Fold recognition analysis of glycosyltransferase families: further members of structural superfamilies

Glycosyltransferases (GTs) are diverse enzymes organized into 65 families. X-ray crystallography and in silico studies have shown many of these to belong to two structural superfamilies: GT-A and GT-B. Through application of fold recognition and iterated sequence searches, we demonstrate that families 60, 62, and 64 may also be grouped into the GT-A fold superfamily. Analysis of conserved acidic residues suggests that catalytic sites are better conserved in superfamily GT-B than in GT-A. Although 26% and 29% of GT families may now be confidently placed in superfamilies GT-A and GT-B, respectively, the remaining 45% of families bear no discernible resemblance to either superfamily, which, given the sensitivity of modern fold recognition methods, suggests the existence of novel structural scaffolds associated with GT activity. Furthermore, bioinformatics studies indicate the apparent ease with which mechanism-inverting or retaining-may change during evolution.     

Pseudo amino acid composition and multi-class support vector machines approach for conotoxin superfamily classification

Conotoxins are disulfide rich small peptides that target a broad spectrum of ion-channels and neuronal receptors. They offer promising avenues in the treatment of chronic pain, epilepsy and cardiovascular diseases. Assignment of newly sequenced mature conotoxins into appropriate superfamilies using a computational approach could provide valuable preliminary information on the biological and pharmacological functions of the toxins. However, creation of protein sequence patterns for the reliable identification and classification of new conotoxin sequences may not be effective due to the hypervariability of mature toxins. With the aim of formulating an in silico approach for the classification of conotoxins into superfamilies, we have incorporated the concept of pseudo-amino acid composition to represent a peptide in a mathematical framework that includes the sequence-order effect along with conventional amino acid composition. The polarity index attribute, which encodes information such as residue surface buriability, polarity, and hydropathy, was used to store the sequence-order effect. Several methods like BLAST, ISort (Intimate Sorting) predictor, least Hamming distance algorithm, least Euclidean distance algorithm and multi-class support vector machines (SVMs), were explored for superfamily identification. The SVMs outperform other methods providing an overall accuracy of 88.1% for all correct predictions with generalized squared correlation of 0.75 using jackknife cross-validation test for A, M, O and T superfamilies and a negative set consisting of short cysteine rich sequences from different eukaryotes having diverse functions. The computed sensitivity and specificity for the superfamilies were found to be in the range of 84.0-94.1% and 80.0-95.5%, respectively, attesting to the efficacy of multi-class SVMs for the successful in silico classification of the conotoxins into their superfamilies.     

Predicting conotoxin superfamily and family by using pseudo amino acid composition and modified Mahalanobis discriminant

The conotoxin proteins are disulfide rich small peptides that target ion channels and G protein coupled receptors. And they provide promising application in treating some chronic pain, epilepsy, cardiovascular diseases, and so on. Conotoxins may be classified into 11 superfamilies: A, D, I1, I2, J, L, M, O, P, S, and T according to the disulfide connectivity, highly conserved N-terminal precursor sequence and similar mode of actions. Successful prediction mature conotoxin superfamily peptide has important signification for the biological and pharmacological functions of the toxins. In this study, a new algorithm of increment of diversity combined with modified Mahalanobis discriminant is presented to predict five superfamilies by using the pseudo amino acid composition. The results of jackknife cross-validation test show that the overall prediction sensitivity and specificity are 88% and 91%, respectively. The predictive algorithm is also used to predict three O-conotoxin families. The 72% sensitivity and 78% specificity are obtained. These results indicate that the conotoxin superfamily peptides correlate with their amino acid compositions.     

