组合化学及其在新农药开发中的应用

结合医药领域的成功经验概述了组合化学的基本概念、化合物库的合成技术与分析、筛选方法，综述了组合化学方法在发现与优化新农药先导化合物中的研究进展，介绍了作者利用互补分子反应活性与分子识别技术优化除草活性原卟啉原氧化酶抑制剂的研究工作，展望了组合化学在新农药创制中的应用前景。     

The development of coatings using combinatorial/high throughput methods: a review of the current status

Combinatorial chemistry is a relatively new experimental methodology developed by academics and researchers in the pharmaceutical industry to reduce the time and cost associated with drug development. Basically, combinatorial chemistry involves the rapid synthesis and evaluation of large numbers of compounds in parallel using robotics, rapid analytical instrumentation, and data management software. More recently, the principles of combinatorial chemistry have been applied to materials development, and interest in this area is increasing rapidly. This interest can be attributed to the potential for obtaining a major competitive advantage by implementing a combinatorial approach. This document provides an introduction to combinatorial materials science and provides a review of efforts aimed at developing combinatorial workflows for coating development. While the application of combinatorial methods to coating development is still in its infancy, full combinatorial workflows have been developed within a few different organizations. Presented at the 2006 FutureCoat! conference, sponsored by the Federation of Societies for Coatings Technology, in New Orleans, LA, on November 1–3, 2006.     

Discovery of Akt Kinase Inhibitors through Structure-Based Virtual Screening and Their Evaluation as Potential Anticancer Agents

Akt acts as a pivotal regulator in the PI3K/Akt signaling pathway and represents a potential drug target for cancer therapy. To search for new inhibitors of Akt kinase, we performed a structure-based virtual screening using the DOCK 4.0 program and the X-ray crystal structure of human Akt kinase. From the virtual screening, 48 compounds were selected and subjected to the Akt kinase inhibition assay. Twenty-six of the test compounds showed more potent inhibitory effects on Akt kinase than the reference compound, H-89. These 26 compounds were further evaluated for their cytotoxicity against HCT-116 human colon cancer cells and HEK-293 normal human embryonic kidney cells. Twelve compounds were found to display more potent or comparable cytotoxic activity compared to compound H-89 against HCT-116 colon cancer cells. The best results were obtained with Compounds a46 and a48 having IC₅₀ values (for HCT-116) of 11.1 and 9.5 µM, respectively, and selectivity indices (IC₅₀ for HEK-293/IC₅₀ for HCT-116) of 12.5 and 16.1, respectively. Through structure-based virtual screening and biological evaluations, we have successfully identified several new Akt inhibitors that displayed cytotoxic activity against HCT-116 human colon cancer cells. Especially, Compounds a46 and a48 may serve as useful lead compounds for further development of new anticancer agents.     

Comparison of Structure‐ and Ligand‐Based Virtual Screening Protocols Considering Hit List Complementarity and Enrichment Factors

Structure‐ and ligand‐based virtual‐screening methods (docking, 2D‐ and 3D‐similarity searching) were analysed for their effectiveness in virtual screening against four different targets: angiotensin‐converting enzyme (ACE), cyclooxygenase 2 (COX‐2), thrombin and human immunodeficiency virus 1 (HIV‐1) protease. The relative performance of the tools was compared by examining their ability to recognise known active compounds from a set of actives and nonactives. Furthermore, we investigated whether the application of different virtual‐screening methods in parallel provides complementary or redundant hit lists. Docking was performed with GOLD, Glide, FlexX and Surflex. The obtained docking poses were rescored by using nine different scoring functions in addition to the scoring functions implemented as objective functions in the docking algorithms. Ligand‐based virtual screening was done with ROCS (3D‐similarity searching), Feature Trees and Scitegic Functional Fingerprints (2D‐similarity searching). The results show that structure‐ and ligand‐based virtual‐screening methods provide comparable enrichments in detecting active compounds. Interestingly, the hit lists that are obtained from different virtual‐screening methods are generally highly complementary. These results suggest that a parallel application of different structure‐ and ligand‐based virtual‐screening methods increases the chance of identifying more (and more diverse) active compounds from a virtual‐screening campaign.     

