线粒体蛋白组研究进展

线粒体蛋白组是指在线粒体中出现的所有蛋白质的集合,包括线粒体自身基因组编码的和 由核基因组编码的蛋白质.线粒体作为真核生物的重要细胞器,它参与去除氧化、产生能量和还原 性物质等等一些重要的生命活动过程.这些功能都依赖于线粒体蛋白组中的蛋白河的相互作用.要 对其有一个较为全面的认识,就必须对其蛋白组进行广泛且深入的研究.根据现有的一些研究成 果,对线粒体蛋白组在起源与进化、跨膜运输、研究方法和计算机预测作了简要综述.     

Microarray-based in vitro evaluation of DNA oligomer libraries designed in silico.

We report on the microarray-based in vitro evaluation of two libraries of DNA oligonucleotide sequences, designed in silico for applications in supramolecular self-assembly, such as DNA computing and DNA-based nanosciences. In this first study which is devoted to the comparison of sequence motif properties theoretically predicted with their performance in real-life, the DNA-directed immobilization (DDI) of proteins was used as an example of DNA-based self-assembly. Since DDI technologies, DNA computing, and DNA nanoconstruction essentially depend on similar prereguisites, in particular, large and uniform hybridization efficiencies combined with low nonspecific cross-reactivity between individual sequences, we anticipate that the microarray approach demonstrated here will enable rapid evaluation of other DNA sequence libraries.     

Cross-Talk between Overlap Interactions in Biomolecules: A Case Study of the β-Turn Motif

Noncovalent interactions play a pivotal role in regulating protein conformation, stability and dynamics. Among the quantum mechanical (QM) overlap-based noncovalent interactions, n→π* is the best understood with studies ranging from small molecules to β-turns of model proteins such as GB1. However, these investigations do not explore the interplay between multiple overlap interactions in contributing to local structure and stability. In this work, we identify and characterize all noncovalent overlap interactions in the β-turn, an important secondary structural element that facilitates the folding of a polypeptide chain. Invoking a QM framework of natural bond orbitals, we demonstrate the role of several additional interactions such as n→σ* and π→π* that are energetically comparable to or larger than n→π*. We find that these interactions are sensitive to changes in the side chain of the residues in the β-turn of GB1, suggesting that the n→π* may not be the only component in dictating β-turn conformation and stability. Furthermore, a database search of n→σ* and π→π* in the PDB reveals that they are prevalent in most proteins and have significant interaction energies (∼1 kcal/mol). This indicates that all overlap interactions must be taken into account to obtain a comprehensive picture of their contributions to protein structure and energetics. Lastly, based on the extent of QM overlaps and interaction energies, we propose geometric criteria using which these additional interactions can be efficiently tracked in broad database searches.     

面向生物信息学计算的网格工作流系统

针对生物信息学网格计算需求,提出了一种网格工作流管理系统模型,系统以Web方式为用户提供服务,通过与软件模块的交互实现良好的可定制的人机交互界面,使得不熟悉网格计算和工作流系统的人也可以快捷直观地操作使用.该系统能够自动地对工作流任务进行调度,然后通过网格中间件进行执行,并对任务进行监控和管理.论述了该系统的框架和实现原理,通过一个生物信息学计算实例说明工作流的定义、描述和使用流程;并且,通过与中国教育科研网格公共支撑平台CGSP工作流系统的对比,说明了该系统在可视化、便捷性上更符合生物信息学计算需求的特点.     

蛋白质中氨基酸间的相关性研究

计算和分析了4种类型(α型、β型、α／β型和α β型)共计204个蛋白质中的20种氨基酸间的相关性．研究发现，氨基酸之间的相关性可分为强正相关、强负相关、弱相关和不相关．作为蛋白质的建筑构件，20种氨基酸在不同类型的蛋白质中的相关性反映了这些建筑构件间的匹配规则，代表了蛋白质的结构特征．本文分析了部分氨基酸间的相关性与蛋白质结构间的联系，从物理和化学性质上解释了氨基酸相关性的起源。     

致病钩端螺旋体特异消减片段的序列测定与分析

对24个已鉴定的赖型致病钩端螺旋体特异消减片段进行DNA序列测定和生物信息学分析.结果显示,片段两端皆含有AluⅠ酶切位点,片段大小为149～1506bp,平均480bp,GC含量平均为36 63%.其中6个序列无任何同源匹配序列,提示可能来自新基因;18个同源序列可分为两类:与外膜蛋白或假想蛋白相关,与生化代谢修饰相关的酶.在Genbank中登记其中20个序列,序列号分别为AF300873-AF300877,AF325807-AF325821.这些基于生物信息学的功能预测,将有助于在此基础上进行相关的基因克隆鉴定、表达分析及功能验证.     

