Quantifying structure-function uncertainty: a graph theoretical exploration into the origins and limitations of protein annotation

Since the advent of investigations into structural genomics, research has focused on correctly identifying domain boundaries, as well as domain similarities and differences in the context of their evolutionary relationships. As the science of structural genomics ramps up adding more and more information into the databanks, questions about the accuracy and completeness of our classification and annotation systems appear on the forefront of this research. A central question of paramount importance is how structural similarity relates to functional similarity. Here, we begin to rigorously and quantitatively answer these questions by first exploring the consensus between the most common protein domain structure annotation databases CATH, SCOP and FSSP. Each of these databases explores the evolutionary relationships between protein domains using a combination of automatic and manual, structural and functional, continuous and discrete similarity measures. In order to examine the issue of consensus thoroughly, we build a generalized graph out of each of these databases and hierarchically cluster these graphs at interval thresholds. We then employ a distance measure to find regions of greatest overlap. Using this procedure we were able not only to enumerate the level of consensus between the different annotation systems, but also to define the graph-theoretical origins behind the annotation schema of class, family and superfamily by observing that the same thresholds that define the best consensus regions between FSSP, SCOP and CATH correspond to distinct, non-random phase-transitions in the structure comparison graph itself. To investigate the correspondence in divergence between structure and function further, we introduce a measure of functional entropy that calculates divergence in function space. First, we use this measure to calculate the general correlation between structural homology and functional proximity. We extend this analysis further by quantitatively calculating the average amount of functional information gained from our understanding of structural distance and the corollary inherent uncertainty that represents the theoretical limit of our ability to infer function from structural similarity. Finally we show how our measure of functional "entropy" translates into a more intuitive concept of functional annotation into similarity EC classes.     

Identification of domains and domain interface residues in multidomain proteins from graph spectral method

We present a novel method for the identification of structural domains and domain interface residues in proteins by graph spectral method. This method converts the three-dimensional structure of the protein into a graph by using atomic coordinates from the PDB file. Domain definitions are obtained by constructing either a protein backbone graph or a protein side-chain graph. The graph is constructed based on the interactions between amino acid residues in the three-dimensional structure of the proteins. The spectral parameters of such a graph contain information regarding the domains and subdomains in the protein structure. This is based on the fact that the interactions among amino acids are higher within a domain than across domains. This is evident in the spectra of the protein backbone and the side-chain graphs, thus differentiating the structural domains from one another. Further, residues that occur at the interface of two domains can also be easily identified from the spectra. This method is simple, elegant, and robust. Moreover, a single numeric computation yields both the domain definitions and the interface residues.     

Simple critical schemes in non-autocatalytic systems of biochemical reactions

Kinetic behavior of various reaction systems consisting of three compounds was analyzed in order to find and study the origin of multiple-steady-state and auto-oscillatory behavior in biochemical systems. More than 3000 such reactions were considered. Using the bigraph method, six simple critical reaction schemes were found. It is shown that the presence of these fragments in the composition of more complex biochemical systems may be the origin of the multiple steady-states and autooscillations.     

Disease gene identification by using graph kernels and Markov random fields

Genes associated with similar diseases are often functionally related. This principle is largely supported by many biological data sources, such as disease phenotype similarities, protein complexes, protein-protein interactions, pathways and gene expression profiles. Integrating multiple types of biological data is an effective method to identify disease genes for many genetic diseases. To capture the gene-disease associations based on biological networks, a kernel-based MRF method is proposed by combining graph kernels and the Markov random field (MRF) method. In the proposed method, three kinds of kernels are employed to describe the overall relationships of vertices in five biological networks, respectively, and a novel weighted MRF method is developed to integrate those data. In addition, an improved Gibbs sampling procedure and a novel parameter estimation method are proposed to generate predictions from the kernel-based MRF method. Numerical experiments are carried out by integrating known gene-disease associations, protein complexes, protein-protein interactions, pathways and gene expression profiles. The proposed kernel-based MRF method is evaluated by the leave-one-out cross validation paradigm, achieving an AUC score of 0.771 when integrating all those biological data in our experiments, which indicates that our proposed method is very promising compared with many existing methods.     

EPG technique as a tool to reveal host plant acceptance by xylem sap‐feeding insects

The discovery of a new exotic insect herbivore triggers responses from biosecurity agencies, one of which is the decision of whether or not to attempt eradication. Rapid determination of the host range of the new invader is necessary, but when sap‐sucking insects are first collected from plants, the lack of visible signs of feeding damage makes it difficult to determine their host status. We investigated the Electrical Penetration Graph (EPG‐DC) technique as tool to assess host range of a xylem sap‐feeding invader, using Carystoterpa fingens (Hemiptera: Aphrophoridae), a New Zealand endemic xylem feeder, as a model insect. Real‐time probing and feeding events over a 12‐h recording period were compared for adult C. fingens on 18 plant species. Hebe azure, a known host, was designated the ‘reference plant species’ against which events on all other plants were statistically compared. EPG waveforms were categorized on their amplitude, frequency, voltage and electrical origin, and six parameters (time taken to first probe, time to first xylem ingestion from first probe, total probing time, number of xylem‐ingesting events, duration of the longest xylem‐ingesting event and total xylem ingestion time) were measured. The total xylem ingestion period (i.e. the actual feeding period) on each plant species expressed as a percentage of total probing time was considered the best parameter for comparing the host status of plants with H. azure. Although the EPG data overestimated the actual host range of C. fingens, we consider that they provided a reasonable first guide to the potential host status of the unknown plants, and so might usefully be used to rapidly assess whether a plant from which a new invader was collected was a host, or whether the association was merely incidental.     

MapGene2Chrom基于Perl和SVG语言绘制基因物理图谱

遗传图谱表现形式简洁明了,为分析遗传规律、克隆基因提供了便利。Gbrowse、MapViewer等工具虽然能够协助研究人员绘制相似形式的物理图谱,但有很大的局限性:(1)数据需提前布置好;(2)输出结果无法灵活修改。鉴于此,文章基于Perl和SVG语言,开发了一款生物辅助作图软件MapGene2Chrom的本地版与网页版,该软件能够依据输入数据快速绘制相应的物理图谱。该软件输入数据格式简单,输出结果易于修改,图片格式为SVG矢量图,具有很好的移植性,以期为研究人员绘制物理图谱提供便利。     

木薯和玉米原料丁醇发酵中丁醇丙酮质量比的图论理论计算及其验证

在丁醇发酵产溶剂阶段,乙酸和丁酸的生成途径、消耗途径同时存在,各自形成一个闭环路径。本研究利用图论对丁醇发酵中丁醇丙酮质量比进行了理论计算,并对以木薯和玉米为原料的丁醇发酵进行了模拟计算,结果表明:丁酸闭环路径(L2环)的代谢强度是影响丁醇丙酮质量比的主要因素,并且L2环的代谢强度越弱,丁醇丙酮质量比越高;与玉米原料丁醇发酵相比,木薯原料发酵的m(丁醇)/m(丙酮)提高了16.7%。实验结果证实了以上计算结果:在传统发酵、油醇萃取发酵和生物柴油萃取发酵中,以木薯(适时添加酵母浸粉)为原料的发酵批次与以玉米为原料的发酵批次相比,由于其丁酸闭环路径代谢强度较弱,相应发酵方式下丁醇丙酮质量比分别提高了12.9%、61.4%和6.7%,而且两种原料相应发酵方式的丁醇总产量和生产效率基本持平。另外,高丁醇丙酮质量比的木薯发酵所得改良型生物柴油中丁醇浓度与玉米发酵的相比提高了16%,性能得到进一步提高。