Lead compounds discovered from libraries: part 2

Improving protein-ligand docking results using the Semiempirical quantum mechanics: testing on the PDBbind 2016 core set

Molecular docking techniques are routinely employed for predicting ligand binding conformations and affinities in the in silico phase of the drug design and development process. In this study, a reliable semiempirical quantum mechanics (SQM) method, PM7, was employed for geometry optimization of top-ranked poses obtained from two widely used docking programs, AutoDock4 and AutoDock Vina. The PDBbind core set (version 2016), which contains high-quality crystal protein - ligand complexes with their corresponding experimental binding affinities, was used as an initial dataset in this research. It was shown that docking pose optimization improves the accuracy of pose predictions and is very useful for the refinement of docked complexes via removing clashes between ligands and proteins. It was also demonstrated that AutoDock Vina achieves a higher sampling power than AutoDock4 in generating accurate ligand poses (RMSD ≤ 2.0 Å), while AutoDock4 exhibits a better ranking power than AutoDock Vina. Finally, a new protocol based on a combination of the results obtained from the two docking programs was proposed for structure-based virtual screening studies, which benefits from the robust sampling abilities of AutoDock Vina and the reliable ranking performance of AutoDock4.Communicated by Ramaswamy H. Sarma.

Lead-oriented synthesis of epigenetic relevant scaffolds

A simple and rational method to rank lead-likeness of molecules using continuous evaluation functions was hereby developed. This strategy proved to be competitive against known methods and finally helped in driving synthetic efforts towards candidates of interest for epigenetic applications against HDAC6, BRD4 and EZH2.

Inkjet Bioprinting on Parchment Paper for Hit Identification from Small Molecule Libraries

In this study, an inkjet bioprinting-based high-throughput screening (HTS) system was designed and applied for the first time to a catecholpyrimidine-based small molecule library to find hit compounds that inhibit c-Jun NH₂-terminal kinase1 (JNK1). JNK1 kinase, inactivated MAPKAPK2, and specific fluorescent peptides along with bioink were printed on parchment paper under optimized printing conditions that did not allow rapid evaporation of printed media based on Triton-X and glycerol. Subsequently, different small compounds were printed and tested against JNK1 kinase to evaluate their degree of phosphorylation inhibition. After printing and incubation, fluorescence intensities from the phosphorylated/nonphosphorylated peptide were acquired for the % phosphorylation analysis. The IM₅₀ (inhibitory mole 50) value was determined as 1.55 × 10^-15 mol for the hit compound, 22. Thus, this work demonstrated that inkjet bioprinting-based HTS can potentially be adopted for the drug discovery process using small molecule libraries, and cost-effective HTS can be expected to be established based on its low nano- to picoliter printing volume.

A Method for Rapid Screening of Anilide-Containing AMPK Modulators Based on Computational Docking and Biological Validation

Adenosine 5'-monophsphate-activated protein kinase (AMPK) is a crucial energy sensor for maintaining cellular homeostasis. Targeting AMPK may provide an alternative approach in treatment of various diseases like cancer, diabetes, and neurodegenerations. Accordingly, novel AMPK activators are frequently identified from natural products in recent years. However, most of such AMPK activators are interacting with AMPK in an indirect manner, which may cause off-target effects. Therefore, the search of novel direct AMPK modulators is inevitable and effective screening methods are needed. In this report, a rapid and straightforward method combining the use of in silico and in vitro techniques was established for selecting and categorizing huge amount of compounds from chemical library for targeting AMPK modulators. A new class of direct AMPK modulator have been discovered which are anilides or anilide-like compounds. In total 1,360,000 compounds were virtually screened and 17 compounds were selected after biological assays. Lipinski's rule of five assessment suggested that, 13 out of the 17 compounds are demonstrating optimal bioavailability. Proton acceptors constituting the structure of these compounds and hydrogen bonds with AMPK in the binding site appeared to be the important factors determining the efficacy of these compounds.

