Maximizing synthetic efficiency: multi-component transformations lead the way

With the emergence of high-throughput screening in the pharmaceutical industry in the early 1990's, organic chemists were faced with a new challenge: how to prepare large collections of molecules (the libraries) to "feed" the high-throughput screen? The unique exploratory power of some reactions (such as the 40 year-old Ugi four-component condensation) was soon recognized to be extremely valuable to produce libraries in a time- and cost-effective manner. Over the last five years, industrial and academic researchers have made these powerful transformations into one of the most efficient and cost-effective tools for combinatorial and parallel synthesis.     

2D and 3D spatially addressed arrays for high-throughput automated synthesis of combinatorial libraries

One of the key elements in the drug discovery process is the use of automation to synthesize libraries of compounds for biological screening. The "split-and-mix" approaches in combinatorial chemistry have been recognized as extremely powerful techniques to access large numbers of compounds, while requiring only few reaction steps. However, the need for effective encoding/deconvolution strategies and demands for larger amounts of compounds have somewhat limited the use of these techniques in the pharmaceutical industry. In this paper, we describe a concept of directed sort and combine synthesis with spatially arranged arrays of macroscopic supports. Such a concept attempts to balance the number of reaction steps, the confidence in compound identity, and the quantity of synthesized compounds. Using three-dimensional arrays of frames each containing a two-dimensional array of macroscopic solid supports, we have conceptualized and developed a modular semiautomated system with a capacity of up to 100 000 compounds per batch. Modularity of this system enables flexibility either to produce large diverse combinatorial libraries or to synthesize more focused smaller libraries, both as single compounds in 12-15 micromol quantities. This method using sortable and spatially addressed arrays is exemplified by the synthesis of a 15 360 compound library.     

Enhancement of combinatorial chemistry by microwave-assisted organic synthesis

It was in the 1980 s that the first papers in which the use of either combinatorial methods or microwave heating in organic chemistry were published. Unlike combinatorial chemistry, which quite readily became an accepted method, particularly in the pharmaceutical industry, it is only now that microwave heating is truly gaining acceptance. Our aim in this review is to attempt to rationalize this slow acceptance and to show the benefits to be gained by employing microwave heating in tandem with combinatorial chemistry. We will also give a number of examples of successful applications.     

The Application of Combinatorial Chemistry in Catalysis

In recent few years combinatorial methodology has been extensively used in material science research. Based on the desired properties of materials, various high throughput synthesizing and screening technologies were developed. These high throughput technologies can increase our speed to more than hundred folds for finding and optimizing materials. One of the most active areas is catalysis. Scientists are developing novel high throughput technologies to screen catalyst libraries to find and optimize new catalysts for chemical industry. In this area die key is combinatorial catalytic reactor design, catalyst library synthesis, and product detection. Systematic technologies for catalyst library synthesis and characterization were developed in our laboratory. In this work, catalyst in situ synthesis, parallel reactor design, and detection methods will be introduced. Combining with the powerful combinatorial methodology, good chemistry design will make our work even more efficient. Hence, as an example of combining combinatorial technologies with chemistry design, a successful catalyst design is also introduced.     

Combinatorial Materials Science and Catalysis

After forever changing the drug discovery process in the pharmaceutical industry, combinatorial chemistry methodologies are increasingly being applied to the discovery and optimization of more efficient catalysts and materials (see picture). With the advent of new combinatorial synthesis and screening technologies, coupled with integrated data management systems, the application of these technologies to materials science and catalyst research holds tremendous potential and brings high expectations to this new and exciting field.     

广义组合化学

积极合理运用组合学方法于化学领域的探索研究,可望产生许多新思想、新方法、新技术和新学科,这一现代“炼金术”是新世纪人类建设美好新生活的强有力杠杆。     

Electrochemical biosensors for food analysis

Abstract  Food analysis has become a very important and interesting area of research because of the rapid expansion of food trade and highly increased mobility of today’s populations. Food quality control is essential both for consumer protection and also for the food industry. Application of the electrochemical biosensors in the field of food analysis is promising. This review covers the recent developments and issues in electrochemical biosensors for food analysis, such as ease of preparation, robustness, sensitivity, and realization of mass production of the detection strategies. This review also emphasizes the current development of electrochemical biosensors combined with nanotechnology. Graphical abstract        

Luddite: an information-theoretic library design tool

We present an algorithm for the design of either combinatorial or discrete informative libraries. This approach is based on information theoretic techniques used extensively in coding theory. We have extended the information theoretic formalism to include an arbitrary number of property distribution constraints, such as Lipinski "drug-like" distributions. The method is demonstrated by comparing and contrasting a variety of different libraries selected from a single combinatorial source pool of compounds.     

