天然活性成分作用靶点识别及确证方法的研究进展

药物靶标的发现和验证是新药研发的关键环节,对新药创制具有源头创新意义。天然产物是新药创制的重要来源,识别其作用靶点不仅为临床预防治疗提供可能新策略,也为进一步阐释中草药及其复方的作用特点及分子机制提供参考依据。随着生命科学和信息学的发展,药物靶点的识别及确证方法不断涌现,生物信息学、网络药理学、蛋白质组学、亲和色谱、药物亲和稳定性、芯片技术、基因敲除技术、RNA干扰等技术的广泛应用,越来越多的天然活性成分的靶点得以识别和验证。因此,本文对近五年来天然活性成分作用靶点识别及确证方法做一简要综述,以供参考。     

Affinity Selection and Mass Spectrometry-Based Strategies to Identify Lead Compounds in Combinatorial Libraries

The screening of diverse libraries of small molecules created by combinatorial synthetic methods is a recent development which has the potential to accelerate the identification of lead compounds in drug discovery. We have developed a direct and rapid method to identify lead compounds in libraries involving affinity selection and mass spectrometry. In our strategy, the receptor or target molecule of interest is used to isolate the active components from the library physically, followed by direct structural identification of the active compounds bound to the target molecule by mass spectrometry. In a drug design strategy, structurally diverse libraries can be used for the initial identification of lead compounds. Once lead compounds have been identified, libraries containing compounds chemically similar to the lead compound can be generated and used to optimize the binding characteristics. These strategies have also been adopted for more detailed studies of protein–ligand interactions.     

Recent advance in the discovery of tyrosinase inhibitors from natural sources via separation methods

Tyrosinase (TYR) inhibitors are in great demand in the food, cosmetic and medical industrials due to their important roles. Therefore, the discovery of high-quality TYR inhibitors is always pursued. Natural products as one of the most important sources of bioactive compounds discovery have been increasingly used for TYR inhibitors screening. However, due to their complex compositions, it is still a great challenge to rapid screening and identification of biologically active components from them. In recent years, with the help of separation technologies and the affinity and intrinsic activity of target enzymes, two advanced approaches including affinity screening and inhibition profiling showed great promises for a successful screening of bioactive compounds from natural sources. This review summarises the recent progress of separation-based methods for TYR inhibitors screening, with an emphasis on the principle, application, advantage, and drawback of each method along with perspectives in the future development of these screening techniques and screened hit compounds.     

Mapping protein-protein interactions by mass spectrometry

Mass spectrometry is currently at the forefront of technologies for mapping protein-protein interactions, as it is a highly sensitive technique that enables the rapid identification of proteins from a variety of biological samples. When used in combination with affinity purification and/or chemical cross-linking, whole or targeted protein interaction networks can be elucidated. Several methods have recently been introduced that display increased specificity and a reduced occurrence of false-positives. In the future, information gained from human protein interaction studies could lead to the discovery of novel pathway associations and therapeutic targets.     

Antibody discovery ex vivo accelerated by the LacO/LacI regulatory network

Monoclonal antibodies (mAbs) can be potent and highly specific therapeutics, diagnostics and research reagents. Nonetheless, mAb discovery using current in vivo or in vitro approaches can be costly and time-consuming, with no guarantee of success. We have established a platform for rapid discovery and optimization of mAbs ex vivo. This DTLacO platform derives from a chicken B cell line that has been engineered to enable rapid selection and seamless maturation of high affinity mAbs. We have validated the DTLacO platform by generation of high affinity and specific mAbs to five cell surface targets, the receptor tyrosine kinases VEGFR2 and TIE2, the glycoprotein TROP2, the small TNF receptor family member FN14, and the G protein-coupled receptor FZD10. mAb discovery is rapid and humanization is straightforward, establishing the utility of the DTLacO platform for identification of mAbs for therapeutic and other applications.     

Preparation of novel anthranilic acids as antibacterial agents: extensive evaluation of structural and physical properties on antibacterial activity and human serum albumin affinity

In the past few years a significant effort has been devoted by Pharmacia toward the discovery of novel antibiotics. We have recently described the identification of an anthranilic acid lead 1 and the optimization resulting in the advanced lead 2. In this report, we describe the preparation of several selected analogs to probe the dependency of this template for antibacterial activity and the affinity these compounds have for human serum albumin (HSA). These analogs illustrate that decreased affinity for HSA can be achieved while retaining relevant antibacterial activity. The most important factor for reduced HSA affinity is decrease in logP rather than a structural change.     