Correlating the potentiometric selectivity of cyclosporin-based electrodes with binding patterns obtained from electrospray ionization-mass spectrometry

Electrospray ionization mass spectrometry ESI-MS is a powerful technique for the characterization of macromolecules and their noncovalent binding with guest ions. We herein evaluate the feasibility of using ESI-MS as a screening tool for predicting potentiometric selectivities of ionophores. Ion-selective electrodes based on the cyclic peptide, cyclosporin A, were developed, and their potentiometric selectivity pattern was evaluated. Optimized electrodes demonstrated near-Nernstian slopes with micromolar detection limits toward calcium. ESI-MS and ESI-MS/MS were employed to determine the relative association strengths of cyclosporin A with various cations. The observed MS intensities of ion-ionophore complexes correlate favorably with the potentiometric selectivity pattern that was demonstrated by cyclosporin-based electrodes. This correlation was found to hold true for other established ionophores, such as valinomycin and benzo-18-crown-6. Taken together, these experiments demonstrate that mass spectrometry could be used to predict the selectivity patterns of new ionophores for potentiometric and optical ion sensors. Further, this approach could be useful in screening mixtures or libraries of newly-synthesized compounds to identify selective ionophores.

Comprehensive evaluation of ten docking programs on a diverse set of protein-ligand complexes: the prediction accuracy of sampling power and scoring power

As one of the most popular computational approaches in modern structure-based drug design, molecular docking can be used not only to identify the correct conformation of a ligand within the target binding pocket but also to estimate the strength of the interaction between a target and a ligand. Nowadays, as a variety of docking programs are available for the scientific community, a comprehensive understanding of the advantages and limitations of each docking program is fundamentally important to conduct more reasonable docking studies and docking-based virtual screening. In the present study, based on an extensive dataset of 2002 protein-ligand complexes from the PDBbind database (version 2014), the performance of ten docking programs, including five commercial programs (LigandFit, Glide, GOLD, MOE Dock, and Surflex-Dock) and five academic programs (AutoDock, AutoDock Vina, LeDock, rDock, and UCSF DOCK), was systematically evaluated by examining the accuracies of binding pose prediction (sampling power) and binding affinity estimation (scoring power). Our results showed that GOLD and LeDock had the best sampling power (GOLD: 59.8% accuracy for the top scored poses; LeDock: 80.8% accuracy for the best poses) and AutoDock Vina had the best scoring power (rp/rs of 0.564/0.580 and 0.569/0.584 for the top scored poses and best poses), suggesting that the commercial programs did not show the expected better performance than the academic ones. Overall, the ligand binding poses could be identified in most cases by the evaluated docking programs but the ranks of the binding affinities for the entire dataset could not be well predicted by most docking programs. However, for some types of protein families, relatively high linear correlations between docking scores and experimental binding affinities could be achieved. To our knowledge, this study has been the most extensive evaluation of popular molecular docking programs in the last five years. It is expected that our work can offer useful information for the successful application of these docking tools to different requirements and targets.

Drug-like properties: guiding principles for design - or chemical prejudice?

The concepts of 'drug-like' and 'lead-like' chemical properties are having a major influence on the selection of compounds for high-throughput screening, and in the design of lead generation libraries. Medicinal chemists are recycling 'privileged' drug-like structures, whilst aiming to seek optimal physical properties for oral delivery. This approach biases the chemical profiles of compound screening collections towards known structures. Novel library synthesis, creating new chemical classes to address intellectual property, toxicity issues, and less chemically tractable targets, though considered risky, is warranted.:

Are molecular alphabets universal enabling factors for the evolution of complex life?

Terrestrial biosystems depend on macromolecules, and this feature is often considered as a likely universal aspect of life. While opinions differ regarding the importance of small-molecule systems in abiogenesis, escalating biological functional demands are linked with increasing complexity in key molecules participating in biosystem operations, and many such requirements cannot be efficiently mediated by relatively small compounds. It has long been recognized that known life is associated with the evolution of two distinct molecular alphabets (nucleic acid and protein), specific sequence combinations of which serve as informational and functional polymers. In contrast, much less detailed focus has been directed towards the potential universal need for molecular alphabets in constituting complex chemically-based life, and the implications of such a requirement. To analyze this, emphasis here is placed on the generalizable replicative and functional characteristics of molecular alphabets and their concatenates. A primary replicative alphabet based on the simplest possible molecular complementarity can potentially enable evolutionary processes to occur, including the encoding of secondarily functional alphabets. Very large uniquely specified ('non-alphabetic') molecules cannot feasibly underlie systems capable of the replicative and evolutionary properties which characterize complex biosystems. Transitions in the molecular evolution of alphabets can be related to progressive bridging of barriers which enable higher levels of biosystem organization. It is thus highly probable that molecular alphabets are an obligatory requirement for complex chemically-based life anywhere in the universe. In turn, reference to molecular alphabets should be usefully applied in current definitions of life.

