Frontiers in Medicinal Chemistry - Online - Current Issue

Biologically active small molecules that interact specifically with protein have tremendous values not only for the functional analysis of genes but also for the drug development. Chemical genetics / genomics-based approach has recently been developed and recognized as one of key solutions for this purpose. This review focuses on the utilization of this new research engine for the target mining and validation of angiogenesis inhibitors that are capable of regulating the growth and spreading of cancer cells. Discovery of novel targets for angiogenesis inhibitors and validation of their biological relevancy based on chemical genetics / genomics provide new insight for the biological role of targets as well as for the development of new angiogenesis inhibitors.

Results of various projects on Mexican Indian ethnobotany and some of the subsequent pharmacological and phytochemical studies are summarised focusing both on chemical-pharmacological as well as anthropological (ethnopharmacological) aspects of our research. We have identified taste and smell properties of medicinal (vs. non-medicinal) plants as important indigenous selection criteria. There exist well-defined criteria specific for each culture, which lead to the selection of a plant as a medicine. This field research has also formed a basis for studies on bioactive natural products from selected species. The bark of Guazuma ulmifolia showed antisecretory activity (cholera toxin-induced chloride secretion in rabbit distal colon in an USSING chamber). Active constituents are procyanidins with a polymerisation degree of eight or higher. Byrsonima crassifolia yielded proanthocyanidins with (+) epicatechin units and Baccharis conferta showed a dose-dependant antispasmodic effect with the effect being particularly strong in flavonoid-rich fractions. Our ethnopharmacological research led to the identification of sesquiterpene lactones (SLs) like parthenolide as potent and relatively specific inhibitors of the transcription factor NF-κB, an important mediator of the inflammatory process. The inhibitory effect of SLs is very strongly enhanced by the presence of such groups as the isoprenoid ring system, a lactone ring containing a conjugated exomethylene group (α-methylene-γ-lactone) and an a,β-unsaturated cyclopentenone or a conjugated ester moieties. Our work also elucidated the NF-κB inhibiting activity of the photosensitiser phaeophorbide A from Solanum diflorum (Solanaceae) in PMA induced HeLa cells. Hyptis verticillata yielded a series of lignans as well as sideritoflavone, rosmarinic acid and (R)- 5-hydroxypyrrolidin-2-one and is rich in essential oil (rich in α-pinene, β- pinene and thymol). Other species investigated include Begonia heracleifolia, Crossopetalum gaumerii, Epaltes mexicana, Pluchea symphytifolia and Xanthosoma robustum.

Natural killer T (NKT) cells are a subset of lymphocytes that express receptors characteristic of conventional T cells together with receptors typically found on natural killer cells. A key feature of NKT cells is the expression of a semi-invariant T cell receptor that is specific for glycolipid antigens presented by the unusual major histocompatibility complex class I-like molecule CD1d. While their precise immunological functions remain unknown, NKT cells have been implicated in the regulation of adaptive immune responses, including those directed against autoantigens. These findings raise the possibility that specific stimulation of NKT cells may be exploited for therapeutic purposes. A number of laboratories have tested this hypothesis, utilizing the sea sponge-derived agent α- galactosylceramide (α-GalCer), a specific agonist of NKT cells. Administration of α-GalCer to mice results in potent activation of NKT cells, rapid and robust cytokine production, and activation of a variety of cells of the innate and adaptive immune systems. Most notably, repeated administration of α-GalCer to mice favors the generation of conventional T lymphocytes producing T helper (Th) type 2 cytokines such as IL-4 and IL-10. These findings suggest that α-GalCer can modulate inflammatory conditions that are mediated by pathogenic Th1 cells. Indeed, recent studies have demonstrated that α-GalCer modulates the development of a variety of autoimmune and inflammatory diseases. Collectively, these studies provide a solid foundation for the development of NKT cell ligands as pharmacological agents for treatment of autoimmune diseases.

