Combinatorial Chemistry & High Throughput Screening - Volume 11, Issue 8, 2008

Chemogenomics is a recent scientific discipline that can be defined as the study of the interaction of functional biological systems with exogenous small molecules, or in broader sense the study of the intersection of biological and chemical spaces. This ambitious objective requires expertise in biology, chemistry and computational sciences (bioinformatics, cheminformatics, large scale statistics and machine learning methods) but it is more than a simple apposition of each of these disciplines. Working together, biologists, chemists, and computer scientists have to find their common language and shared concepts. Biological entities interacting with small molecules can be isolated proteins or more elaborate systems, from single cells to complete organisms. The biological space is therefore analyzed at various genomic levels (genomic, transcriptomic, proteomic or any phenotypic level). The space of small molecules is partially real, corresponding to commercial and academic collections of compounds, and partially virtual, corresponding to the chemical space possibly synthesizable. Synthetic chemistry has developed novel strategies allowing a physical exploration of this universe of possibilities. A major challenge of cheminformatics is to charter the virtual space of small molecules using realistic biological constraints (bioavailability, druggability, structural biological information). Chemogenomics is a descendent of conventional pharmaceutical approaches, since it involves the screening of chemolibraries for their effect on biological targets, and benefits from the advances in the corresponding enabling technologies and the introduction of new biological markers. Screening was originally motivated by the rigorous discovery of new drugs, neglecting and throwing away any molecule that would fail to meet the standards required for a therapeutic treatment. It is now the basis for the discovery of small molecules that might or might not be directly used as drugs, but which have an immense potential for basic research, as probes to explore an increasing number of biological phenomena. Concerns about the environmental impact of chemical industry also open new fields of research for chemogenomics. In this special issue (CCHTS Vol. 11, No. 8), biologists, chemists, computer scientists and mathematicians help to capture a global view, shedding light on the diverse aspects of chemogenomics. Together, their focused reviews illustrate how this discipline is at the crossroad of high throughput technologies, biomarker research, combinatorial chemistry, genomics, cheminformatics, bioinformatics and artificial intelligence.

Chemogenomics is the study of the interaction of functional biological systems with exogenous small molecules, or in broader sense the study of the intersection of biological and chemical spaces. Chemogenomics requires expertises in biology, chemistry and computational sciences (bioinformatics, cheminformatics, large scale statistics and machine learning methods) but it is more than the simple apposition of each of these disciplines. Biological entities interacting with small molecules can be isolated proteins or more elaborate systems, from single cells to complete organisms. The biological space is therefore analyzed at various postgenomic levels (genomic, transcriptomic, proteomic or any phenotypic level). The space of small molecules is partially real, corresponding to commercial and academic collections of compounds, and partially virtual, corresponding to the chemical space possibly synthesizable. Synthetic chemistry has developed novel strategies allowing a physical exploration of this universe of possibilities. A major challenge of cheminformatics is to charter the virtual space of small molecules using realistic biological constraints (bioavailability, druggability, structural biological information). Chemogenomics is a descendent of conventional pharmaceutical approaches, since it involves the screening of chemolibraries for their effect on biological targets, and benefits from the advances in the corresponding enabling technologies and the introduction of new biological markers. Screening was originally motivated by the rigorous discovery of new drugs, neglecting and throwing away any molecule that would fail to meet the standards required for a therapeutic treatment. It is now the basis for the discovery of small molecules that might or might not be directly used as drugs, but which have an immense potential for basic research, as probes to explore an increasing number of biological phenomena. Concerns about the environmental impact of chemical industry open new fields of research for chemogenomics.

Diversity-Oriented Synthesis (DOS) aims to broaden the frontier of accessible collections of complex and diverse small molecules. This review endeavours to dissect the DOS concept through three elements of diversity: building block, stereochemistry, and skeleton. Recent examples in the literature that emphasize the efficient combinations of these elements to generate diversity are reported.