In situ click chemistry: a powerful means for lead discovery

Combinatorial chemistry and parallel synthesis are important and regularly applied tools for lead identification and optimisation, although they are often accompanied by challenges related to the efficiency of library synthesis and the purity of the compound library. In the last decade, novel means of lead discovery approaches have been investigated where the biological target is actively involved in the synthesis of its own inhibitory compound. These fragment-based approaches, also termed target-guided synthesis (TGS), show great promise in lead discovery applications by combining the synthesis and screening of libraries of low molecular weight compounds in a single step. Of all the TGS methods, the kinetically controlled variant is the least well known, but it has the potential to emerge as a reliable lead discovery method. The kinetically controlled TGS approach, termed in situ click chemistry, is discussed in this article.

Stilbene-chalcone hybrids: design, synthesis, and evaluation as a new class of antimalarial scaffolds that trigger cell death through stage specific apoptosis

Novel stilbene-chalcone (S-C) hybrids were synthesized via a sequential Claisen-Schmidt-Knoevenagel-Heck approach and evaluated for antiplasmodial activity in in vitro red cell culture using SYBR Green I assay. The most potent hybrid (11) showed IC(50) of 2.2, 1.4, and 6.4 μM against 3D7 (chloroquine sensitive), Indo, and Dd2 (chloroquine resistant) strains of Plasmodium falciparum, respectively. Interestingly, the respective individual stilbene (IC(50) > 100 μM), chalcone (IC(50) = 11.5 μM), or an equimolar mixture of stilbene and chalcone (IC(50) = 32.5 μM) were less potent than 11. Studies done using specific stage enriched cultures and parasite in continuous culture indicate that 11 and 18 spare the schizont but block the progression of the parasite life cycle at the ring or the trophozoite stages. Further, 11 and 18 caused chromatin condensation, DNA fragmentation, and loss of mitochondrial membrane potential in Plasmodium falciparum, thereby suggesting their ability to cause apoptosis in malaria parasite.

Computational medicinal chemistry in fragment-based drug discovery: what, how and when

The use of fragment-based drug discovery (FBDD) has increased in the last decade due to the encouraging results obtained to date. In this scenario, computational approaches, together with experimental information, play an important role to guide and speed up the process. By default, FBDD is generally considered as a constructive approach. However, such additive behavior is not always present, therefore, simple fragment maturation will not always deliver the expected results. In this review, computational approaches utilized in FBDD are reported together with real case studies, where applicability domains are exemplified, in order to analyze them, and then, maximize their performance and reliability. Thus, a proper use of these computational tools can minimize misleading conclusions, keeping the credit on FBDD strategy, as well as achieve higher impact in the drug-discovery process. FBDD goes one step beyond a simple constructive approach. A broad set of computational tools: docking, R group quantitative structure–activity relationship, fragmentation tools, fragments management tools, patents analysis and fragment-hopping, for example, can be utilized in FBDD, providing a clear positive impact if they are utilized in the proper scenario – what, how and when. An initial assessment of additive/non-additive behavior is a critical point to define the most convenient approach for fragments elaboration.