Lead identification and optimization is always a challenge to the medicinal chemists in drug discovery. Numbers of simple to complex and smaller to bigger organic compounds are prepared to meet the screening purpose of biological targets. Conventional solution phase synthetic methodologies are lacking the speed to run along with the need of medicinally interesting compounds due to their long reaction time, tedious work-up and purification problems. Alternatively opted polymer-supported synthesis of combinatorial libraries has emerged as a promising tool in generating large numbers of structurally diverse molecules parallelly and rapidly. Microwave-assisted solid / liquid phase combinatorial synthetic techniques have proved their efficiencies to reduce the reaction time from days & hours to minutes & seconds and more promisingly to produce improved yields with high purities. This review briefs about the theory behind microwave chemical technology and glimpses of recent advancements in its application on polymer supported combinatorial synthesis.

Pharmacophore discovery is one of the major elements of molecular modeling in the absence of X-ray structural data. While pharmacophores initially made their debut as a means for lead discovery, more recent refinements have brought them into the domain of lead optimization, e.g. as a means to define the molecular alignment in 3D-QSAR. In this review, the experiences of over a decade of confronting and solving the challenges of pharmacophore discovery applied to actual drug discovery are summarized. Also, practical tips are described for using the author's methodology for pharmacophore discovery, DANTE.

In recent years, tools for the development of new drugs have been dramatically improved. These include genomic and proteomic research, numerous biophysical methods, combinatorial chemistry and screening technologies. In addition, early ADMET studies are employed in order to significantly reduce the failure rate in the development of drug candidates. As a consequence, the lead finding, lead optimization and development process has gained marked enhancement in speed and efficiency. In parallel to this development, major pharmaceutical companies are increasingly outsourcing many components of drug discovery research to biotech companies. All these measures are designed to address the need for a faster time to market. New screening methodologies have significantly enhanced the drug discovery process. High throughput screening accelerates lead discovery through rapid evaluation of compound collections, which may already be biased toward a target of interest through in silico screening. This article discusses new NMR screening techniques, which have opened the door to a wide range of new lead finding and lead optimization opportunities.

Methods for the prediction of octanol / water partition coefficient, aqueous solubility and acid / base dissociation constants are described and discussed. The advantages and limitations of the different approaches are described and an indication of problem areas discussed. Available prediction software is described and listed and attempts are made to assess the likely reliability of the predictions. The concept of “drug-likeness” is introduced and put into context and models for the prediction of ADME properties and toxicity are briefly described and assessed. Software for ADME / toxicity prediction is listed and the impact of these techniques on current drug design efforts is described. Web references are given for both commercial and public domain software which is available for property prediction from chemical structure.

Cytochromes P450 (Cyt P450s) constitute the most important biotransformation enzymes involved in the biotransformation of drugs and other xenobiotics. Because drug metabolism by Cyt P450s plays such an important role in the disposition and in the pharmacological and toxicological effects of drugs, early consideration of ADME-properties is increasingly seen as essential for the discovery and the development of new drugs and drug candidates. The primary aim of this paper is to present various computational approaches used to rationalize and predict the activity and substrate selectivity of Cyt P450s, as well as the possibilities and limitations of these approaches, now and in the future. Attention is also paid to the experimental validation of these approaches by using high-throughput screening (HTS) of affinities to drug-drug interactions at the level of Cyt P450-isoenzymes. Since human Cyt P450 2D6 is one of the most important drug metabolizing enzymes and since in this regard much pioneering work has been done with this Cyt P450, Cyt P450 2D6 is chosen as a model for this discussion. Apart from early mechanism-based ab initio calculations on substrates of Cyt P450 2D6, pharmacophore modeling of ligands (i.e. both substrates and inhibitors) of Cyt P450 2D6 and protein homology modeling have been used succesfully for the rationalisation and prediction of metabolite formation by this Cyt P450 isoenzyme. Significant protein structure-related species differences have been reported recently. It is concluded that not one computational approach is capable of rationalizing and reliably predicting metabolite formation by Cyt P450 2D6, but that it is rather the combination of the various complimentary approaches. It is moreover concluded, that experimental validation of the computational models and predictions is often still lacking. With the advent of novel, easily and well applicable in vitro based high throughput assays for ligand binding and turnover this limitation could be overcome soon, however. When effective links with other new and recent developments, such as bioinformatics, neural network computing, genomics and proteomics can be created, in silico rationalisation and prediction of drug metabolism by Cyt P450s is likely to become one of the key technologies in early drug discovery and development processes.