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。     

Application of Combinatorial Technologies for Catalyst Design and Development

To increase the rate of materials discovery and optimization, different strategies and technologies for the combinatorial synthesis and evaluation of functional materials have been developed. In this article, the use of combinatorial techniques as a method for the high-speed chemical synthesis and high-throughput screening of new inorganic and organic catalysts is surveyed.     

Managing laboratory automation: integration and informatics in drug discovery

Drug discovery today requires the focused use of laboratory automation and other resources in combinatorial chemistry and high-throughput screening (HTS). The ultimate value of both combinatorial chemistry and HTS technologies and the lasting impact they will have on the drug discovery process is a chapter that remains to be written. Central to their success and impact is how well they are integrated with each other and with the rest of the drug discovery processes-informatics is key to this success. This presentation focuses on informatics and the integration of the disciplines of combinatorial chemistry and HTS in modern drug discovery. Examples from experiences at Neurogen from the last five years are described.     

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.     

Repertoires of aggregation-resistant human antibody domains

We recently described a method for the generation of a large human domain antibody repertoire involving combinatorial assembly of CDR building blocks from a smaller repertoire comprising a high frequency of aggregation-resistant antibody domains. Here we show that the frequency of aggregation-resistant domains in the combinatorial repertoire remained high. Furthermore, one of the antigen-binding domains selected from the combinatorial repertoire retained its binding properties through 25 cycles of thermal denaturation, suggesting that antibody domains can be created that rival the heat-resistance of thermophilic proteins such as Taq polymerase.     

Proteomic Tools for the Quantitative Analysis of Artificial Peptide Libraries: Detection and Characterization of Target-Amplified PD-1 Inhibitors

We report a quantitative proteomics data analysis pipeline, which coupled to protein-directed dynamic combinatorial chemistry (DDC) experiments, enables the rapid discovery and direct characterization of protein-protein interaction (PPI) modulators. A low-affinity PD-1 binder was incubated with a library of >100 D-peptides under thiol-exchange favoring conditions, in the presence of the target protein PD-1, and we determined the S-linked dimeric species that resulted, amplified in the protein samples versus the controls. We chemically synthesized the target dimer candidates and validated them by thermophoresis binding and protein-protein interaction assays. The results provide a proof-of-concept for using this strategy in the high-throughput search of improved drug-like peptide binders that block therapeutically relevant protein-protein interactions.     

组合催化的原理、策略与发展

介绍了组合催化的基本原理和催化剂库的高通量筛选方法;讨论了组合催化技术的2个关键因素———催化剂库的合成方法和相应的高通量检测技术在催化研究中的重要作用。综述了组合催化技术在无机、有机以及生物催化领域中的应用进展,指出进一步与计算机相结合,研究新的催化剂体系、开发新的催化剂合成技术和新的筛选技术是今后组合催化的发展方向和趋势。     

Simultaneous Disulfide and Boronic Acid Ester Exchange in Dynamic Combinatorial Libraries

Dynamic combinatorial chemistry has emerged as a promising tool for the discovery of complex receptors in supramolecular chemistry. At the heart of dynamic combinatorial chemistry are the reversible reactions that enable the exchange of building blocks between library members in dynamic combinatorial libraries (DCLs) ensuring thermodynamic control over the system. If more than one reversible reaction operates in a single dynamic combinatorial library, the complexity of the system increases dramatically, and so does its possible applications. One can imagine two reversible reactions that operate simultaneously or two reversible reactions that operate independently. Both these scenarios have advantages and disadvantages. In this contribution, we show how disulfide exchange and boronic ester transesterification can function simultaneous in dynamic combinatorial libraries under appropriate conditions. We describe the detailed studies necessary to establish suitable reaction conditions and highlight the analytical techniques appropriate to study this type of system.     

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.     

