In Silico Biology - Volume 6, issue 6

Authors: Benítez-Páez, Alfonso

Article Type: Research Article

Abstract: The Receptor Activity-Modifying Proteins (RAMP) is a family constituted by a single N-terminal extracellular domain and a transmembrane region ending in a short cytoplasmic region. Due to their specific role in modulating the specificity of ligand binding in many class II G-Protein Coupled Receptors, these proteins are awaiting further characterization and elucidation of their structure. This was the aim of this study. We were able to find 13 new RAMP sequences including new protein sequences and …predicted peptides from Expressed Sequence Tags and genomic DNA, all of them annotated in databases such as GeneBank, EMBL, Swissprot and ENSEMBL. The predicted peptides came from an array of different organisms including Teleostei and Elasmobranchii species, of which the latter was the most ancient RAMP sequence found. It was also possible to efficiently predict the 1D structure of the extracellular RAMP domain and its 3D conformation was inferred through a combination of bioinformatic approaches such as threading. The 1D structure of the extracellular RAMP domain was predicted as three α-helix domain. The most highly conserved residues in the RAMP family were found to be involved in critical functions. Bioinformatic data mining and multiple sequence alignment analysis were crucial for improving the characterization of RAMP proteins and prediction of their 1D and 3D configurations. Show more

Keywords: RAMP proteins, structure prediction, sequence alignments

Citation: In Silico Biology, vol. 6, no. 6, pp. 467-483, 2006

Authors: Singh, Nitesh Kumar | Selvam, S. Mahalaxmi | Chakravarthy, Paulsharma

Article Type: Research Article

Abstract: With the completion of the Human Genome Project in 2003, many new projects to sequence bacterial genomes were started and soon many complete bacterial genome sequences were available. The sequenced genomes of pathogenic bacteria provide useful information for understanding host-pathogen interactions. These data prove to be a new weapon in fighting against pathogenic bacteria by providing information about potential drug targets. But the limitation of computational tools for finding potential drug targets has …hindered the process and further experimental analysis. There are many in silico approaches proposed for finding drug targets but only few have been automated. One such approach finds essential genes in bacterial genomes with no human homologue and predicts these as potential drug targets. The same approach is used in our tool. T-iDT, a tool for the identification of drug targets, finds essential genes by comparing a bacterial gene set against DEG (Database of Essential Genes) and excludes homologue genes by comparing against a human protein database. The tool predicts both the set of essential genes as well as potential target genes for the given genome. The tool was tested with Mycobacterium tuberculosis and results were validated. With default parameters, the tool predicted 236 essential genes and 52 genes to encode potential drug targets. A pathway-based approach was used to validate these potential drug target genes. The pathway in which the products of these genes are involved was determined. Our analysis shows that almost all these pathways are very essential for the bacterial survival and hence these genes encode possible drug targets. Our tool provides a fast method for finding possible drug targets in bacterial genomes with varying stringency level. The tool will be helpful in finding possible drug targets in various pathogenic organisms and can be used for further analysis in novel therapeutic drug development. The tool can be downloaded from http://www.milser.co.in/research.htm and http://www.srmbioinformatics.edu.in/forum.htm. Show more

Keywords: Comparative genomics, BLAST, essential genes, DEG, drug target, subtractive genomics

Citation: In Silico Biology, vol. 6, no. 6, pp. 485-493, 2006

Authors: Andrade, Jorge | Berglund, Lisa | Uhlén, Mathias | Odeberg, Jacob

Article Type: Research Article

Abstract: For several applications and algorithms used in applied bioinformatics, a bottle neck in terms of computational time may arise when scaled up to facilitate analyses of large datasets and databases. Re-codification, algorithm modification or sacrifices in sensitivity and accuracy may be necessary to accommodate for limited computational capacity of single work stations. Grid computing offers an alternative model for solving massive computational problems by parallel execution of existing algorithms and software implementations. …We present the implementation of a Grid-aware model for solving computationally intensive bioinformatic analyses exemplified by a blastp sliding window algorithm for whole proteome sequence similarity analysis, and evaluate the performance in comparison with a local cluster and a single workstation. Our strategy involves temporary installations of the BLAST executable and databases on remote nodes at submission, accommodating for dynamic Grid environments as it avoids the need of predefined runtime environments (preinstalled software and databases at specific Grid-nodes). Importantly, the implementation is generic where the BLAST executable can be replaced by other software tools to facilitate analyses suitable for parallelisation. This model should be of general interest in applied bioinformatics. Scripts and procedures are freely available from the authors. Show more

Keywords: Grid, BLAST, distributed computing

Citation: In Silico Biology, vol. 6, no. 6, pp. 495-504, 2006

Authors: Png, Adrian E.H. | Choo, Keng Wah | Lee, Cheryl I.P. | Leong, Siew Hong | Kon, Oi Lian

