Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification

One of the initial steps of modern drug discovery is the identification of small organic molecules able to inhibit a target macromolecule of therapeutic interest. A small proportion of these hits are further developed into lead compounds, which in turn may ultimately lead to a marketed drug. A commonly used screening protocol used for this task is high-throughput screening (HTS). However, the performance of HTS against antibacterial targets has generally been unsatisfactory, with high costs and low rates of hit identification. Here, we present a novel computational methodology that is able to identify a high proportion of structurally diverse inhibitors by searching unusually large molecular databases in a time-, cost- and resource-efficient manner. This virtual screening methodology was tested prospectively on two versions of an antibacterial target (type II dehydroquinase from Mycobacterium tuberculosis and Streptomyces coelicolor), for which HTS has not provided satisfactory results and consequently practically all known inhibitors are derivatives of the same core scaffold. Overall, our protocols identified 100 new inhibitors, with calculated K_i ranging from 4 to 250 μM (confirmed hit rates are 60% and 62% against each version of the target). Most importantly, over 50 new active molecular scaffolds were discovered that underscore the benefits that a wide application of prospectively validated in silico screening tools is likely to bring to antibacterial hit identification.     

以中央地方共建为契机建立生物信息综合实验平台

结合中央与地方共建特色实验室项目,以应用生物的理论和方法技术研究生物等问题为切入点,在将生物信息学院实验室提升为具有产学研一体化功能、特色鲜明的现代化生物信息实验教学中心方面进行了研究与实践,取得了阶段性成果。     

Comparison of 10,11‐Dehydrocurvularin Polyketide Synthases from Alternaria cinerariae and Aspergillus terreus Highlights Key Structural Motifs

Iterative type I polyketide synthases (PKSs) from fungi are multifunctional enzymes that use their active sites repeatedly in a highly ordered sequence to assemble complex natural products. A phytotoxic macrolide with anticancer properties, 10,11‐dehydrocurvularin (DHC), is produced by cooperation of a highly reducing (HR) iterative PKS and a non‐reducing (NR) iterative PKS. We have identified the DHC gene cluster in Alternaria cinerariae, heterologously expressed the active HR PKS (Dhc3) and NR PKS (Dhc5) in yeast, and compared them to corresponding proteins that make DHC in Aspergillus terreus. Phylogenetic analysis and homology modeling of these enzymes identified variable surfaces and conserved motifs that are implicated in product formation.     

使用pFind软件深度检测蛋白质修饰

Tandem mass spectrometry-based protein identification provides a powerful means for large-scale mapping of post-translational modifications. However, due to the complexity of tandem mass spectra and the large number of modifications, comprehensive and efficient detection of modifications remains an unsolved problem. This paper briefly describes a new solution used by the pFind software for in-depth detection of modifications.     

An Overview of Synergistic Data Tools for Biological Scrutiny

A network of biological databases is reviewed, supplying a framework for studies of human genes and the association of their genomic variations with human phenotypes. The network is composed of GeneCards, the human gene compendium, which provides comprehensive information on all known and predicted human genes, along with its suite members GeneDecks and GeneLoc. Two databases are shown that address genes and variations focusing on olfactory reception (HORDE) and transduction (GOSdb). In the realm of disease scrutiny, we portray MalaCards, a novel comprehensive database of human diseases and their annotations. Also shown is GeneKid, a tool aimed at generating novel kidney disease biomarkers using systems biology, as well as Xome, a database for whole-exome next-generation DNA sequences for human diseases in the Israeli population. Finally, we show LifeMap Discovery, a database of embryonic development, stem cell research and regenerative medicine, which links to both GeneCards and MalaCards.     

Mass spectrometry of peptides and proteins from human blood

It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post‐translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post‐translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ～1 ng/mL. © 2010 Wiley Periodicals, Inc., Mass Spec Rev 30:685–732, 2011     

基于GC-GM的多序列比对穷举遗传算法

多序列比对问题是生物信息学中尚未解决的一个NP完全的组合优化问题。通过对重新组装的空位矩阵进行遗传操作来实现最优比对,设计了一个新型的基于GC-GM的多序列比对穷举遗传算法。从BAliBASE 比对数据库中选取了一些比对例子进行了模拟计算,并与Clustal-W算法进行了比较,实验表明该算法是有效的。     

蛋白质相互作用网络的相似子网搜索问题研究

蛋白质相互作用网络（Protein-Protein Interactions Network,PIN）的相似性问题是目前生物信息学领域研究的热点。将计算机科学和生物学相结合,提出了蛋白质相互作用网络邻居优先搜索算法。该算法综合蛋白质的序列信息和蛋白质相互作用网络的拓扑结构信息,适度提高与相似蛋白质有直接相互作用的蛋白质之间的相似系数,实现了不同物种间蛋白质相互作用相似子网络的搜索。与同类算法的对比实验表明,该算法可以处理更大规模的目标子网搜索,计算速度明显提高,且利用该算法获得的结果与目标子网具有更长的相似路径。论文采用该算法研究了酵母和果蝇的蛋白质相互作用网络,获得了10条相对保守的蛋白质相互作用（Protein-Protein Interactions,PPI）。