MicroRNA定量检测方法的研究进展

MicroRNA是一类内源性的非编码小分子RNA, 通过下调蛋白编码基因的表达而对不同的细胞发育过程起到重要的调控作用。分析组织或细胞样本中microRNA的表达可为研究这类分子的生物学功能提供重要的信息。近年来, 研究者发展了许多方法检测不同的生理和病理学过程中microRNA的表达差异, 并发现microRNA的异常表达与癌症、神经紊乱和心脏疾病等的发生相关。文章系统地介绍了最新发展的microRNA定量检测方法, 详细阐述了基于探针杂交技术的Northern blotting法、微阵列芯片法、纳米金标记法、桥连同位素标记法, 以及基于扩增技术的定量PCR检测法、滚环扩增法、引物入侵法和新一代大规模高通量测序法等, 并对这些方法的优缺点进行了分析比较。     

MicroRNAs研究方法与技术

MicroRNAs简称miRNAs(微小RNAs),是真核生物、原核生物以及病毒中由非编码蛋白基因转录的初级microRNAs加工成的调控因子.在转录后水平和蛋白质翻译水平,microRNAs通过降解或翻译抑制甚至激活来调控靶mRNA.实验和计算机方法已应用于microRNAs和靶基因的鉴定.大规模测序技术使得microRNAs在不同物种的多样性分析得以实现.着重介绍microRNAs、靶基因及其功能研究的实验技术和计算机方法,以及基于microRNAs的保守性,借助模式生物中已知的microRNAs,研究其在其他生物中的功能和作用.     

Combinatorial approaches to materials discovery

Using a mixture of scientific intuition, iteration and serendipity, combinatorial materials science is an approach to the discovery and study of new materials that combines high-speed chemical synthesis, high-throughput screening and high-capacity information processing to create, analyse and interpret large numbers of new and diverse material compositions. Technology has now been developed that makes this powerful integration possible. The classes of materials under investigation include catalysts, luminescent, optical, magnetic and dielectric materials, and structural polymers.     

New approaches to antibiotic discovery

New antibiotics are urgently required by human medicine as pathogens emerge with developed resistance to almost all antibiotic classes. Pioneering approaches, methodologies and technologies have facilitated a new era in antimicrobial discovery. Innovative culturing techniques such as iChip and co-culturing methods which use ‘helper’ strains to produce bioactive molecules have had notable success. Exploiting antibiotic resistance to identify antibacterial producers performed in tandem with diagnostic PCR based identification approaches has identified novel candidates. Employing powerful metagenomic mining and metabolomic tools has identified the antibiotic’ome, highlighting new antibiotics from underexplored environments and silent gene clusters enabling researchers to mine for scaffolds with both a novel mechanism of action and also few clinically established resistance determinants. Modern biotechnological approaches are delivering but will require support from government initiatives together with changes in regulation to pave the way for valuable, efficacious, highly targeted, pathogen specific antimicrobial therapies.     

microRNA计算发现方法的研究进展

microRNA (miRNA)是近几年发现的一类长度为～21 nt的内源非编码小RNA, 在植物和动物中发挥着重要而广泛的调控功能。它的发现主要有cDNA克隆测序和计算发现两条途径。由于cDNA克隆测序方法受miRNA表达的时间和组织特异性以及表达水平的影响, 而计算发现可以弥补其不足, 因此miRNA的计算发现方法研究受到了广泛的重视。文章对近几年计算发现miRNA的研究进展进行了综述, 根据计算发现方法的本质, 将计算发现方法归纳为5类, 分别是同源片段搜索方法、基于比较基因组学的预测方法、基于序列和结构特征打分的预测方法、结合作用靶标的预测方法和基于机器学习的预测方法, 并对各类方法的原理、核心思想、优点和局限性进行了分析, 最后探讨了进一步的发展方向。     

High-throughput approaches to catalyst discovery

High-throughput synthesis and screening approaches to catalyst discovery and optimization are systematically changing the way in which catalyst research is conducted. Increased rates of innovation, cost effectiveness, improved intellectual property, reduced time to market and an improved probability of success are some of the attractive features that demand consideration. Advances made over the past few years reveal that any initial skepticism is waning, and high-throughput approaches to catalyst discovery are now being implemented broadly in industrial and academic laboratories.     

Genomic approaches to drug discovery

Considerable progress has been made in exploiting the enormous amount of genomic and genetic information for the identification of potential targets for drug discovery and development. New tools that incorporate pathway information have been developed for gene expression data mining to reflect differences in pathways in normal and disease states. In addition, forward and reverse genetics used in a high-throughput mode with full-length cDNA and RNAi libraries enable the direct identification of components of signaling pathways. The discovery of the regulatory function of microRNAs highlights the importance of continuing the investigation of the genome with sophisticated tools. Furthermore, epigenetic information including DNA methylation and histone modifications that mediate important biological processes add to the possibilities to identify novel drug targets and patient populations that will benefit from new therapies.     

