In Silico Biology - Volume 7, issue 4-5

Authors: Padhi, Abinash | Verghese, Bindhu | Otta, Subhendu K. | Varghese, Binu | Ramu, Karri

Article Type: Research Article

Abstract: The tissue-specific expression and differential function of the crustacean hyperglycemic hormone (CHH) in Carcinus maenas indicate an interesting evolutionary history. Previous studies have shown that CHH from the sinus gland X-organ (XO-type) has hyperglycemic activity, whereas the CHH from the pericardial organ (PO-type) neither shows hyperglycemic activity nor it inhibits Y-organ ecdysteroid synthesis. Here we examined the types of selective pressures operating on the variants of CHH in Carcinus maenas. Maximum likelihood-based …codon substitution analyses revealed that the variants of this neuropeptide in C. maenas have been subjected to positive Darwinian selection indicating adaptive evolution and functional divergence among the CHH variants leading to two unique groups (PO and XO-type). Although the average ratio of nonsynonymous to synonymous substitution (ω) for the entire coding region is 0.5096, few codon sites showed significantly higher ω (10.95). Comparison of models that incorporate positive selection (ω > 1) with models not incorporating positive selection (ω <1) at certain codon sites failed to reject (p=0) evidence of positive Darwinian selection. Show more

Keywords: Molecular evolution, crustacean hyperglycemic hormone, positive Darwinian selection, synonymous and nonsynonymous substitution, Carcinus maenas

Citation: In Silico Biology, vol. 7, no. 4-5, pp. 355-367, 2007

Authors: Saha, Sudipto | Raghava, Gajendra P.S.

Article Type: Research Article

Abstract: We have developed a method NTXpred for predicting neurotoxins and classifying them based on their function and origin. The dataset used in this study consists of 582 non-redundant, experimentally annotated neurotoxins obtained from Swiss-Prot. A number of modules have been developed for predicting neurotoxins using residue composition based on feed-forwarded neural network (FNN), recurrent neural network (RNN), support vector machine (SVM) and achieved maximum accuracy of 84.19%, 92.75%, 97.72% respectively. In addition, …SVM modules have been developed for classifying neurotoxins based on their source (e.g., eubacteria, cnidarians, molluscs, arthropods have been and chordate) using amino acid composition and dipeptide composition and achieved maximum overall accuracy of 78.94% and 88.07% respectively. The overall accuracy increased to 92.10%, when the evolutionary information obtained from PSI-BLAST was combined with SVM module of source classification. We have also developed SVM modules for classifying neurotoxins based on functions using amino acid, dipeptide composition and achieved overall accuracy of 83.11%, 91.10% respectively. The overall accuracy of function classification improved to 95.11%, when PSI-BLAST output was combined with SVM module. All the modules developed in this study were evaluated using five-fold cross-validation technique. The NTXpred is available at www.imtech.res.in/raghava/ntxpred/ and mirror site at http://bioinformatics.uams.edu/mirror/ntxpred. Show more

Keywords: NTXpred, prediction of neurotoxins, Webserver, blockers of ion channels

Citation: In Silico Biology, vol. 7, no. 4-5, pp. 369-387, 2007

Authors: Lim, Boon-San | Chong, Chan-Eng | Zamrod, Zulkeflie | Nathan, Sheila | Mohamed, Rahmah

Article Type: Research Article

Abstract: Many members of the AraC/XylS family transcription regulator have been proven to play a critical role in regulating bacterial virulence factors in response to environmental stress. By using the Hidden Markov Model (HMM) profile built from the alignment of a 99 amino acid conserved domain sequence of 273 AraC/XylS family transcription regulators, we detected a total of 45 AraC/XylS family transcription regulators in the genome of the Gram-negative pathogen, Burkholderia pseudomallei. Further in silico analysis of …each detected AraC/XylS family transcription regulatory protein and its neighboring genes allowed us to make a first-order guess on the role of some of these transcription regulators in regulating important virulence factors such as those involved in three type III secretion systems and biosynthesis of pyochelin, exopolysaccharide (EPS) and phospholipase C. This paper has demonstrated an efficient and systematic genome-wide scale prediction of the AraC/XylS family that can be applied to other protein families. Show more

Keywords: AraC/XylS, α-helix-turn-α-helix, hidden Markov model, Burkholderia pseudomallei

Citation: In Silico Biology, vol. 7, no. 4-5, pp. 389-397, 2007

Authors: Bajpai, Anjali | Sridhar, Settu | Reddy, Hemakumar M. | Jesudasan, Rachel A.