PepFun: Open Source Protocols for Peptide-Related Computational Analysis

Peptide research has increased during the last years due to their applications as biomarkers, therapeutic alternatives or as antigenic sub-units in vaccines. The implementation of computational resources have facilitated the identification of novel sequences, the prediction of properties, and the modelling of structures. However, there is still a lack of open source protocols that enable their straightforward analysis. Here, we present PepFun, a compilation of bioinformatics and cheminformatics functionalities that are easy to implement and customize for studying peptides at different levels: sequence, structure and their interactions with proteins. PepFun enables calculating multiple characteristics for massive sets of peptide sequences, and obtaining different structural observables derived from protein-peptide complexes. In addition, random or guided library design of peptide sequences can be customized for screening campaigns. The package has been created under the python language based on built-in functions and methods available in the open source projects BioPython and RDKit. We present two tutorials where we tested peptide binders of the MHC class II and the Granzyme B protease.     

Recent Advances in Discovery of Lead Structures from Microbial Natural Products: Genomics- and Metabolomics-Guided Acceleration

Natural products (NPs) are evolutionarily optimized as drug-like molecules and remain the most consistently successful source of drugs and drug leads. They offer major opportunities for finding novel lead structures that are active against a broad spectrum of assay targets, particularly those from secondary metabolites of microbial origin. Due to traditional discovery approaches’ limitations relying on untargeted screening methods, there is a growing trend to employ unconventional secondary metabolomics techniques. Aided by the more in-depth understanding of different biosynthetic pathways and the technological advancement in analytical instrumentation, the development of new methodologies provides an alternative that can accelerate discoveries of new lead-structures of natural origin. This present mini-review briefly discusses selected examples regarding advancements in bioinformatics and genomics (focusing on genome mining and metagenomics approaches), as well as bioanalytics (mass-spectrometry) towards the microbial NPs-based drug discovery and development. The selected recent discoveries from 2015 to 2020 are featured herein.     

Highly Luminescent N‐Doped Carbon Quantum Dots as an Effective Multifunctional Fluorescence Sensing Platform

The doping of carbon quantum dots with nitrogen provides a promising direction to improve fluorescence performance and broaden their applications in sensing systems. Herein we report a one‐pot solvothermal synthesis of N‐doped carbon quantum dots (NCQDs) and the synthesis of a series of NCQDs with different nitrogen contents. The as‐prepared NCQDs were compared with carbon quantum dots (CQDs); the introduction of nitrogen atoms largely increased the quantum yield of NCQDs and highest emission efficiency is up to 36.3 %. The fluorescence enhancement may originate from more polyaromatic structures induced by incorporated nitrogen atoms and protonation of nitrogen atoms on dots. It was found that NCQDs can act as a multifunctional fluorescence sensing platform because they can be used to detect pH values, Ag^I, and Fe^III in aqueous solution. The fluorescence intensity of NCQDs is inversely proportional to pH values across a broad range from 5.0 to 13.5, which indicates that NCQDs can be devised as an effective pH indicator. Selective detection of Ag^I and Fe^III was achieved based on their distinctive fluorescence influence because Ag^I can significantly enhance the fluorescence whereas Fe^III can greatly quench the fluorescence. The quantitative determination of Ag^I can be accomplished with NCQDs by using the linear relationship between fluorescence intensity of NCQDs and concentration of Ag^I. The sensitive detection of H₂O₂ was developed by taking advantage of the distinct quenching ability of Fe^III and Fe^II toward the fluorescence of NCQDs. Cellular toxicity test showed NCQDs still retain low toxicity to cells despite the introduction of a great deal of nitrogen atoms. Moreover, bioimaging experiments demonstrated that NCQDs have stronger resistance to photobleaching than CQDs and more excellent fluorescence labeling performance.