Intracellular trafficking of TRP channels

Thirteen years ago, it was suggested that exocytotic insertion of store-operated channels into the plasma membrane lead to increased Ca(2+) entry in non-excitable cells upon G protein-coupled or tyrosine kinase receptor stimulation. Since the discovery of the TRP channel superfamily and their involvement in receptor-induced Ca(2+) entry, many studies have shown that different members of the TRP superfamily translocate into the plasma membrane upon stimulation. While the exact molecular mechanism by which TRP channels insert into the plasma membrane is unknown, TRP-binding proteins have been shown to directly regulate this trafficking. This review summarizes recent advances related to the mechanism of TRP channel trafficking, focusing on the role of TRP-binding proteins.     

Structural insights into group II TRP channels

The seven members of the TRP channel superfamily are divided into two main groups with five members comprising group I (TRPC/V/M/N/A) and TRPML (TRP MucoLipin) and TRPP (TRP Polycystin) making up group II. Group II channels share a high sequence homology on their transmembrane domains and are distinct from group I members as they contain a large luminal/extracellular domain between transmembrane helix 1 (S1) and S2. Since 2016, there are more than ten research papers reporting various structures of group II channels by either cryo-EM or X-ray crystallography. These studies along with recent functional analysis by the other groups have considerably strengthened our knowledge on TRPML and TRPP channels. In this review, we summarize and discuss these reports providing molecular insights into the group II TRP channel family.     

基于GC-MS的异翅亚目臭腺分泌物化学分类学分析

【目的】探讨异翅亚目(Heteroptera)昆虫不同类群间臭腺分泌物化学组分的差异,为该类昆虫寻找新的分类特征并为各类群间的相互关系提供新的证据。【方法】我们采用固相微萃取(solid phase microextraction, SPME)偶联气相色谱-质谱仪(GC-MS)对采自中国的异翅亚目8个总科32个种的臭腺分泌物进行了测定分析;采用典型判别分析法、非参数多元方差分析法、典型变量分析法进行了高级阶元分泌物的化学分类学分析。【结果】典型判别分析结果表明,异翅亚目,尤其是蝽次目中不同总科间的臭腺分泌物具显著差异性,可作为总科间的分类特征;非参数多元方差分析结果支持臭腺分泌物在总科间的显著差异性;结合典型判别分析结果和典型变量分析的结果找到划分异翅亚目8个总科32个种的主要特征性化合物有6类共30种,包括酸类［己酸(hexanoic acid)、丁酸(butanoic acid)、2-己烯酸(2-hexenoic acid)］,醇类｛2-丁基-1-辛醇(2-butyl-octan-1-ol)、2-己基-1-辛醇(2-hexyl-octan-1-ol)、2-己炔-1-醇(2-hexyn-1-ol)、3,7-二甲基-2-辛烯-1-醇(3,7-dimethyl-2-octen-1-ol)、4,8-二甲基-1-壬醇(4,8-dimethyl-1-nonanol)、2-癸烯-1-醇(2-decen-1-ol)、1-己醇(1-hexanol)、高蒎醇(cis-pinene hydrate)、2-茨醇(borneol)、冰片(2-bornanol)、丙二醇甲醚(1-methoxy-propan-2-ol)、2-乙基1-己醇(2-ethyl-hexan-1-ol)、(6Z, 9Z)-十五烷-1-醇［(6Z, 9Z)-pentadecadien-1-ol］、(E)-9-十六碳烯-1-醇［(E)-9-hexadecen-1-ol］、(S)-3-乙基-4-甲基-1-戊醇［(S)-3-ethyl-4-methyl-pentan-1-ol］、异葑醇(isofenchol)、斯巴醇(spathulenol)｝,醛类｛(E)-2-辛烯醛［(E)-2-octenal］、十二醛(dodecanal)、(Z)-3-己烯醛［(Z)-3-hexenal］、(E)-2-癸烯醛［(E)-2-decenal］、(E, E)-2,4-癸二烯醛［(E, E)-2,4-decadienal］｝,烷类［2-甲基己烷(2-methyl-hexane)、2,21-二甲基二十二烷(2,21-dimethyl-docosane)］,环类［糠醛(furfural)］和萜类［二氢香芹醇(neodihydrocarveol)、二氢松油醇(dihydroterpineol)］。【结论】本研究从异翅亚目8个总科32个物种臭腺分泌物中鉴定的30种特征性化合物在一定程度上可作为异翅亚目总科级阶元的分类特征并为其相互关系提供依据。     