Design of new catalysts for ecological high-quality transportation fuels by combinatorial computational chemistry and tight-binding quantum chemical molecular dynamics approaches

Recently, we introduced a concept of combinatorial chemistry to computational chemistry and proposed a new method called “combinatorial computational chemistry”, which enables us to perform a theoretical high-throughput screening of catalysts. In the present paper, we reviewed our recent application of our combinatorial computational chemistry approach to the design of new catalysts for high-quality transportation fuels. By using our combinatorial computational chemistry techniques, we succeeded to predict new catalysts for methanol synthesis and Fischer–Tropsch synthesis. Moreover, we have succeeded in the development of chemical reaction dynamics simulator based on our original tight-binding quantum chemical molecular dynamics method. This program realizes more than 5000 times acceleration compared to the regular first-principles molecular dynamics method. Electronic- and atomic-level information on the catalytic reaction dynamics at reaction temperatures significantly contributes the catalyst design and development. Hence, we also summarized our recent applications of the above quantum chemical molecular dynamics method to the clarification of the methanol synthesis dynamics in this review.     

Library Screening by Means of Mass Spectrometry (MS) Binding Assays-Exemplarily Demonstrated for a Pseudostatic Library Addressing γ-Aminobutyric Acid (GABA) Transporter 1 (GAT1)

In the present study, the application of mass spectrometry (MS) binding assays as a tool for library screening is reported. For library generation, dynamic combinatorial chemistry (DCC) was used. These libraries can be screened by means of MS binding assays when appropriate measures are taken to render the libraries pseudostatic. That way, the efficiency of MS binding assays to determine ligand binding in compound screening with the ease of library generation by DCC is combined. The feasibility of this approach is shown for γ‐aminobutyric acid (GABA) transporter 1 (GAT1) as a target, representing the most important subtype of the GABA transporters. For the screening, hydrazone libraries were employed that were generated in the presence of the target by reacting various sets of aldehydes with a hydrazine derivative that is delineated from piperidine‐3‐carboxylic acid (nipecotic acid), a common fragment of known GAT1 inhibitors. To ensure that the library generated is pseudostatic, a large excess of the nipecotic acid derivative is employed. As the library is generated in a buffer system suitable for binding and the target is already present, the mixtures can be directly analyzed by MS binding assays—the process of library generation and screening thus becoming simple to perform. The binding affinities of the hits identified by deconvolution were confirmed in conventional competitive MS binding assays performed with single compounds obtained by separate synthesis. In this way, two nipecotic acid derivatives exhibiting a biaryl moiety, 1‐{2‐[2′‐(1,1’‐biphenyl‐2‐ylmethylidene)hydrazine]ethyl}piperidine‐3‐carboxylic acid and 1‐(2‐{2′‐[1‐(2‐thiophenylphenyl)methylidene]hydrazine}ethyl)piperidine‐3‐carboxylic acid, were found to be potent GAT1 ligands exhibiting pK_i values of 6.186±0.028 and 6.229±0.039, respectively. This method enables screening of libraries, whether generated by conventional chemistry or DCC, and is applicable to all kinds of targets including membrane‐bound targets such as G protein coupled receptors (GPCRs), ion channels and transporters. As such, this strategy displays high potential in the drug discovery process.     

Internet上的化学化工信息资源(续前)

Ｉｎｔｅｒｎｅｔ上的化学化工信息资源（续前）汝天张汝琴（化工部晨光化工研究院成都６１００４１）（上接１９９７年第６期第１７页）２．３Ｉｎｔｅｒｎｅｔ上的期刊文献及Ｕｎｃｏｖｅｒ文章拷贝服务在虚拟图书馆中专门列有期刊类Ｐｅｒｉｏｄｉ－ｃａｌｓ（ｈｔｔｐ...     

A Combinatorial Virtual Screening Approach Driving the Synthesis of 2,4-Thiazolidinedione-Based Molecules as New Dual mPGES-1/5-LO Inhibitors

Dual inhibition of microsomal prostaglandin E₂ synthase-1 (mPGES-1) and 5-lipoxygenase (5-LO), two key enzymes involved in pro-inflammatory eicosanoid biosynthesis, represents a new strategy for treating inflammatory disorders. Herein we report the discovery of 2,4-thiazolidinedione-based mPGES-1/5-LO dual inhibitors following a multidisciplinary protocol, involving virtual combinatorial screening, chemical synthesis, and validation of the biological activities for the selected compounds. Following the multicomponent-based chemical route for the decoration of the 2,4-thiazolidinedione core, a large library of virtual compounds was built (∼2.0×10⁴ items) and submitted to virtual screening. Nine selected molecules were synthesized and biologically evaluated, disclosing among them four compounds able to reduce the activity of both enzymes in the mid- and low- micromolar range of activities. These results are of interest for further expanding the chemical diversity around the 2,4-thiazolidinedione central core, facilitating the identification of novel anti-inflammatory agents endowed with a promising and safer pharmacological profile.     