The more recently discovered anthozoan fluorescent proteins (FPs) and the classic Aequorea victoria Green Fluorescent Protein (avGFP) as well as their derivatives have become versatile tools as live cell markers in fluorescence microscopy. In this review, we show the use of these FPs in drug discovery assays. Assay examples are given for the application of FPs in multiplexed imaging, as photosensitizers, as fluorescent timers, as pulse-chase labels and for robotically integrated compound testing. The development of fast microscopic imaging devices has enabled the application of automated fluorescence microscopy combined with image analysis to pharmaceutical high throughput drug discovery assays, generally referred to as High Content Screening (HCS).

Cell-based screening using phenotypic assays is a useful means of identifying bioactive chemicals for use as tools to elucidate complex cellular processes. However, the chemicals must display sufficient selectivity and their targets have to be identified. We describe how cell-based screening assays can be designed to maximize the likelihood of discovering selective compounds through the choice of positive readouts, low chemical concentrations and long incubation periods. Examining the potency, efficacy and activity range of chemicals can further help set apart those likely to act more specifically. Identifying the cellular targets of active chemicals can be especially demanding. Secondary screens and the cautious use of the candidate approach can help narrow down their mechanisms of action, but biased approaches may lead to the identification of secondary or even irrelevant targets. We discuss strategies for unbiased target identification by sampling potential targets at the genome-wide and proteome-wide levels.

Microtubules are still a promising target for new therapeutic agents. Thus, there is a continuous interest for compounds able to modify microtubule assembly, either by interacting directly with tubulin, or by interacting with microtubules regulators. Because of its dynamic characteristics, the microtubule cytoskeleton is a suitable target for small molecules that rapidly diffuse in the cell cytoplasm. Moreover, compounds targeting the microtubule cytoskeleton have proved to be valuable tools for basic research in cell biology. In this paper, after a short presentation of the apparent molecular pathways involved in the anticancer effect of agents that interfere with microtubules functions, the potentials and impact of chemogenomics and cell-based assays in the discovery of new therapeutic compounds and of new regulators of the microtubule cytoskeleton are described.

Infectious diseases caused by protozoan parasites - malaria, sleeping sickness, leishmaniasis, Chagas' disease, toxoplasmosis - remain chronic problems for humanity. We lack vaccines and have limited drug options effective against protozoa. Research into anti-protozoan drugs has accelerated with improved in vitro cultivation methods, enhanced genetic accessibility, completed genome sequences for key protozoa, and increased prominence of protozoan diseases on the agendas of well-resourced public figures and foundations. Concurrent advances in high-throughput screening (HTS) technologies and availability of diverse small molecule libraries offer the promise of accelerated discovery of new drug targets and new drugs that will reduce disease burdens imposed on humanity by parasitic protozoa. We provide a status report on HTS technologies in hand and cell-based assays under development for biological investigations and drug discovery directed toward the three best-characterized parasitic protozoa: Trypanosoma brucei, Plasmodium falciparum, and Toxoplasma gondii. We emphasize cell growth assays and new insights into parasite cell biology speeding development of better cell-based assays, useful in primary screens for anti-protozoan drug leads and secondary screens to decipher mechanisms of action of leads identified in growth assays. Small molecules that interfere with specific aspects of protozoan biology, identified in such screens, will be valuable tools for dissecting parasite cell biology and developing antiprotozoan drugs. We discuss potential impacts on drug development of new consortia among academic, corporate, and public partners committed to discovery of new, effective anti-protozoan drugs.

As plants lack a circulatory system and adaptive immune system, they have evolved their own defense systems distinct from animals, in which each plant cell is capable of defending itself from pathogens. Plants induce a number of defense responses, which are triggered by a variety of molecules derived from pathogenic microorganisms, referred to as microbe-associated molecular patterns (MAMPs), including peptides, proteins, lipopolysaccharide, β-glucan, chitin, and ergosterol. The interaction between plants and chemicals in the context of plant defense represents a “natural” and simple model for chemogenomics, at the intersection between chemical and biological diversities. For protection of crop plants from diseases, it has been shown to be effective to stimulate the plant immunity by chemical compounds, the so-called “plant defense activators”. Combinatorial chemistry techniques can be applied to the search for novel plant defense activators, but it is essential to establish an efficient and reliable screening system suitable for library screening. For studies of the plant immune system, it is difficult to use isolated proteins as biological targets because the receptors for MAMP recognition are largely unknown and even the receptors identified so far are transmembrane proteins. Therefore, screening for novel peptides acting on MAMP receptors from combinatorial libraries must rely on a solution-phase assay using cells as the biological targets. In this review, we introduce the cell-based lawn format assay for identification of peptides acting as plant defense activators from combinatorial peptide libraries. The requirements and limitations in constructing the screening system using combinatorial libraries in the studies of plant sciences are also discussed.