Virtual darwinian drug design: QSAR inverse problem, virtual combinatorial chemistry, and computational screening

The generation of diversity and its further selection by an external system is a common mechanism for the evolution of the living species and for the current drug design methods. This assumption allows us to label the methods based on generation and selection of molecular diversity as "Darwinian" ones, and to distinguish them from the structure-based, structure-modulation approaches. An example of a Darwinian method is the inverse QSAR. It consists of the computational generation of candidate chemical structures and their selection according to a previously established QSAR model. New trends in the field of combinatorial chemical syntheses comprise the concepts of virtual combinatorial synthesis and virtual or computational screening. Virtual combinatorial synthesis, closely related to inverse QSAR, can be defined as the computational simulation of the generation of new chemical structures by using a combinatorial strategy to generate a virtual library. Virtual screening is the selection of chemical structures having potential desirable properties from a database or virtual library in order to be synthesized and assayed. This review is mainly focused on graph theoretical drug design approaches, but a survey with key references is provided that covers other simulation methods.     

Label-free detection of gliadin food allergen mediated by real-time apta-PCR

Celiac disease is an immune-mediated enteropathy triggered by the ingestion of gluten. The only effective treatment consists in a lifelong gluten-free diet, requiring the food industry to tightly control the gluten contents of their products. To date, several gluten quantification approaches using antibodies are available and recommended by the legal authorities, such as Codex Alimentarius. However, whilst these antibody-based tests exhibit high sensitivity and specificity, the production of antibodies inherently requires the killing of host animals and is time-consuming and relatively expensive. Aptamers are structured single-stranded nucleic acid ligands that bind with high affinity and specificity to their cognate target, and aiming for a cost-effective viable alternative to the use of antibodies. Herein, we report the systematic evolution of ligands by exponential enrichment (SELEX)-based selection of a DNA aptamer against gliadin from a combinatorial DNA library and its application in a novel detection assay. Taking into account the hydrophobic nature of the gliadin target, a microtitre plate format was exploited for SELEX, where the target was immobilised via hydrophobic interactions, thus exposing aptatopes accessible for interaction with the DNA library. Evolution was followed using surface plasmon resonance, and following eight rounds of SELEX, the enriched DNA pool was cloned, sequenced and a clear consensus motif was identified. An apta-PCR assay was developed where competition for the aptamer takes place between the surface-immobilised gliadin and gliadin in the target sample, akin to an ELISA competitive format where the more target present in the sample, the less aptamer will bind to the immobilised gliadin. Following competition, any aptamer bound to the immobilised gliadin was heat-eluted and quantitatively amplified using real-time PCR, achieving a detection limit of approx. 2 nM (100 ng mL^?1). The specificity of the selected aptamer was demonstrated and no cross-reactivity was observed with streptavidin, bovine serum albumin or anti-gliadin IgG.

Chemical Sensors for Electronic Nose Systems

Chemical sensors have been widely used for the analysis of volatile organic compounds. Employing chemical sensors in an array format with pattern recognition provides a higher degree of selectivity and reversibility leading to an extensive range of applications. When such systems are used for odour analysis they are termed electronic noses. Application of electronic noses ranges from the food industry, medical industry to environmental monitoring and process control. Many types of different gas sensors have been employed in the array. These include conducting polymers, metal oxide semiconductors, piezoelectric, optical fluorescence and amperometric gas sensors The transducer principle of these sensors is varied and is discussed in detail within this review. Examples of the current trends in sensor array technology as well as the applications to which the sensor-based noses have been applied are also discussed.     

Combinatorial Materials Research in the Polymer Industry: Speed versus Flexibility

With combinatorial materials research (CMR), a new research approach toward the development and optimization of materials has been established at BASF. While adopting the basic ideas of combinatorial chemistry, CMR faces a whole bunch of challenges throughout the entire combinatorial process loop. New concepts for sample preparation on a smaller scale, i.e. synthesis and formulation, for parallel or fast sequential screening and characterization, and for appropriate management of yet unknown amounts of data have been developed. The integration of as many as possible workflow steps and the interplay of experts from various relevant fields, such as chemistry, engineering, robotics, informatics, and physics, are necessary. First results in the fields of polymer synthesis and coatings formulation give an impression of the innovative power and efficiency of this new kind of research.