Tools and methodologies capable of isolating and identifying a target molecule for a bioactive compound

Elucidating the mechanism of action of bioactive compounds, such as commonly used pharmaceutical drugs and biologically active natural products, in the cells and the living body is important in drug discovery research. To this end, isolation and identification of target protein(s) for the bioactive compound are essential in understanding its function fully. And, development of reliable tools and methodologies capable of addressing efficiently identification and characterization of the target proteins based on the bioactive compounds accelerates drug discovery research. Affinity-based isolation and identification of target molecules for the bioactive compounds is a classic, but still powerful approach. This paper introduces recent progress on affinity chromatography system, focusing on development of practical affinity matrices and useful affinity-based methodologies on target identification. Beneficial affinity chromatography systems with using practical tools and useful methodologies facilitate chemical biology and drug discovery research.     

High throughput solution-based measurement of antibody-antigen affinity and epitope binning

Advances in human antibody discovery have allowed for the selection of hundreds of high affinity antibodies against many therapeutically relevant targets. This has necessitated the development of reproducible, high throughput analytical techniques to characterize the output from these selections. Among these characterizations, epitopic coverage and affinity are among the most critical properties for lead identification. Biolayer interferometry (BLI) is an attractive technique for epitope binning due to its speed and low antigen consumption. While surface-based methods such as BLI and surface plasmon resonance (SPR) are commonly used for affinity determinations, sensor chemistry and surface related artifacts can limit the accuracy of high affinity measurements. When comparing BLI and solution equilibrium based kinetic exclusion assays, significant differences in measured affinity (10-fold and above) were observed. KinExA direct association (k_a) rate constant measurements suggest that this is mainly caused by inaccurate k_a measurements associated with BLI related surface phenomena. Based on the kinetic exclusion assay principle used for KinExA, we developed a high throughput 96-well plate format assay, using a Meso Scale Discovery (MSD) instrument, to measure solution equilibrium affinity. This improved method combines the accuracy of solution-based methods with the throughput formerly only achievable with surface-based methods.     

RNA模式分析进展

研究表明,R N A模式在基因表达调控方面起着重要作用.由于RN A模式不仅与初级序列有关,更多的表现为高级结构(一般为二级结构)的保守性,所以R N A模式的识别比D N A模式的识别要复杂的多.近十几年里,对R N A模式分析作了大量的计算方面的研究,包括:R N A结构的预测、识别和已知的类型相似的R N A模式、在一组功能或进化相关的基因中找出共同的R N A模式.这里对上述3个方面的计算方法的发展和研究进行了综述.     

Current tools for the identification of miRNA genes and their targets

The discovery of microRNAs (miRNAs), almost 10 years ago, changed dramatically our perspective on eukaryotic gene expression regulation. However, the broad and important functions of these regulators are only now becoming apparent. The expansion of our catalogue of miRNA genes and the identification of the genes they regulate owe much to the development of sophisticated computational tools that have helped either to focus or interpret experimental assays. In this article, we review the methods for miRNA gene finding and target identification that have been proposed in the last few years. We identify some problems that current approaches have not yet been able to overcome and we offer some perspectives on the next generation of computational methods.     

Molecular identification of high and low affinity receptors for nicotinic acid

Nicotinic acid has been used clinically for over 40 years in the treatment of dyslipidemia producing a desirable normalization of a range of cardiovascular risk factors, including a marked elevation of high density lipoprotein and a reduction in mortality. The precise mechanism of action of nicotinic acid is unknown, although it is believed that activation of a G(i)-G protein-coupled receptor may contribute. Utilizing available information on the tissue distribution of nicotinic acid receptors, we identified candidate orphan receptors. The selected orphan receptors were screened for responses to nicotinic acid, in an assay for activation of G(i)-G proteins. Here we describe the identification of the G protein-coupled receptor HM74 as a low affinity receptor for nicotinic acid. We then describe the subsequent identification of HM74A in follow-up bioinformatics searches and demonstrate that it acts as a high affinity receptor for nicotinic acid and other compounds with related pharmacology. The discovery of HM74A as a molecular target for nicotinic acid may facilitate the discovery of superior drug molecules to treat dyslipidemia.     