Article Type: Research Article

Abstract: BLAST and Repeat Masker Parser (BRM-Parser) is a service that provides users a unified platform for easy analysis of relatively large outputs of BLAST (Basic Local Alignment Search Tool) and RepeatMasker programs. BLAST Summary feature of BRM-Parser summarizes BLAST outputs, which can be filtered using user defined thresholds for hit length, percentage identity and E-value and can be sorted by query or subject coordinates and length of the hit. It also provides a tool that merges …BLAST hits which satisfy user-defined criteria for hit length and gap between hits. The RepeatMasker Summary feature uses the RepeatMasker alignment as an input file and calculates the frequency and proportion of mutations in copies of repeat elements, as identified by the RepeatMasker. Both features can be run through a GUI or can be executed via command line using the standalone version. Show more

Keywords: BLAST, RepeatMasker, repeats, parse, filter, merge, mutation

Citation: In Silico Biology, vol. 7, no. 4-5, pp. 399-403, 2007

Authors: Saha, Sudipto | Raghava, Gajendra P.S.

Article Type: Research Article

Abstract: This paper describes a method developed for predicting bacterial toxins from their amino acid sequences. All the modules, developed in this study, were trained and tested on a non-redundant dataset of 150 bacterial toxins that included 77 exotoxins and 73 endotoxins. Firstly, support vector machines (SVM) based modules were developed for predicting the bacterial toxins using amino acids and dipeptides composition and achieved an accuracy of 96.07% and 92.50%, respectively. Secondly, SVM based modules were …developed for discriminating entotoxins and exotoxins, using amino acids and dipeptides composition and achieved an accuracy of 95.71% and 92.86%, respectively. In addition, modules have been developed for classifying the exotoxins (e.g. activate adenylate cyclase, activate guanylate cyclase, neurotoxins) using hidden Markov models (HMM), PSI-BLAST and a combination of the two and achieved overall accuracy of 95.75%, 97.87% and 100%, respectively. Based on the above study, a web server called 'BTXpred' has been developed, which is available at http://www.imtech.res.in/raghava/btxpred/. Supplementary information is available at http://www.imtech.res.in/raghava/btxpred/supplementary.html. Show more

Keywords: Bacterial toxins, exotoxins, endotoxins, BTXpred, prediction server

Citation: In Silico Biology, vol. 7, no. 4-5, pp. 405-412, 2007

Authors: Rajesh, Rengaraj | Gunasekaran, Kasinathan | Muthukumaravel, Subramanian | Balaraman, Kothandapani | Jambulingam, Purusothaman

Article Type: Research Article

Abstract: The voltage-gated sodium channel (VGSC) is the target site for insecticides such as DDT and synthetic pyrethroids. A single base (A-T) change in the knock-down resistance (kdr) allele leads to an amino acid substitution at position 267 that confers the target-mediated resistance to DDT and synthetic pyrethroids in Anopheles gambiae. A theoretical model of the VGSC domain II that contains the site of mutation was constructed using the K^+ channel protein of Aeropyrum pernix …as a template. The validated model with 88.6% residues in the favored region was subjected to the CASTp program that predicted 30 pockets in the modeled domain II for ligand interaction. In the model, at position 267, leucine was manually replaced with phenylalanine. When this altered model was subjected to the CASTp program, the search results showed the same number of pockets. The docking results indicate that DDT interacts with the modeled VGSC domain II at position 275 in the presence of leucine or in the presence of phenylalanine (binding energy =−5.32 kcal/mol, −6.21 kcal/mol). It appears from the results that the mutation at position 267 has no direct influence on the interaction of DDT with the target protein. Therefore, to understand the interaction affinity of DDT with the target and influence of the mutation on the existence of active sites/pockets in relation to ligand binding, a whole VGSC model is necessary. Show more

Keywords: DDT, target mediated resistance, kdr, 3D model, VGSC domain-II, Anopheles gambiae, ligand interaction pockets, CASTp