Molecular Evolution and Diversity of Conus Peptide Toxins,as Revealed by Gene Structure and Intron Sequence Analyses

Cone snails, which are predatory marine gastropods, produce a cocktail of venoms used for predation, defense and competition. The major venom component, conotoxin, has received significant attention because it is useful in neuroscience research, drug development and molecular diversity studies. In this study, we report the genomic characterization of nine conotoxin gene superfamilies from 18 Conus species and investigate the relationships among conotoxin gene structure, molecular evolution and diversity. The I1, I2, M, O2, O3, P, S, and T superfamily precursors all contain three exons and two introns, while A superfamily members contain two exons and one intron. The introns are conserved within a certain gene superfamily, and also conserved across different Conus species, but divergent among different superfamilies. The intronic sequences contain many simple repeat sequences and regulatory elements that may influence conotoxin gene expression. Furthermore, due to the unique gene structure of conotoxins, the base substitution rates and the number of positively selected sites vary greatly among exons. Many more point mutations and trinucleotide indels were observed in the mature peptide exon than in the other exons. In addition, the first example of alternative splicing in conotoxin genes was found. These results suggest that the diversity of conotoxin genes has been shaped by point mutations and indels, as well as rare gene recombination or alternative splicing events, and that the unique gene structures could have made a contribution to the evolution of conotoxin genes.     

基于18S rDNA序列的蝽次目(半翅目：异翅亚目)

利用18SrDNA分子约1 912 bp的序列对蝽次目21个科53个种进行系统发育分析。运用MP法、ML法和NJ法分析后的结果表明:蝽次目的单系性得到很高的支持;扁蝽总科成为毛点类的姐妹群;毛点类基本确定为两大分支:一支包含蝽总科和红蝽总科;另一支主要由长蝽总科、缘蝽总科和南蝽总科组成;长蝽总科和缘蝽总科都是多系;长蝽总科中,跷蝽科和皮蝽科的关系最近,构成姐妹群,位于整个毛点类的基部;与长蝽总科中另外两个科长蝽科和地长蝽科的关系很远。说明利用18SrDNA分子对研究蝽次目的系统发育关系是适合的,能够重建蝽次目;扁蝽总科和蝽总科单系性的结果与形态学的研究以及Li et al (2005)的研究一致;但较Li et al(2005)的研究更进一步把红蝽总科从广义的缘蝽总科中分出来;并建议皮蝽科作为一个独立的总科更合适。     

Evolution of protein superfamilies and bacterial genome size

We present the structural annotation of 56 different bacterial species based on the assignment of genes to 816 evolutionary superfamilies in the CATH domain structure database. These assignments have enabled us to analyse the recurrence of specific superfamilies within and across the genomes. We have selected the superfamilies that have a very broad representation and therefore appear to be universally distributed in a significant number of bacterial lineages. Occurrence profiles of these universally distributed superfamilies are compared with genome size in order to estimate the correlation between superfamily duplication and the increase in proteome size. This distinguishes between those size-dependent superfamilies where frequency of occurrence is highly correlated with increase in genome size, and size-independent superfamilies where no correlation is observed. Consideration of the size correlation and the ratio between the mean and the standard deviations for all the superfamily profiles allows more detailed subdivisions and classification of superfamilies. For example, within the size-independent superfamilies, we distinguished a group that are distributed evenly amongst all the genomes. Within the size-dependent superfamilies we differentiated two groups: linearly distributed and non-linearly distributed. Functional annotation using the COG database was performed for all superfamilies in each of these groups, and this revealed significant differences amongst the three sets of superfamilies. Evenly distributed, size-independent domains are shown to be involved primarily in protein translation and biosynthesis. For the size-dependent superfamilies, linearly distributed superfamilies are involved mainly in metabolism, and non-linearly distributed superfamily domains are involved principally in gene regulation.     