Computational chemistry, data mining, high-throughput synthesis and screening - informatics and integration in drug discovery

Drug discovery today includes considerable focus of laboratory automation and other resources on both combinatorial chemistry and high-throughput screening, and computational chemistry has been a part of pharmaceutical research for many years. The real benefit of these technologies is beyond the exploitation of each individually. Only recently have significant efforts focused on effectively integrating these and other discovery disciplines to realize their larger potential. This technical note will describe one example of these integration efforts.     

Combinatorial chemistry in the discovery and development of drugs

A Comprehensive review of the tractic and strategies that are available to the drug discovery process using combinatorial techniques.     

Fast NMR Methods for Measuring in the Direct and/or Competition Mode the Dissociation Constants of Chemical Fragments Interacting with a Receptor

Ligand-based NMR screening represents a powerful method in fragment-based drug discovery for the identification of chemical matter interacting with the receptor of interest. The large dynamic range of these methods allows the detection of weakly binding ligands. However, the methodology has not been extensively used for quantifying the strength of these interactions. This knowledge is important for ranking fragments according to their binding strength and for prioritizing structure-based and medicinal chemistry activities. Rapid NMR methods for measuring the dissociation constant in direct and competition modes are presented here. The theory underpinning these methods are presented, along with their application to the measurement of the binding affinities of several ligands of the heat shock protein 90.     

Vacuum and Pressured Combinatorial Processings for Exploration of Environmental Catalysts

Two types of combinatorial chemical reactors have been developed for high-throughput experimentation of catalysts that attract much interest from global environmental viewpoints. The high vacuum combinatorial laser MBE system was applied to the preparation of thin film library of TiO₂ with its film thickness gradually increased, which resulted in the discovery of new phenomenon indicating a quantum size effect in TiO₂ photo-catalysis. The combinatorial autoclave reactor was made to explore new catalysts and optimum reaction conditions efficiently for alternating CO₂ copolymerization with epoxide (oxirane) to form bio-degradable polycarbonates. Some preliminary results are reported on the CO₂ copolymerization with propylene oxide, as a means of CO₂ fixation into chemically useful material.     

In search of peptide-based catalysts for asymmetric organic synthesis

The discovery of short peptide sequences that function as asymmetric catalysts for a variety of reactions is documented. The evolution of the project from an exercise in rational design to an endeavor that combines combinatorial screening with various mechanism-based experiments is presented. The specific development of catalysts for enantioselective acylation, phosphorylation, conjugate addition, and Morita-Baylis-Hillman reactions is described.     

A loop-mimetic inhibitor of the HCV-NS3 protease derived from a minibody

We have been interested for some time in establishing a strategyfor deriving lead compounds from macromolecule ligands suchas minibody variants. A minibody is a minimized antibody variabledomain whose two loops are amenable to combinatorial mutagenesis.This approach can be especially useful when dealing with `difficult'targets. One such target is the NS3 protease of hepatitis Cvirus (HCV), a human pathogen that is believed to infect about100 million individuals worldwide and for which an effectivetherapy is not yet available. Based on known inhibitor specificity(residues P6-P1) of NS3 protease, we screened a number of minibodiesfrom our collection and we were able to identify a competitiveinhibitor of this enzyme. We thus validated an aspect of recognitionby HCV NS3 protease, namely that an acid anchor is necessaryfor inhibitor activity. In addition, the characterization ofthe minibody inhibitor led to the synthesis of a constrainedhexapeptide mimicking the bioactive loop of the parent macromolecule.The cyclic peptide is a lead compound prone to rapid optimizationthrough solid phase combinatorial chemistry. We therefore confirmedthat the potential of turning a protein ligand into a low molecularweight active compound for lead discovery is achievable andcan complement more traditional drug discovery approaches.     

The virtue of the multifunctional triazene linkers in the efficient solid-phase synthesis of heterocycle libraries

With the implementation of combinatorial chemistry into the modern drug discovery process, the approach to novel diverse heterocycle libraries is an indispensable requirement. Triazenes, which are concealed diazonium salts, can be used to link functionalized arenes and amines to generate various heterocyclic structures, namely, benzoannelated nitrogen heterocycles, upon cleavage from the resin. Since triazene anchors are stable toward various reagents and perform well under a range of reaction conditions, these multifunctional linkers are well suited for automated solid-phase syntheses and the syntheses of complex organic molecules, such as natural products, on solid supports.     