In situ click chemistry: probing the binding landscapes of biological molecules

Combinatorial approaches to the discovery of new functional molecules are well established among chemists and biologists, inspired in large measure by the modular composition of many systems and molecules in Nature. Many approaches rely on the synthesis and testing of individual members of a candidate combinatorial library, but attention has also been paid to techniques that allow the target to self-assemble its own binding agents. These fragment-based methods, grouped under the general heading of target-guided synthesis (TGS), show great promise in lead discovery applications. In this tutorial review, we review the use of the 1,3-dipolar cycloaddition reaction of organic azides and alkynes in a kinetically-controlled TGS approach, termed in situ click chemistry. The azide-alkyne reaction has several distinct advantages, most notably high chemoselectivity, very low background ligation rates, facile synthetic accessibility, and the stability and properties of the 1,2,3-triazole products. Examples of the discovery of potent inhibitors of acetylcholinesterases, carbonic anhydrase, HIV-protease, and chitinase are described, as are methods for the templated assembly of agents that bind DNA and proteins.

Kinetic target-guided synthesis

In the last decade, various target-guided synthesis (TGS) approaches have been developed in which a target protein is actively engaged in the assembly of its own bidentate ligand from a pool of smaller reactive fragments. Although TGS is relatively less explored, it demonstrates great promise to streamline drug discovery by combining screening and synthesis into a single step. Herein, we focus on the class of kinetic TGS approaches which utilize irreversible reactions to combine two reactive fragments into the inhibitory compound. These kinetic TGS applications have been successful due to the unique combination of the slow nature of the chemical reaction combining the two fragments into a single molecule and the use of reactive fragments displaying good affinities toward one of the binding sites. So far, kinetic TGS and especially in situ click chemistry, a kinetic TGS variant using the 1,3-dipolar cycloaddition of azides and alkynes, have led to the identification of highly potent inhibitors. This tutorial review focuses on kinetic TGS approaches aside from those employing the 1,3-dipolar cycloaddition of azides and alkynes, and discusses the features and advantages of these TGS approaches in detail.

The influence of lead discovery strategies on the properties of drug candidates

Despite the widespread acceptance of guidelines related to desirable physicochemical properties of potential small-molecule drugs, key properties - such as lipophilicity - of recently developed clinical candidates and advanced lead compounds have been shown to differ significantly from those of historical leads and drugs. By analysing the physicochemical properties of a large database of hits and corresponding leads identified in the past decade, we show that this undesirable phenomenon can be traced back to the nature of high-throughput screening hits and hit-to-lead optimization practices. Conceptual and organizational adjustments may be required to enable a smooth lead-evolution process that reduces the chance of high compound-related attrition in clinical trials.

Maximizing efficiency in the production of compound libraries

Efficiency is one of the most important criteria in departments responsible for the production of compounds in a library format. Consequently, this was a key factor in the initial design of our automated medicinal chemistry department, established some years ago. Nonetheless, we were able to improve and optimize our workflows and processes constantly. Here, we outline our current setup, from design to submission of libraries, and discuss which procedures and techniques appear to be useful for us and which ones turned out to be less effective. The aim of the manuscript is not to present individualized and tailor-made solutions in our laboratory but rather to describe approaches (often executed with commercial equipment) which might be of relevance for a broader readership working in this field.

Design and implementation of cell-based assays to model human disease

Cell-based assays, if appropriately designed, can be used to rapidly identify molecular mechanisms of human disease and develop novel therapeutics. In the last 20 years, many genes that cause or contribute to diverse disorders, including cancer and neurodegenerative disease, have been identified. With such genes in hand, scientists have created numerous model systems to dissect the molecular mechanisms of basic cellular and developmental biology. Meanwhile, techniques for high-throughput screening that use large chemical libraries have been developed, as have cDNA and RNA interference libraries that cover the entire human genome. By combining cell-based assays with chemical and genetic screens, we now have vastly improved our ability to dissect molecular mechanisms of disease and to identify therapeutic targets and therapeutic lead compounds. However, cell-based screening systems have yet to yield many fundamental insights into disease pathogenesis, and the development of therapeutic leads is frustratingly slow. This may be due to a failure of such assays to accurately reflect key aspects of pathogenesis. This Review attempts to guide the design of productive cellular models of human disease that may be used in high-throughput chemical and genetic screens. We emphasize two points: (i) model systems should use quantifiable molecular indicators of a pathogenic process, and (ii) small chemical libraries that include molecules with known biological activity and/or acceptable safety profiles are very useful.