The TRPC3/6/7 subfamily of cation channels

The mammalian transient receptor potential (TRP) proteins consist of a superfamily of Ca2+-permeant non-selective cation channels with structural similarities to Drosophila TRP. The TRP superfamily can be divided into three major families, among them the "canonical TRP" family (TRPC). The seven protein products of the mammalian TRPC family of genes (designated TRPC1-7) share in common the activation through PLC-coupled receptors and have been proposed to encode components of native store-operated channels in different cell types. In addition, the three members of the TRPC3/6/7 subfamily of TRPC channels can be activated by diacylglycerol analogs, providing a possible mechanism of activation of these channels by PLC-coupled receptors. This review summarizes the current knowledge about the mechanism of activation of the TRPC3/6/7 subfamily, as well as the potential role of these proteins as components of native Ca2+-permeant channels.     

Revealing the set of mutually correlated positions for the protein families of immunoglobulin fold

In this study, I explain the observation that a rather limited number of residues (about 10) establishes the immunoglobulin fold for the sequences of about 100 residues. Immunoglobulin fold proteins (IgF) comprise SCOP protein superfamilies with rather different functions and with less than 10% sequence identity; their alignment can be accomplished only taking into account the 3D structure. Therefore, I believe that discovering the additional common features of the sequences is necessary to explain the existence of a common fold for these SCOP superfamilies. We propose a method for analysis of pair-wise interconnections between residues of the multiple sequence alignment which helps us to reveal the set of mutually correlated positions, inherent to almost every superfamily of this protein fold. Hence, the set of constant positions (comprising the hydrophobic common core) and the set of variable but mutually correlated ones can serve as a basis of having the common 3D structure for rather distinct protein sequences.     

FuzzyART neural network for protein classification

One of the major research directions in bioinformatics is that of predicting the protein superfamily in large databases and classifying a given set of protein domains into superfamilies. The classification reflects the structural, evolutionary and functional relatedness. These relationships are embodied in hierarchical classification such as Structural Classification of Protein (SCOP), which is manually curated. Such classification is essential for the structural and functional analysis of proteins. Yet, a large number of proteins remain unclassified. We have proposed an unsupervised machine-learning FuzzyART neural network algorithm to classify a given set of proteins into SCOP superfamilies. The proposed method is fast learning and uses an atypical non-linear pattern recognition technique. In this approach, we have constructed a similarity matrix from p-values of BLAST all-against-all, trained the network with FuzzyART unsupervised learning algorithm using the similarity matrix as input vectors and finally the trained network offers SCOP superfamily level classification. In this experiment, we have evaluated the performance of our method with existing techniques on six different datasets. We have shown that the trained network is able to classify a given similarity matrix of a set of sequences into SCOP superfamilies at high classification accuracy.     

Identification of neurotransmitter receptor genes under significantly relaxed selective constraint by orthologous gene comparisons between humans and rodents

