concise, organized, and useful description and use of the tools and databases available for both protein and gene pattern matching. It is marred by a reference to an apparently missing Figure 5.5 in the “Introduction” section to the chapter. This figure describing the functional anatomy of a gene seems to be nowhere in this section, whereas Figure 5.5 in chapter 5 describes principal components analysis and correspondence analysis of gene expression. Chapter 3, “Tools for Computational Protein Annotation and Functional Assignment,” covers the broad range of annotation tools and strategies from sequence similarity, structural similarity, and functional and contextual similarity methods. It also provides a good warning to ensure that obsolete tools are avoided. Emphasis is placed on a need to understand the algorithms being used on the various databases and commercial products to ensure the best use of these products. This chapter has an extensive list of references and a well-organized list of links to the tools mentioned in the text. Chapter 4, “The Impact of Genetic Variation on Drug Discovery and Development,” focuses on the impact of genetic variation on the drug discovery process and both how it is manifested through genetic variation and the databases from which it can be accessed and manipulated and a review of the functional impact of this genetic variation. The chapter introduces human genetic variation in a drug discovery context and covers mutations, insertion and deletions, single nucleotide polymorphisms, and variable-number tandem repeat polymorphisms. The chapter covers human genetic variation databases and their uses, tools for data visualization, and the functional impact of different types of genetic variation. Chapter 5, “Mining of GeneExpression Data,” confines itself to gene expression analysis using microarray methods. After a brief review of microarrays, various approaches to visualization and statistical analysis are described. It has a useful list of open and commercial software packages for manipulation of gene expression and microarray data. The 2nd section, chapters 6 through 11, centers on target validation. Chapter 6, “Text Mining,” describes the growing need to use automated tools to extract relevant biological information from the literature to assist in human interpretation and annotation of drug targets. Technical aspects of text mining from simple keyword searching to more sophisticated methods that cluster relevant documents together are discussed, with examples of the application for such uses as drug-safety assessment, disease-togene linkages, the drug discovery and development phases, and systems biology applications. Chapter 7, “Pathways and Networks,” sets out to define how pathways and cellular networks can help provide an interpretation of how a cellular or organismic function is realized. The chapter describes mostly the middle and higher level of representation of pathways and networks. It includes a good set of Web resources and discussion on standards. The section on pathway analysis includes mathematical representations of the various methods of analysis. The chapter is, unfortunately, quite long as the authors attempt a comprehensive but confusing set of mathematical equations difficult to explore in depth in a book composed of review chapters. Chapter 8, “Molecular Interactions: Learning from Protein Complexes,” discusses both computational and experimental methods for understanding protein interactions. Although it has a good list of the databases on protein interactions and an extensive list of references, the chapter is quite short for such a complex subject. Chapter 9, “In Silico siRNA Design,” is a quite compact description of the computational methods that can be used for small interfering RNA (siRNA) design, the databases and software tools that are available, and some reasonable practical applications of siRNA. Chapter 10, “Predicting Protein