Automated medicinal chemistry

With the advent of high throughput technologies in biological screening in the 1980s, providing sufficient numbers of small molecules for screening became a bottleneck in the drug discovery process. Combinatorial chemistry was the first attempt by chemists to address this issue. However, since its first applications, combinatorial chemistry has evolved rapidly into diverse fields. This review will focus on the evolution and the current status of what we refer to today as automated medicinal chemistry.

Hit discovery and hit-to-lead approaches

Hit discovery technologies range from traditional high-throughput screening to affinity selection of large libraries, fragment-based techniques and computer-aided de novo design, many of which have been extensively reviewed. Development of quality leads using hit confirmation and hit-to-lead approaches present their own challenges, depending on the hit discovery method used to identify the initial hits. In this paper, we summarize common industry practices adopted to tackle hit-to-lead challenges and review how the advantages and drawbacks of different hit discovery techniques could affect the various issues hit-to-lead groups face.

Yeast as a tool to uncover the cellular targets of drugs

Knowledge of the spectrum of cellular proteins targeted by experimental therapeutic agents would greatly facilitate drug development. However, identifying the targets of drugs is a daunting challenge. The yeast Saccharomyces cerevisiae is a valuable model organism for human diseases and pathways because it is genetically tractable and shares many functional homolog with humans. In yeast, it is possible to increase or decrease the expression level of essentially every gene and measure changes in drug sensitivity to uncover potential targets. It is also possible to infer mechanism of action from comparing the changes in mRNA expression elicited by drug treatment with those induced by gene deletions or by other drugs. Proteins that bind drugs directly can be identified using yeast protein chips. This review of the use of yeast for discovering targets of drugs discusses the advantages and drawbacks of each approach and how combining methods may reveal targets more efficiently.

An Ultraefficient Affinity-Based High-Throughout Screening Process: Application to Bacterial Cell Wall Biosynthesis Enzyme MurF

The authors describe the discovery of a new class of inhibitors to an essential Streptococcus pneumoniae cell wall biosyn-thesis enzyme, MurF, by a novel affinity screening method. The strategy involved screening very large mixtures of diverse small organic molecules against the protein target on the basis of equilibrium binding, followed by iterative ultrafiltration steps and ligand identification by mass spectrometry. Hits from any affinity-based screening method often can be relatively nonselective ligands, sometimes referred to as “nuisance” or “promiscuous” compounds. Ligands selective in their binding affinity for the MurF target were readily identified through electronic subtraction of an empirically determined subset of promiscuous compounds in the library without subsequent selectivity panels. The complete strategy for discovery and identification of novel specific ligands can be applied to all soluble protein targets and a wide variety of ligand libraries.

How good is your screening library?

Efficient library design is an ongoing challenge for investigators seeking novel ligands for proteins, whether for drug discovery or chemical biology. Strategies that add neglected chemistry or exclude unproductive compounds are two dominant recent themes, as is a growing awareness of molecular complexity and its implications. The choice of how complex molecules in screening libraries should be often amounts to how big they should be. Small, simple molecules have lower affinities and must be screened at high concentration, but they will also have higher hit rates. Larger compounds, on the other hand, will often more closely resemble final drugs, but because they are more highly functionalized and specific, they will have much lower hit rates. The best general-purpose screening libraries may well be those of intermediate complexity that are free of artifact-causing nuisance compounds.

High-Throughput Physical Organic Chemistry Hammett Parameter Evaluation

High-throughput analysis techniques were developed to allow the rapid assessment of a range of Hammett parameters utilizing positive electrospray mass spectrometry (ESI+ -MS) as the sole quantitative tool, with the core of the approach being a so-called "analytical construct". Hammett substituent parameters were determined for a range of meta- and para-substituted anilines by high-throughput (HT) assessment of relative reaction rates for competitive amide bond formation reaction with up to five parameters determined in a single pot reaction. Sensitivity of the reaction to substituents' effects (materialized by Hammett's rho parameter) was determined in the first instance, with HT Hammett's sigma substituent parameter assessment then carried out successfully for over 30 anilines, with excellent correlation observed between the HT ESI+ -MS method of determination and literature values.