The decline of antibiotic era--new approaches for antibacterial drug discovery

Infectious diseases still remain the main cause of human premature deaths; especially in developing countries. The emergence and spread of pathogenic bacteria resistant to many antibiotics (multidrug-resistant strains) have created the need for the development of novel therapeutic agents. Only two new classes of antibiotics of novel mechanisms of action (linezolid and daptomycin) have been introduced into the market during the last three decades. The recent progress in molecular biology and bacterial genome analysis has had an enormous impact on antibacterial drug research. This review presents new achievements in searching a new bacterial essential genes, a potential targets for antibacterial drugs. Application of metagenomics strategy is also shown. Some recent technologies aimed at development of anti-pathogenic drugs such as inhibitors of quorum sensing process or histidine kinases are also discussed. Extensive research efforts have provided many details concerning structure of bacterial proteins playing an important role in pathogenesis such as adherence proteins or toxins, what allowed searching for antitoxin drugs or drugs interfering with bacterial adhesion. As an example, the review focuses on anthrax therapies under development. Additionally, the article presents the progress in phage therapy; using bacteriophages or their products such as lysins in antibacterial therapy.     

Emerging frontiers in virtual drug discovery: From quantum mechanical methods to deep learning approaches

Virtual screening-based approaches to discover initial hit and lead compounds have the potential to reduce both the cost and time of early drug discovery stages, as well as to find inhibitors for even challenging target sites such as protein–protein interfaces. Here in this review, we provide an overview of the progress that has been made in virtual screening methodology and technology on multiple fronts in recent years. The advent of ultra-large virtual screens, in which hundreds of millions to billions of compounds are screened, has proven to be a powerful approach to discover highly potent hit compounds. However, these developments are just the tip of the iceberg, with new technologies and methods emerging to propel the field forward. Examples include novel machine-learning approaches, which can reduce the computational costs of virtual screening dramatically, while progress in quantum-mechanical approaches can increase the accuracy of predictions of various small molecule properties.     

Chemogenomics approaches to novel target discovery

Chemogenomics involves the combination of a compound's effect on biological targets together with modern genomics technologies. The merger of these two methodologies is creating a new way to screen for compound-target interactions, as well as map chemical and biological space in a parallel fashion. The challenge associated with mining complex databases has initiated the development of many novel in silico tools to profile and analyze data in a systematic way. The ability to analyze the combinatorial effects of chemical libraries on biological systems will aid the discovery of new therapeutic entities. Chemogenomics provides a tool for the rapid validation of novel targeted therapeutics, where a specific molecular target is modulated by a small molecule. Along with targeted therapies comes the ability to discovery pathway nodes where a single molecular target might be an essential component of more than one disease. Several disease areas will benefit directly from the chemogenomics approach, the most advanced being cancer. A genetic loss-of-function screen can be modulated in the presence of a compound to search for genes or pathways involved in the compound's activity. Several recent papers highlight how chemogenomics is changing with RNA interference-based screening and shaping the discovery of new targeted therapies. Together, chemical and RNA interference-based screens open the door for a new way to discovery disease-associated genes and novel targeted therapies.     

Chemogenomics approaches to novel target discovery

Chemogenomics involves the combination of a compound’s effect on biological targets together with modern genomics technologies. The merger of these two methodologies is creating a new way to screen for compound–target interactions, as well as map chemical and biological space in a parallel fashion. The challenge associated with mining complex databases has initiated the development of many novel in silico tools to profile and analyze data in a systematic way. The ability to analyze the combinatorial effects of chemical libraries on biological systems will aid the discovery of new therapeutic entities. Chemogenomics provides a tool for the rapid validation of novel targeted therapeutics, where a specific molecular target is modulated by a small molecule. Along with targeted therapies comes the ability to discovery pathway nodes where a single molecular target might be an essential component of more than one disease. Several disease areas will benefit directly from the chemogenomics approach, the most advanced being cancer. A genetic loss-of-function screen can be modulated in the presence of a compound to search for genes or pathways involved in the compound’s activity. Several recent papers highlight how chemogenomics is changing with RNA interference-based screening and shaping the discovery of new targeted therapies. Together, chemical and RNA interference-based screens open the door for a new way to discovery disease-associated genes and novel targeted therapies.     

Genome-wide approaches for cancer gene discovery

One of the central aims of cancer research is to identify and characterize cancer-causing alterations in cancer genomes. In recent years, unprecedented advances in genome-wide sequencing, functional genomics technologies for RNA interference screens and methods for evaluating three-dimensional chromatin organization in vivo have resulted in important discoveries regarding human cancer. The cancer-causing genes identified from these new genome-wide technologies have also provided opportunities for effective and personalized cancer therapy. In this review, we describe some of the most recent technologies for cancer gene discovery. We also provide specific examples in which these technologies have proven remarkably successful in uncovering important cancer-causing alterations.     

Fragment-based approaches in drug discovery and chemical biology

Fragment-based approaches to finding novel small molecules that bind to proteins are now firmly established in drug discovery and chemical biology. Initially developed primarily in a few centers in the biotech and pharma industry, this methodology has now been adopted widely in both the pharmaceutical industry and academia. After the initial success with kinase targets, the versatility of this approach has now expanded to a broad range of different protein classes. Herein we describe recent fragment-based approaches to a wide range of target types, including Hsp90, β-secretase, and allosteric sites in human immunodeficiency virus protease and fanesyl pyrophosphate synthase. The role of fragment-based approaches in an academic research environment is also examined with an emphasis on neglected diseases such as tuberculosis. The development of a fragment library, the fragment screening process, and the subsequent fragment hit elaboration will be discussed using examples from the literature.     

Novel and revisited approaches in antituberculosis drug discovery

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Image source (SEM of Mtb): NIAID.