Analysis of high-affinity binding determinants in the receptor binding epitope of basic fibroblast growth factor

Basic fibroblast growth factor (bFGF) is implicated in the pathogenesis of several vascular and connective diseases. A key step in the discovery of bFGF receptor antagonists to mitigate these actions is to define the functional epitope required for receptor binding of the growth factor. In previous studies, we identified Glu96 as an essential residue in this epitope using site-directed mutagenesis. Here we examined the role of solvent accessible neighboring residues of Glu96 of bFGF on receptor binding affinity. Wild-type bFGF and its muteins were cloned and expressed in Escherichia coli and evaluated for FGF receptor binding affinity. Replacement of Asn104 of bFGF by alanine reduced receptor binding affinity over 400-fold compared with wild-type bFGF. We next explored the effect of neighboring residues of Asn104 on receptor binding affinity-Muteins in which Arg97, Leu98, Glu99, Asn101, Asn102, Thr105 and Pro141 were individually replaced by alanine exhibited receptor binding similar to wild-type bFGF. By contrast, substitution of Tyr103 or Leu140 by alanine reduced receptor binding affinity about 400- and 150-fold, respectively, in accord with a previous report. We conclude that at least six solvent-accessible residues in bFGF are crucial for high-affinity receptor binding, as evidenced by at least a 10-fold diminution in the affinity of the corresponding alanine muteins. The polar residues Glu96 and Asn104 appear to form an area important for facilitating the initial contact between ligand and receptor, whereas Tyr24, Tyr103, Leu140 and Met142 form a hydrophobic patch that may stabilize the complex. The detailed structure of this functional epitope can be employed in the discovery and design of bFGF antagonists using computational methods.      

SERS assisted ultra-fast peptidic screening: a new tool for drug discovery

Herein we present a direct label-free ultra-fast method for the identification and classification of the active members of a combinatorial library directly on the solid support used for their synthesis. The method is based on the appropriate functionalization of polyethylene glycol grafted polystyrene (TentaGel?) microbeads with Au@Ag nanoparticles, the use of these materials directly as solid-phase supports for the synthesis of combinatorial libraries of peptides and the subsequent SERS analysis for identification of each peptide on each bead.     

Conformationally restricted hydantoin-based peptidomimetics as inhibitors of caspase-3 with basic groups allowed at the S3 enzyme subsite

By using a combination of molecular modeling, combinatorial chemistry, and biological essays, novel scaffold molecules for the inhibition of caspase-3 have been developed. These compounds have an overall attenuated negative charge and show similar IC(50) values for both recombinant and human endogenous caspase-3. This might provide the basis for a novel strategy for the discovery of potent and more druglike inhibitors of caspase-3.     

DeepDISE: DNA Binding Site Prediction Using a Deep Learning Method

It is essential for future research to develop a new, reliable prediction method of DNA binding sites because DNA binding sites on DNA-binding proteins provide critical clues about protein function and drug discovery. However, the current prediction methods of DNA binding sites have relatively poor accuracy. Using 3D coordinates and the atom-type of surface protein atom as the input, we trained and tested a deep learning model to predict how likely a voxel on the protein surface is to be a DNA-binding site. Based on three different evaluation datasets, the results show that our model not only outperforms several previous methods on two commonly used datasets, but also demonstrates its robust performance to be consistent among the three datasets. The visualized prediction outcomes show that the binding sites are also mostly located in correct regions. We successfully built a deep learning model to predict the DNA binding sites on target proteins. It demonstrates that 3D protein structures plus atom-type information on protein surfaces can be used to predict the potential binding sites on a protein. This approach should be further extended to develop the binding sites of other important biological molecules.