Neurotransmitter receptors (neuroreceptors) are classified into two types, G protein-coupled receptors (GPCRs) and ligand-gated ion channels. The former occupies a small part of the large GPCR superfamily, whereas the latter consists of three superfamilies. In these superfamilies, humans and rodents share almost the same set of neuroreceptor genes. This neuroreceptor gene set is good material to examine the degree of selective constraint exerted on each member gene of a given superfamily. If there are any neuroreceptor genes under the degree of selective constraint that is very different from that of the other member genes, they may have influenced the functional features characteristic of human neural activities. With the aim of identifying such neuroreceptor genes, we collected sequence data of orthologous neuroreceptor genes for humans, mice, and rats by database searches. This data set included ortholog pairs for 141 kinds of neuroreceptor genes, which covered almost the whole set of neuroreceptor genes known to be expressed in the human brain. The degree of selective constraint was estimated by computing the ratio (d(N)/d(S)) of the number of nonsynonymous substitutions to that of synonymous substitutions. We found that the d(N)/d(S) ratio ranged widely and its distribution fitted a gamma distribution. In particular, we found that four neuroreceptor genes are under the significantly relaxed selective constraint. They are an ionotropic glutamate receptor subunit NMDA-2C, two GABA(A) receptor subunits, i.e., GABA(A)-epsilon and GABA(A)-theta, and a dopamine receptor D4. Interestingly, these neuroreceptors have been reported to be associated with cognitive abilities such as memory and learning, and responsiveness to novel stimuli. These cognitive abilities can influence the behavioral features of an individual. Thus, it suggests that the relaxed-constraint neuroreceptor genes have evolved, assuring that the nervous system responds to a variety of stimuli with proper flexibility.     

Evolutionarily conserved substrate substructures for automated annotation of enzyme superfamilies

The evolution of enzymes affects how well a species can adapt to new environmental conditions. During enzyme evolution, certain aspects of molecular function are conserved while other aspects can vary. Aspects of function that are more difficult to change or that need to be reused in multiple contexts are often conserved, while those that vary may indicate functions that are more easily changed or that are no longer required. In analogy to the study of conservation patterns in enzyme sequences and structures, we have examined the patterns of conservation and variation in enzyme function by analyzing graph isomorphisms among enzyme substrates of a large number of enzyme superfamilies. This systematic analysis of substrate substructures establishes the conservation patterns that typify individual superfamilies. Specifically, we determined the chemical substructures that are conserved among all known substrates of a superfamily and the substructures that are reacting in these substrates and then examined the relationship between the two. Across the 42 superfamilies that were analyzed, substantial variation was found in how much of the conserved substructure is reacting, suggesting that superfamilies may not be easily grouped into discrete and separable categories. Instead, our results suggest that many superfamilies may need to be treated individually for analyses of evolution, function prediction, and guiding enzyme engineering strategies. Annotating superfamilies with these conserved and reacting substructure patterns provides information that is orthogonal to information provided by studies of conservation in superfamily sequences and structures, thereby improving the precision with which we can predict the functions of enzymes of unknown function and direct studies in enzyme engineering. Because the method is automated, it is suitable for large-scale characterization and comparison of fundamental functional capabilities of both characterized and uncharacterized enzyme superfamilies.     

Exploring the evolution of novel enzyme functions within structurally defined protein superfamilies

In order to understand the evolution of enzyme reactions and to gain an overview of biological catalysis we have combined sequence and structural data to generate phylogenetic trees in an analysis of 276 structurally defined enzyme superfamilies, and used these to study how enzyme functions have evolved. We describe in detail the analysis of two superfamilies to illustrate different paradigms of enzyme evolution. Gathering together data from all the superfamilies supports and develops the observation that they have all evolved to act on a diverse set of substrates, whilst the evolution of new chemistry is much less common. Despite that, by bringing together so much data, we can provide a comprehensive overview of the most common and rare types of changes in function. Our analysis demonstrates on a larger scale than previously studied, that modifications in overall chemistry still occur, with all possible changes at the primary level of the Enzyme Commission (E.C.) classification observed to a greater or lesser extent. The phylogenetic trees map out the evolutionary route taken within a superfamily, as well as all the possible changes within a superfamily. This has been used to generate a matrix of observed exchanges from one enzyme function to another, revealing the scale and nature of enzyme evolution and that some types of exchanges between and within E.C. classes are more prevalent than others. Surprisingly a large proportion (71%) of all known enzyme functions are performed by this relatively small set of 276 superfamilies. This reinforces the hypothesis that relatively few ancient enzymatic domain superfamilies were progenitors for most of the chemistry required for life.     