A Minimalist Approach to the Design of Complexity‐Enriched Bioactive Small Molecules: Discovery of Phenanthrenoid Mimics as Antiproliferative Agents

Over the last decades, much effort has been devoted to the design of the “ideal” library for screening, the most promising strategies being those which draw inspiration from biogenic compounds, as the aim is to add biological relevance to such libraries. On the other hand, there is a growing understanding of the role that molecular complexity plays in the discovery of new bioactive small molecules. Nevertheless, the introduction of molecular complexity must be balanced with synthetic accessibility. In this work, we show that both concepts can be efficiently merged—in a minimalist way—by using very simple guidelines during the design process along with the application of multicomponent reactions as key steps in the synthetic process. Natural phenanthrenoids, a class of plant aromatic metabolites, served as inspiration for the synthesis of a library in which complexity‐enhancing features were introduced in few steps using multicomponent reactions. These resulting chemical entities were not only more complex than the parent natural products, but also interrogated an alternative region of the chemical space, which led to an outstanding hit rate in an antiproliferative assay: four out of twenty‐six compounds showed in vitro activity, one of them being more potent than the clinically useful drug 5‐fluorouracil.     

Chemical Synthesis in Micro Reactors

This article reviews the current applications of micro reactors in the field of combinatorial chemistry and discusses how the methodology could be applied to drug discovery. Liquid phase reactions have been used to illustrate the advantages of performing chemical reactions in micro reactors which illustrate that reactions can be performed very rapidly in high conversion to enable the preparation of combinatorial libraries of structurally related compounds.     

Combinatorial chemistry methods for coating development: VI. Correlation of high throughput screening methods with conventional measurement techniques

Combinatorial chemistry has proven to be a valuable tool for the development of new compounds. In the pharmaceutical industry, where combinatorial chemistry began, the approach has been instrumental in the high-speed development of new drugs. Due to the overwhelming success of the combinatorial methodology in the pharmaceutical industry, it has been recently applied to materials development. We have recently developed a combinatorial factory capable of preparing and evaluating on the order of 100 organic clear coatings in a day.

One of the most challenging aspects of the creation of the combinatorial factory was the development of the high throughput screening (HTS) methods for the primary coating properties of interest such as optical clarity, abrasion resistance, adhesion, and weatherability. For each property, an entirely new method was developed that allowed for rapid measurement of these properties on very small samples. This paper describes various aspects of the development of these novel measurement systems including the correlation of the HTS methods with conventional, industry standard measurement methods.     

Promoting GAINs (Give Attention to Limitations in Assays) over PAINs Alerts: no PAINS,more GAINs

Many concepts and guidelines in medicinal chemistry have been introduced to aid in successful drug discovery and development. An example is the concept of Pan-Assay Interference Compounds (PAINS) and the elimination of such nuisance compounds from high-throughput screening (HTS) libraries. PAINs, along with other guidelines in medicinal chemistry, are like double-edged swords. If used appropriately, they may be beneficial for drug discovery and development. However, rigid and blind use of such concepts can hinder productivity. In this perspective, we introduce GAINS ( g ive a ttention to l i mitatio n s in assay s ) and highlight its relevance for successful drug discovery.     

Machine Learning-Based Virtual Screening for the Identification of Cdk5 Inhibitors

Cyclin-dependent kinase 5 (Cdk5) is an atypical proline-directed serine/threonine protein kinase well-characterized for its role in the central nervous system rather than in the cell cycle. Indeed, its dysregulation has been strongly implicated in the progression of synaptic dysfunction and neurodegenerative diseases, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD), and also in the development and progression of a variety of cancers. For this reason, Cdk5 is considered as a promising target for drug design, and the discovery of novel small-molecule Cdk5 inhibitors is of great interest in the medicinal chemistry field. In this context, we employed a machine learning-based virtual screening protocol with subsequent molecular docking, molecular dynamics simulations and binding free energy evaluations. Our virtual screening studies resulted in the identification of two novel Cdk5 inhibitors, highlighting an experimental hit rate of 50% and thus validating the reliability of the in silico workflow. Both identified ligands, compounds CPD1 and CPD4, showed a promising enzyme inhibitory activity and CPD1 also demonstrated a remarkable antiproliferative activity in ovarian and colon cancer cells. These ligands represent a valuable starting point for structure-based hit-optimization studies aimed at identifying new potent Cdk5 inhibitors.     