NMR screening in drug discovery

NMR methods in drug discovery have traditionally been used to obtain structural information for drug targets or target-ligand complexes. Recently, it has been shown that NMR may be used as an alternative approach for identification of ligands that bind to protein drug targets, shifting the emphasis of many NMR laboratories towards screening and design of potential drug molecules, rather than structural characterization.     

Proteomic methods for drug target discovery

The field of drug target discovery is currently very popular with a great potential for advancing biomedical research and chemical genomics. Innovative strategies have been developed to aid the process of target identification, either by elucidating the primary mechanism-of-action of a drug, by understanding side effects involving unanticipated 'off-target' interactions, or by finding new potential therapeutic value for an established drug. Several promising proteomic methods have been introduced for directly isolating and identifying the protein targets of interest that are bound by active small molecules or for visualizing enzyme activities affected by drug treatment. Significant progress has been made in this rapidly advancing field, speeding the clinical validation of drug candidates and the discovery of the novel targets for lead compounds developed using cell-based phenotypic screens. Using these proteomic methods, further insight into drug activity and toxicity can be ascertained.     

Virtual screening strategies in drug discovery

The identification of novel therapeutic targets and characterization of their 3D structures is increasing at a dramatic rate. Computational screening methods continue to be developed and improved as credible and complementary alternatives to high-throughput biochemical compound screening (HTS). While the majority of drug candidates currently being developed have been found using HTS methods, high-throughput docking and pharmacophore-based searching algorithms are gaining acceptance and becoming a major source of lead molecules in drug discovery. Refinements and optimization of high-throughput docking methods have lead to improvements in reproducing experimental data and in hit rates obtained, validating their use in hit identification. In parallel with virtual screening methods, concomitant developments in cheminformatics including identification, design and manipulation of drug-like small molecule libraries have been achieved. Herein, currently used in silico screening techniques and their utility on a comparative and target dependent basis is discussed.     

Biotechnology techniques for the development of new tumor specific peptides

Peptides, proteins and antibodies are promising candidates as carriers for radionuclides in endoradiotherapy. This novel class of pharmaceuticals offers a great potential for the targeted therapy of cancer. The fact that some receptors are overexpressed in several tumor types and can be targeted by small peptides, proteins or antibodies conjugated to radionuclides has been used in the past for the development of peptide endoradiotherapeutic agents such as ⁹⁰Y-DOTATOC or radioimmunotherapy of lymphomas with Zevalin. These procedures have been shown to be powerful options for the treatment of cancer patients.Design of new peptide libraries and scaffolds combined with biopanning techniques like phage and ribosome display may lead to the discovery of new specific ligands for target structures overexpressed in malignant tumors. Display methods are high throughput systems which select for high affinity binders. These methods allow the screening of a vast amount of potential binding motifs which may be exposed to either cells overexpressing the target structures or in a cell-free system to the protein itself. Labelling these binders with radionuclides creates new potential tracers for application in diagnosis and endoradiotherapy. This review highlights the advantages and problems of phage and ribosome display for the identification and evaluation of new tumor specific peptides.     

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.     

MSblender: A probabilistic approach for integrating peptide identifications from multiple database search engines

Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for every possible PSM and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for most proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses.     

Affinity separation and enrichment methods in proteomic analysis

Protein separation or enrichment is one of the rate-limiting steps in proteomic studies. Specific capture and removal of highly-abundant proteins (HAP) with large sample-handling capacities are in great demand for enabling detection and analysis of low-abundant proteins (LAP). How to grasp and enrich these specific proteins or LAP in complex protein mixtures is also an outstanding challenge for biomarker discovery and validation. In response to these needs, various approaches for removal of HAP or capture of LAP in biological fluids, particularly in plasma or serum, have been developed. Among them, immunoaffinity subtraction methods based upon polyclonal IgY or IgG antibodies have shown to possess unique advantages for proteomic analysis of plasma, serum and other biological samples. In addition, other affinity methods that use recombinant proteins, lectins, peptides, or chemical ligands have also been developed and applied to LAP capture or enrichment. This review discusses in detail the need to put technologies and methods in affinity subtraction or enrichment into a context of proteomic and systems biology as "Separomics" and provides a prospective of affinity-mediated proteomics. Specific products, along with their features, advantages, and disadvantages will also be discussed.