Superfamily active site templates

We show that three-dimensional signatures consisting of only a few functionally important residues can be diagnostic of membership in superfamilies of enzymes. Using the enolase superfamily as a model system, we demonstrate that such a signature, or template, can identify superfamily members in structural databases with high sensitivity and specificity. This is remarkable because superfamilies can be highly diverse, with members catalyzing many different overall reactions; the unifying principle can be a conserved partial reaction or chemical capability. Our definition of a superfamily thus hinges on the disposition of residues involved in a conserved function, rather than on fold similarity alone. A clear advantage of basing structure searches on such active site templates rather than on fold similarity is the specificity with which superfamilies with distinct functional characteristics can be identified within a large set of proteins with the same fold, such as the (beta/alpha)8 barrels. Preliminary results are presented for an additional group of enzymes with a different fold, the haloacid dehalogenase superfamily, suggesting that this approach may be generally useful for assigning reading frames of unknown function to specific superfamilies and thereby allowing inference of some of their functional properties.     

Recent breakthroughs in the molecular mechanism of capacitative calcium entry (with thoughts on how we got here)

Activation of phospholipase C by G-protein-coupled receptors results in release of intracellular Ca(2+) and activation of Ca(2+) channels in the plasma membrane. The intracellular release of Ca(2+) is signaled by the second messenger, inositol 1,4,5-trisphosphate. Ca(2+) entry involves signaling from depleted intracellular stores to plasma membrane Ca(2+) channels, a process referred to as capacitative calcium entry or store-operated calcium entry. The electrophysiological current associated with capacitative calcium entry is the calcium-release-activated calcium current, or I(crac). In the 20 years since the inception of the concept of capacitative calcium entry, a variety of activation mechanisms have been proposed, and there has been considerable interest in the possibility of transient receptor potential channels functioning as store-operated channels. However, in the past 2 years, two major players in both the signaling and permeation mechanisms for store-operated channels have been discovered: Stim1 (and possibly Stim2) and the Orai proteins. Activation of store-operated channels involves an endoplasmic reticulum Ca(2+) sensor called Stim1. Stim1 acts by redistributing within a small component of the endoplasmic reticulum, approaching the plasma membrane, but does not appear to translocate into the plasma membrane. Stim1, either directly or indirectly, signals to plasma membrane Orai proteins which constitute pore-forming subunits of store-operated channels.     

中国蝗总科昆虫科间系统发育关系支序分析：直翅目;蝗亚目

在形态学研究的基础上,配方选择了１２个特征,利用Ｈｅｎｎｉｇ８６程序包,以支序分析探讨了中国蝗总科昆虫科间的系统发育关系。结果表明蝗虫类昆虫稳定的分为两大类,即癞蝗类和蝗类,本文建议蝗虫类昆虫分为分为两个总科较宜。长腹蝗亚科似归入斑腿蝗亚科更为合理;而皱腹亚科则应提升为独立科。     

Capacitative calcium entry in the nervous system

Capacitative calcium entry is a process whereby the depletion of Ca(2+) from intracellular stores (likely endoplasmic or sarcoplasmic reticulum) activates plasma membrane Ca(2+) channels. Current research has focused on identification of capacitative calcium entry channels and the mechanism by which Ca(2+) store depletion activates the channels. Leading candidates for the channels are members of the transient receptor potential (TRP) superfamily, although no single gene or gene product has been definitively proven to mediate capacitative calcium entry. The mechanism for activation of the channels is not known; proposals fall into two general categories, either a diffusible signal released from the Ca(2+) stores when their Ca(2+) levels become depleted, or a more direct protein-protein interaction between constituents of the endoplasmic reticulum and the plasma membrane channels. Capacitative calcium entry is a major mechanism for regulated Ca(2+) influx in non-excitable cells, but recent research has indicated that this pathway plays an important role in the function of neuronal cells, and may be important in a number of neuropathological conditions. This review will summarize some of these more recent findings regarding the role of capacitative calcium entry in normal and pathological processes in the nervous system.