Multi-target strategies for the improved treatment of depressive states: Conceptual foundations and neuronal substrates, drug discovery and therapeutic application

Major depression is a debilitating and recurrent disorder with a substantial lifetime risk and a high social cost. Depressed patients generally display co-morbid symptoms, and depression frequently accompanies other serious disorders. Currently available drugs display limited efficacy and a pronounced delay to onset of action, and all provoke distressing side effects. Cloning of the human genome has fuelled expectations that symptomatic treatment may soon become more rapid and effective, and that depressive states may ultimately be "prevented" or "cured". In pursuing these objectives, in particular for genome-derived, non-monoaminergic targets, "specificity" of drug actions is often emphasized. That is, priority is afforded to agents that interact exclusively with a single site hypothesized as critically involved in the pathogenesis and/or control of depression. Certain highly selective drugs may prove effective, and they remain indispensable in the experimental (and clinical) evaluation of the significance of novel mechanisms. However, by analogy to other multifactorial disorders, "multi-target" agents may be better adapted to the improved treatment of depressive states. Support for this contention is garnered from a broad palette of observations, ranging from mechanisms of action of adjunctive drug combinations and electroconvulsive therapy to "network theory" analysis of the etiology and management of depressive states. The review also outlines opportunities to be exploited, and challenges to be addressed, in the discovery and characterization of drugs recognizing multiple targets. Finally, a diversity of multi-target strategies is proposed for the more efficacious and rapid control of core and co-morbid symptoms of depression, together with improved tolerance relative to currently available agents.

Computational chemistry-driven decision making in lead generation

Novel starting points for drug discovery projects are generally found either by screening large collections of compounds or smaller more-focused libraries. Ideally, hundreds or even thousands of actives are initially found, and these need to be reduced to a handful of promising lead series. In several sequential steps, many actives are dropped and only some are followed up. Computational chemistry tools are used in this context to predict properties, cluster hits, design focused libraries and search for close analogues to explore the potential of hit series. At the end of hit-to-lead, the project must commit to one, or preferably a few, lead series that will be refined during lead optimization and hopefully produce a drug candidate. Striving for the best possible decision is crucial because choosing the wrong series is a costly one-way street.

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.

Solid-supported reagents and catalysts for the preparation of large ring compounds

Parallel combinatorial synthesis in solution using immobilized reagents, catalysts, and scavengers has emerged as a powerful technique for the preparation of diverse libraries of compounds. This technique has only recently been applied to the synthesis of large-ring compounds. In this comprehensive review several strategies are presented and discussed, including Pd-catalyzed allylic alkylation, Stille-coupling, macrolactonization and macrolactamization using solid supported reagents and catalysts. In several cases site isolation has allowed operation, of these macrocyclization reactions in concentrated solution (pseudo-dilution effect).

High Throughput Physical Organic Chemistry: Analytical Constructs for Monomer Reactivity Profiling

A polymer-supported analytical construct was used to quantify the reactivity of a range of monomers in the Ugi four-component condensation using positive electrospray ionization mass spectrometry (MS) as a quantitative analytical tool. The construct incorporated a bromo group to act as a peak splitter and a quaternary ammonium to act as a MS sensitizer and ionization leveler, thereby allowing direct quantitation of the cleaved adducts by MS. The relative reactivities of 10 carboxylic acids were quantified by the relative levels of product generated as determined by MS and 10 isonitriles, and 10 aldehydes were investigated in the same way. The effect of concentration variations on monomers reactivity and product profiles were rapidly determined using this approach, and the method opens up the way for studying, in a single pot, multiple reactions with a broad range of monomers under identical and self-consistent reaction conditions.

Exploring the chemogenomic knowledge space with annotated chemical libraries

The recent human genome initiatives have led to the discovery of a multitude of genes that are potentially associated with various pathologic conditions and, thus, have opened new horizons in drug discovery. Simultaneously, annotated chemical libraries have emerged as information-rich databases to integrate biological and chemical data. They can be useful for the discovery of new pharmaceutical leads, the validation of new biotargets and the determination of the structural basis of ligand selectivity within target families. Annotated libraries provide a strong information basis for computational design of target-directed combinatorial libraries, which are a key component of modern drug discovery. Today, the rational design of chemical libraries enhanced with chemogenomics data is a new area of progressive research.