Citation: In Silico Biology, vol. 7, no. 4-5, pp. 413-421, 2007

Authors: Ranjan, Ashutosh | Vidyarthi, Ambrish Sharan | Poddar, Raju

Article Type: Research Article

Abstract: To reveal the relative synonymous codon usage and base composition variation in bacteriophages, six mycobacteriophages were used as a model system here and both parameters in these phages and their host bacteria, Mycobacterium tuberculosis, have been determined and compared. As expected for GC-rich genomes, there are predominantly G and C ending codons in all 6 phages. Both N_{c} plot and correspondence analysis on relative synonymous codon usage indicate that mutation bias and translation …selection influences codon usage variation in the 6 phages. Further analysis indicates that among 6 Mycobacterium phages Che9c, Bxz1 and TM4 may be extremely virulent in nature as most of their genes have high translation efficiency. Based on our data we suggest that the genes of above three phages are expressed rapidly by host's translation machinery. The information might be used to select the extremely virulent Mycobacterium tuberculosis phages suitable for phage therapy. Show more

Keywords: Relative synonymous codon usage, correspondence analysis, translational selection, multivariate statistical analysis, Mycobacterium tuberculosis

Citation: In Silico Biology, vol. 7, no. 4-5, pp. 423-431, 2007

Authors: Kaba, Bangaly | Pinet, Nicolas | Lelandais, Gaëlle | Sigayret, Alain | Berry, Anne

Article Type: Research Article

Abstract: Recent work has used graphs to modelize expression data from microarray experiments, in view of partitioning the genes into clusters. In this paper, we introduce the use of a decomposition by clique separators. Our aim is to improve the classical clustering methods in two ways: first we want to allow an overlap between clusters, as this seems biologically sound, and second we want to be guided by the structure of the graph to define the number …of clusters. We test this approach with a well-known yeast database (Saccharomyces cerevisiae). Our results are good, as the expression profiles of the clusters we find are very coherent. Moreover, we are able to organize into another graph the clusters we find, and order them in a fashion which turns out to respect the chronological order defined by the the sporulation process. Show more

Keywords: Clustering method, microarray, graph decomposition, threshold family of graphs, expression profile

Citation: In Silico Biology, vol. 7, no. 4-5, pp. 433-452, 2007

Authors: Perumal, Deepak | Lim, Chu Sing | Sakharkar, Kishore R. | Sakharkar, Meena K.

Article Type: Research Article

Abstract: Complete genome sequences of several pathogenic bacteria have been determined, and many more such projects are currently under way. While these data potentially contain all the determinants of host-pathogen interactions and possible drug targets, computational tools for selecting suitable candidates for further experimental analyses are currently limited. Detection of bacterial genes that are non-homologous to human genes, and are essential for the survival of the pathogen represents a promising means of identifying novel drug …targets. We used a differential pathway analyses approach (based on KEGG data) to identify essential genes from Pseudomonas aeruginosa. Our approach identified 214 unique enzymes in P. aeruginosa that may be potential drug targets and can be considered for rational drug design. About 40% of these putative targets have been reported as essential by transposon mutagenesis data elsewhere. Homology model for one of the proteins (LpxC) is presented as a case study and can be explored for in silico docking with suitable inhibitors. This approach is a step towards facilitating the search for new antibiotics. Show more

Keywords: Pseudomonas aeruginosa, Homo sapiens, comparative microbial genomics, KEGG, homology, MODELLER, LpxC, potential drug targets

Citation: In Silico Biology, vol. 7, no. 4-5, pp. 453-465, 2007

Authors: Blachon, Sylvain | Pensa, Ruggero G. | Besson, Jérémy | Robardet, Céline | Boulicaut, Jean-François | Gandrillon, Olivier

Article Type: Research Article

Abstract: The production of high-throughput gene expression data has generated a crucial need for bioinformatics tools to generate biologically interesting hypotheses. Whereas many tools are available for extracting global patterns, less attention has been focused on local pattern discovery. We propose here an original way to discover knowledge from gene expression data by means of the so-called formal concepts which hold in derived Boolean gene expression datasets. We first encoded the over-expression properties of genes in human …cells using human SAGE data. It has given rise to a Boolean matrix from which we extracted the complete collection of formal concepts, i.e., all the largest sets of over-expressed genes associated to a largest set of biological situations in which their over-expression is observed. Complete collections of such patterns tend to be huge. Since their interpretation is a time-consuming task, we propose a new method to rapidly visualize clusters of formal concepts. This designates a reasonable number of Quasi-Synexpression-Groups (QSGs) for further analysis. The interest of our approach is illustrated using human SAGE data and interpreting one of the extracted QSGs. The assessment of its biological relevancy leads to the formulation of both previously proposed and new biological hypotheses. Show more

Keywords: Transcriptome, SAGE, pattern discovery, formal concepts, closed sets, clustering

Citation: In Silico Biology, vol. 7, no. 4-5, pp. 467-483, 2007