VirtualFlow Ants—Ultra-Large Virtual Screenings with Artificial Intelligence Driven Docking Algorithm Based on Ant Colony Optimization

The docking program PLANTS, which is based on ant colony optimization (ACO) algorithm, has many advanced features for molecular docking. Among them are multiple scoring functions, the possibility to model explicit displaceable water molecules, and the inclusion of experimental constraints. Here, we add support of PLANTS to VirtualFlow (VirtualFlow Ants), which adds a valuable method for primary virtual screenings and rescoring procedures. Furthermore, we have added support of ligand libraries in the MOL2 format, as well as on the fly conversion of ligand libraries which are in the PDBQT format to the MOL2 format to endow VirtualFlow Ants with an increased flexibility regarding the ligand libraries. The on the fly conversion is carried out with Open Babel and the program SPORES. We applied VirtualFlow Ants to a test system involving KEAP1 on the Google Cloud up to 128,000 CPUs, and the observed scaling behavior is approximately linear. Furthermore, we have adjusted several central docking parameters of PLANTS (such as the speed parameter or the number of ants) and screened 10 million compounds for each of the 10 resulting docking scenarios. We analyzed their docking scores and average docking times, which are key factors in virtual screenings. The possibility of carrying out ultra-large virtual screening with PLANTS via VirtualFlow Ants opens new avenues in computational drug discovery.     

Solid-phase synthesis of sulfur containing heterocycles

Solid-phase organic synthesis by combinatorial techniques is a widely exploited area in the discovery of new pharmacologically active compounds and is a rapidly expanding area of synthetic organic chemistry. Because of many biological activities possessed by heterocycles, a large number of reports related to their solid-phase synthesis have appeared in recent decades. In this review article, I have described the importance of solid-phase synthetic strategies for the synthesis of sulfur atom containing heterocycles.     

Drug design strategies for targeting G-protein-coupled receptors

G-protein-coupled receptors (GPCRs) form a large protein family that plays an important role in many physiological and pathophysiological processes. Since the sequencing of the human genome has revealed several hundred new members of this receptor family, many new opportunities for developing novel therapeutics have emerged. The increasing knowledge of GPCRs (biological target space) and their ligands (chemical ligand space) enables novel drug design strategies to accelerate the finding and optimization of GPCR leads: The crystal structure of rhodopsin provides the first three-dimensional GPCR information, which now supports homology modeling studies and structure-based drug design approaches within the GPCR target family. On the other hand, the classical ligand-based design approaches (for example, virtual screening, pharmacophore modeling, quantitative structure-activity relationship (QSAR)) are still powerful methods for lead finding and optimization. In addition, the cross-target analysis of GPCR ligands has revealed more and more common structural motifs and three-dimensional pharmacophores. Such GPCR privileged structural motifs have been successfully used by many pharmaceutical companies to design and synthesize combinatorial libraries, which are subsequently tested against novel GPCR targets for lead finding. In the near future structural biology and chemogenomics might allow the mapping of the ligand binding to the receptor. The linking of chemical and biological spaces will aid in generating lead-finding libraries, which are tailor-made for their respective receptor.     

Modeling natural anti-inflammatory compounds by molecular topology

One of the main pharmacological problems today in the treatment of chronic inflammation diseases consists of the fact that anti-inflammatory drugs usually exhibit side effects. The natural products offer a great hope in the identification of bioactive lead compounds and their development into drugs for treating inflammatory diseases. Computer-aided drug design has proved to be a very useful tool for discovering new drugs and, specifically, Molecular Topology has become a good technique for such a goal. A topological-mathematical model, obtained by linear discriminant analysis, has been developed for the search of new anti-inflammatory natural compounds. An external validation obtained with the remaining compounds (those not used in building up the model), has been carried out. Finally, a virtual screening on natural products was performed and 74 compounds showed actual anti-inflammatory activity. From them, 54 had been previously described as anti-inflammatory in the literature. This can be seen as a plus in the model validation and as a reinforcement of the role of Molecular Topology as an efficient tool for the discovery of new anti-inflammatory natural compounds.