Natural products and combinatorial chemistry: back to the future

The introduction of high-throughput synthesis and combinatorial chemistry has precipitated a global decline in the screening of natural products by the pharmaceutical industry. Some companies terminated their natural products program, despite the unproven success of the new technologies. This was a premature decision, as natural products have a long history of providing important medicinal agents. Furthermore, they occupy a complementary region of chemical space compared with the typical synthetic compound library. For these reasons, the interest in natural products has been rekindled. Various approaches have evolved that combine the power of natural products and organic chemistry, ranging from the combinatorial total synthesis of analogues to the exploration of natural product scaffolds and the design of completely unnatural molecules that resemble natural products in their molecular characteristics.

Applying combinatorial chemistry and biology to food research

In the past decade combinatorial chemistry has become a major focus of research activity in the pharmaceutical industry for accelerating the development of novel therapeutic compounds. The same combinatorial strategies could be applied to a broad spectrum of areas in agricultural and food research, including food safety and nutrition, development of product ingredients, and processing and conversion of natural products. In contrast to "rational design", the combinatorial approach relies on molecular diversity and high-throughput screening. The capability of exploring the structural and functional limits of a vast population of diverse chemical and biochemical molecules makes it possible to expedite the creation and isolation of compounds of desirable and useful properties. Several studies in recent years have demonstrated the utility of combinatorial methods for food research. These include the discovery of synthetic antimicrobial, antioxidative, and aflatoxin-binding peptides, the identification and analysis of unique flavor compounds, the generation of new enzyme inhibitors, the development of therapeutic antibodies for botulinum neurotoxins, the synthesis of unnatural polyketides and carotenoids, and the modification of food enzymes with novel properties. The results of such activities could open a large area of applications with potential benefits to the food industry. This review describes the current techniques of combinatorial chemistry and their applications, with emphasis on examples in food science research.

Disruption of Protein-Membrane Binding and Identification of Small-Molecule Inhibitors of Coagulation Factor VIII

Factor VIII is a critical member of the blood coagulation cascade. It binds to the membrane surfaces of activated platelets at the site of vascular injury via a highly specific interaction between factor VIII's carboxy-terminal C2 domain and their phosphatidylserine-rich lipid bilayer. We have identified small-molecule inhibitors of factor VIII's membrane binding activity that have IC50 values as low as 2.5 microM. This interaction is approximately 10(3)-fold tighter than that of free o-phospho-L-serine. These compounds also inhibit factor VIII-dependent activation of factor X, indicating that disruption of membrane lipid binding leads to inhibition of the intrinsic coagulation pathway. The tightest binding inhibitor is specific and does not prevent membrane binding by the closely related coagulation factor V. These results indicate that this and related compounds may be used as leads to develop novel antithrombotic agents.

Isolation of a library of aromadendranes from Landolphia dulcis and its characterization using the VolSurf approach

A library of nine aromadendrane-type sesquiterpenes (1-9), including eight new natural products (1-5 and 7-9), was isolated from Landolphia dulcis var. barteri along with a previously described cadinane derivative (10) and a new muurolane derivative (11). The structures of all compounds were established by means of NMR methods including COSY, NOESY, HSQC, and HMBC experiments, supported by HRMS and optical rotation data. Virtual characterization of the aromadendrane library (1-9) was performed using chemoinformatics tools. 3D molecular fields were calculated with the GRID program using low-energy structures obtained with the MMFF force field. VolSurf descriptors were calculated from the GRID maps and subsequently analyzed by multivariate statistics. The analysis disclosed the presence of a common motif for possible interactions of the aromadendranes with a putative target receptor. At the same time, a considerable chemical diversity within the library was disclosed, despite a close biosynthetic relationship of its members. The results can be interpreted in terms of evolutionary optimization of structures of secondary metabolites for interaction with macromolecular targets and are of interest in terms of assessment of potential "drug-likeness" of natural products.