Assignment of function to protein sequence is a task of growing importance in the life sciences, as new highthroughput sequencing DNA technologies generate ever increasing quantities of genomic and meta-genomic data. Patterns within the sequence space, caused by the evolutionary conservation and assembly of protein domains, make possible the inference of function from sequence similarity. Clustering similar sequences is a useful technique for finding conserved sequences; the CluSTr database is a publicly-available database arranging proteins in a hierarchy structured by similarity. The protein classification tool InterProScan builds on this approach by applying a range of methods to detect proteins that contain signatures indicative of the presence of particular conserved domains. The use of ontologies to describe protein function provides a flexible and abstract language to classify proteins. Together, these techniques can provide an understanding of the shape of the protein space, and can be used to explore the unchartered waters of the emerging metagenomic world.

This article reviews the application of fragment descriptors at different stages of virtual screening: filtering, similarity search, and direct activity assessment using QSAR/QSPR models. Several case studies are considered. It is demonstrated that the power of fragment descriptors stems from their universality, very high computational efficiency, simplicity of interpretation and versatility.

The practical implementation and validation of a ligand-based approach to mining the chemogenomic space of drugs is presented and applied to the in silico target profiling of 767 drugs against 684 targets of therapeutic relevance. The results reveal that drugs targeting aminergic G protein-coupled receptors (GPCRs) show the most promiscuous pharmacological profiles. The detection of cross-pharmacologies between aminergic GPCRs and the opioid, sigma, NMDA, and 5-HT3 receptors aggravate the potential promiscuity of those drugs, predominantly including analgesics, antidepressants, and antipsychotics.

Support vector machines and kernel methods belong to the same class of machine learning algorithms that has recently become prominent in both computational biology and chemistry, although both fields have largely ignored each other. These methods are based on a sound mathematical and computationally efficient framework that implicitly embeds the data of interest, respectively proteins and small molecules, in high-dimensional feature spaces where various classification or regression tasks can be performed with linear algorithms. In this review, we present the main ideas underlying these approaches, survey how both the “biological” and the “chemical” spaces have been separately constructed using the same mathematical framework and tricks, and suggest different avenues to unify both spaces for the purpose of in silico chemogenomics.

Dr. Eric Marechal is a CNRS Research Director, presently in charge of the Comparative Chemogenomics team at Institut de Recherches en Technologies et Sciences pour le Vivant, UMR 5168 CNRS-CEA-INRA-Universite J. Fourier, Grenoble, France. He received an Agregation teaching degree in Life Science (1990) from the Ministry of National Education, a MS (1991) in Cell Biology from Ecole Normale Supérieure de Lyon and a Ph.D. (1994) in Molecular and Cell Biology from the University of Grenoble, France. His Ph.D. project focused on the biochemical characterization of a protein embedded in plant plastid membranes. From 1994 to 1997, he joined the Nam-Hai Chua laboratory at the Rockefeller University, New York, USA, funded by the Human Frontier Program and by Monsanto, as a post-doctoral fellow in plant biochemistry. After a short period at Rhone-Poulenc Industrialisation, Lyon, he joined the CNRS in 1998. Since 1998, Eric Marechal has focused on the lipid metabolism and dynamics in plants and in apicomplexan parasites (a group of species including the malaria parasite Plasmodium falciparum), taking this opportunity to start target and drug discovery projects, in collaboration with CEREP and Gene-IT. He coauthored several papers in biochemistry, cell biology, plant physiology, toxoplasmosis and malaria research, biomathematics, bioinformatics and chemogenomics. His scientific interests include chemogenomics, from pharmacological high-throughput screening to drug candidate development, comparative genomics of plant and apicomplexans and phylogenomics. He codirected the first teaching book on chemogenomics in French (”Chemogenomique: des petites molecules pour explorer le vivant“, 2007, EDP Sciences, pp. 257).