生物信息学导论课程与进阶课程比较

本文根据生物信息学是一门交叉学科的特点,在分析国内外高校相关课程设置的基础上,系统比较了生物信息学导论课程和进阶课程的差异和共性,提出了有针对性的内容安排方法和教学方式.笔者总结了授课过程的几个要点,即概念清楚、围绕主线、因材施教和加强实践,并在生物信息学课程教学中取得较好的效果.     

基于Memetic优化的智能DNA序列数据压缩算法

提出近似重复矢量(Approximate Repeat Vector,ARV)模型用于DNA序列冗余片段的描述.通过将数据生物信息学特征引入压缩预处理,并使用ARV矢量构造编码码本,提出了非对称DNA序列压缩算法BioLZMA-2.算法引入基于粒子群优化的Memetic改进方法CLIPSO-MA用于压缩码本的智能优化设计,有效提升了编码性能.在标准测试序列上的实验结果表明,BioLZMA-2可获得比现有DNA序列数据压缩方法更高的压缩率.     

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.     

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.     

PSICO: Solving Protein Structures with Constraint Programming and Optimization

In this paper we propose PSICO (Processing Structural Information with Constraint programming and Optimisation) as a constraint-based approach to determining protein structures compatible with distance constraints obtained from Nuclear Magnetic Resonance (NMR) data. We compare the performance of our proposed algorithm with DYANA (Dynamics algorithm for NMR applications) an existing commercial application based on simulated annealing. On a test case with experimental data on the dimeric protein Desulforedoxin, the method proposed here supplied similar results in less than 10 minutes compared to approximately 10 hours of computation time for DYANA. Although the quality of results can still be improved, this shows that CP technology can greatly reduce computation time, a major advantage because structural NMR technique generally demands multiple runs of structural computation.     

HGA-COFFEE:多序列比对问题的混合遗传算法求解

针对生物序列分析中的多序列比对问题，设计了一个求解多序列比对问题的混合遗传算法（与之相应的软件称为HGA-COFFEE），该算法采用COFFEE函数作为个体的适应度函数，构造了5种新的遗传算子，包括1种选择算子，2种交叉算子和2种变异算子，其中一种变异算子基于COFFEE的一致性信息设计，以改善算法的整体搜索能力；另一种变异算子基于动态规划方法设计，以增强其局部搜索能力。最后，通过对BAliBASE中144个测试例的测试，证明该算法是有效的，与已有的算法相比，该算法对处于朦胧区和具有N／C末端延伸的序列比对问题有更强的问题求解能力。     

Inhibition of Eimeria tenella CDK‐Related Kinase 2: From Target Identification to Lead Compounds

Apicomplexan parasites encompass several human‐ and animal‐pathogenic protozoans such as Plasmodium falciparum, Toxoplasma gondii, and Eimeria tenella. E. tenella causes coccidiosis, a disease that afflicts chickens, leading to tremendous economic losses to the global poultry industry. The considerable increase in drug resistance makes it necessary to develop new therapeutic strategies against this parasite. Cyclin‐dependent kinases (CDKs) are key molecules in cell‐cycle regulation and are therefore prominent target proteins in parasitic diseases. Bioinformatics analysis revealed four potential CDK‐like proteins, of which one—E. tenella CDK‐related kinase 2 (EtCRK2)—has already been characterized by gene cloning and expression. 1 By using the CDK‐specific inhibitor flavopiridol in EtCRK2 enzyme assays and schizont maturation assays (SMA), we could chemically validate CDK‐like proteins as potential drug targets. An X‐ray crystal structure of human CDK2 (HsCDK2) served as a template to build protein models of EtCRK2 by comparative homology modeling. Structural differences in the ATP binding site between EtCRK2 and HsCDK2, as well as chicken CDK3, were addressed for the optimization of selective ATP‐competitive inhibitors. Virtual screening and “wet‐bench” high‐throughput screening campaigns on large compound libraries resulted in an initial set of hit compounds. These compounds were further analyzed and characterized, leading to a set of four promising lead compounds for development as EtCRK2 inhibitors.     

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）。