     

Computational combinatorial ligand design: Application to human α-thrombin

Summary A new method is presented for computer-aided ligand design by combinatorial selection of fragments that bind favorably to a macromolecular target of known three-dimensional structure. Firstly, the multiple-copy simultaneous-search procedure (MCSS) is used to exhaustively search for optimal positions and orientations of functional groups on the surface of the macromolecule (enzyme or receptor fragment). The MCSS minima are then sorted according to an approximated binding free energy, whose solvation component is expressed as a sum of separate electrostatic and nonpolar contributions. The electrostatic solvation energy is calculated by the numerical solution of the linearized Poisson-Boltzmann equation, while the nonpolar contribution to the binding free energy is assumed to be proportional to the loss in solvent-accessible surface area. The program developed for computational combinatorial ligand design (CCLD) allows the fast and automatic generation of a multitude of highly diverse compounds, by connecting in a combinatorial fashion the functional groups in their minimized positions. The fragments are linked as two atoms may be either fused, or connected by a covalent bond or a small linker unit. To avoid the combinatorial explosion problem, pruning of the growing ligand is performed according to the average value of the approximated binding free energy of its fragments. The method is illustrated here by constructing candidate ligands for the active site of human -thrombin. The MCSS minima with favorable binding free energy reproduce the interaction patterns of known inhibitors. Starting from these fragments, CCLD generates a set of compounds that are closely related to high-affinity thrombin inhibitors. In addition, putative ligands with novel binding motifs are suggested. Probable implications of the MCSS-CCLD approach for the evolving scenario of drug discovery are discussed.     

食品中7种常见的非食用色素检测研究进展

食用色素可以明显的改善食品外观,激发食欲,在食品行业有着广泛的应用,但一些不法分子为了牟取暴利向食品中添加非食用色素来代替食用色素,但是非食用色素对人体存在致癌风险。食品中常见的非食用色素有以下7种：碱性嫩黄O、碱性橙II、酸性橙II、苏丹红、罗丹明B、美术绿和孔雀石绿,而目前对这7种非食用色素的检测还未全部建立国家标准。本文综述了近3年来食品行业中针对这7种非食用色素的各种检验方法,以期为食品安全监督监督检测机构提供参考。     

Production and certification of “fresh” reference material for macronutrient analysis

Summary Reference materials for carrying out in-house quality assurance by food laboratories that analyse macronutrients have to date been inadequate. The freeze-dried, very specialized, materials that exist on the market are not always comparable with ordinary food products analysed at those laboratories.A homogeneous, fresh, canned meat material was produced by an ordinary cannery. The total amount of material (pork, nitrite salt and water) was 1700 kg. During production, the fat content was continuously analysed in the different sub-batches and combinations are made accordingly. The material was packed in tin cans containing 200 g, and tested for homogeneity. The shelf life is, by experience, at least five years. A large number of authorized public and industry laboratories participated in the certification procedure. For each constituent different types of standard analytical methods were used. The material is offered for sale together with a certificate, giving mean values for moisture, ash, fat, nitrogen, sodium, sodium chloride and hydroxyproline content. The uncertainty is given as standard deviations including the analytical error and the variations between laboratories, methods and units.     

Natural product drug discovery in the artificial intelligence era

Natural products (NPs) are primarily recognized as privileged structures to interact with protein drug targets. Their unique characteristics and structural diversity continue to marvel scientists for developing NP-inspired medicines, even though the pharmaceutical industry has largely given up. High-performance computer hardware, extensive storage, accessible software and affordable online education have democratized the use of artificial intelligence (AI) in many sectors and research areas. The last decades have introduced natural language processing and machine learning algorithms, two subfields of AI, to tackle NP drug discovery challenges and open up opportunities. In this article, we review and discuss the rational applications of AI approaches developed to assist in discovering bioactive NPs and capturing the molecular “patterns” of these privileged structures for combinatorial design or target selectivity.

Natural products (NPs) are primarily recognized as privileged structures to interact with protein drug targets.     

Studies on some microbiological and chemical aspects of irradiated vanilla beans

Vanilla bean is a valuable food additive used in many branches of food industry as a source of natural vanillin. The influence of⁶⁰Co -radiation in the dose range of 5–50 kGy has been investigated on: (1) the survival of contaminating microflora, and (2) more important vanilla constituents like vanillin and sugars. It has been found that the main vanilla contamination is connected with mesophylic microorganisms in the amount of 8.4·10⁴/g. The dose of 15 kGy is sufficient for decontamination of commercial raw material. The samples under investigation on account of sensory properties and chemical composition were in agreement with country regulations. Doses up to 50 kGy do not cause undesirable changes in the content of sugars and vanillin, which has been confirmed by studies on model compounds.     

Natural gum reduced/stabilized gold nanoparticles for drug delivery formulations

"Gellan Gum", widely used in food and confectionary industry as a thickening and gelling agent, has been employed as a reducing and stabilizing agent for the synthesis of gold nanoparticles. These nanoparticles display greater stability to electrolyte addition and pH changes relative to the traditional citrate and borohydride reduced nanoparticles. Subsequently these have been used to load anthracycline ring antibiotic doxorubicin hydrochloride. The drug loaded on these nanoparticles showed enhanced cytotoxic effects on human glioma cell lines LN-18 and LN-229.