Article Type: Research Article

Abstract: Whole Genome Amplification (WGA) is an important process to increase limiting amounts of genomic DNA prior to genomic analyses. Current amplification methods based on primer extension or strand displacement principles employ primers of partially or totally random sequence. In this paper, we present a method using Genetic Algorithms to optimize a single primer design to be used in a primer extension reaction to achieve unbiased WGA. Computational simulation and prediction of a suitable primer proposed two …candidates NYP6-1 (ATCTCA) and NYP6-2 (TGAGAT). NYP6-1 amplified to a maximum length of 2537 base pairs (bp), had genome coverage of approximately 45.62%, with an average of 493 and variance of 163 amplicons per 1 megabasepairs (Mb). NYP6-2 amplified to a maximum length of 2926 bp and covered 54.35% of the genome with an average of 579 and a variance of 191 amplicons per Mb. In contrast, the original primer used in Degenerate Oligonucleotide-Primed PCR (DOP-PCR) had coverage of 20.93%, an average of 74 and variance of 188 amplicons per Mb when extended up to a length of 2000 bp. Successful WGA of miniscule amounts of genomic DNA requires the amplification method used to resolve issues on efficiency, accurate representation of the whole genome and ability to degraded DNA. The sequence NYP6-2 discovered using our method can be confidently used in a primer extension based protocol to perform quantitatively unbiased WGA. Show more

Keywords: Whole genome amplification, genetic algorithms

Citation: In Silico Biology, vol. 6, no. 6, pp. 505-514, 2006

Authors: Dohkan, Shinsuke | Koike, Asako | Takagi, Toshihisa

Article Type: Research Article

Abstract: Predicting the interactions between all the possible pairs of proteins in a given organism (making a protein-protein interaction map) is a crucial subject in bioinformatics. Most of the previous methods based on supervised machine learning use datasets containing approximately the same number of interacting pairs of proteins (positives) and non-interacting pairs of proteins (negatives) for training a classifier and are estimated to yield a large number of false positives. Thinking that the negatives used in previous …studies cannot adequately represent all the negatives that need to be taken into account, we have developed a method based on multiple Support Vector Machines (SVMs) that uses more negatives than positives for predicting interactions between pairs of yeast proteins and pairs of human proteins. We show that the performance of a single SVM improved as we increased the number of negatives used for training and that, if more than one CPU is available, an approach using multiple SVMs is useful not only for improving the performance of classifiers but also for reducing the time required for training them. Our approach can also be applied to assessing the reliability of high-throughput interactions. Show more

Keywords: Protein-protein interaction map, SVM, prediction, negative data

Citation: In Silico Biology, vol. 6, no. 6, pp. 515-529, 2006

Authors: Kim, Tae-Min | Jung, Myeong Ho

Article Type: Research Article

Abstract: To understand the transcriptional regulatory network in eukaryotic cells, it is essential to identify functional cis-regulatory sequences that interact with trans-acting factors. A number of algorithms have been developed to predict common cis-regulatory elements for co-regulated genes with similar expression patterns. However, previous methods usually deal with disjoint gene groups partitioned or clustered by arbitrary cutoffs, which might cause information losses. To preclude the defining step of gene set, we adopted enrichment …analysis and termed the method binding site enrichment analysis (BSEA). BSEA was first applied for publicly available ChIP-on-chip data of c-MYC, MAX and E2F transcription factors, identifying significant enrichment for signatures of corresponding factors and potential co-activators. Using time-scaled expression profiling of 3T3-L1 adipogenesis, we observed enrichment for signatures of known adipogenic factors such as C/EBPα, C/EBPβ and PPARγ, temporally coincident with previous reports. BSEA was also applied to tissue-specific expression profiles of human and mouse, identifying well-known tissue-specific transcription factors such as HNF-4 in liver and MEF-2 in heart along with other putative tissue-specific regulators. With extended versatility coping with various kinds of microarray dataset, BSEA can identify key regulators for global microarray data in which transcriptional regulation plays a major role. As a generalized method, BSEA would help to elucidate the transcriptional regulatory networks, the primary challenges in functional genomics. Show more

Keywords: Transcriptional regulation, cis-regulatory sequence, tissue-specific expression, microarray, ChIP-on-chip, enrichment analysis

Citation: In Silico Biology, vol. 6, no. 6, pp. 531-544, 2006

Authors: Valeyev, Najl V. | Downing, A. Kristina | Skorinkin, Andrei I. | Campbell, Iain D. | Kotov, Nikolai V.

Article Type: Research Article

Abstract: Cell migration has long been studied by a variety of techniques and many proteins have been implicated in its regulation. Integrins, key proteins that link the cell to the extracellular matrix, are central to adhesion complexes whose turnover defines the rate of cell locomotion. The formation and disassembly of these adhesions is regulated by both intracellular and extracellular factors. In this study we have focused on the Ca^{2+} -dependent protein network (module) that disassembles …the adhesion complexes. We have developed a mathematical model that includes the Ca^{2+} -dependent enzymes μ-calpain and phospholipase C (PLC) as well as IP_{3} receptors and stretch activated Ca^{2+} channels, all of which have been reported to regulate migration. The model also considers the spatial effects of Ca^{2+} propagation into lamella. Our model predicts differential activation of calpain at the leading and trailing edges of the cell. Since disassembly of integrin adhesive contacts is proportional to the degree of calpain activation, this leads to cell migration in a preferred direction. We show how the dynamics of Ca^{2+} spiking affects calpain activation and thus changes the disassembly rate of adhesions. The spiking is controlled by PLC activity and currents through stretch-activated Ca^{2+} channels. Our model thus combines the effects of various molecular factors and leads to a consistent explanation of the regulation of the rate and direction of cell migration. Show more

Keywords: Calcium, cell migration, adhesion turnover, mathematical modelling, μ-calpain regulation, cell detachment, cell polarization

Citation: In Silico Biology, vol. 6, no. 6, pp. 545-572, 2006

Authors: Bleakley, Kevin | Giudicelli, Véronique | Wu, Yan | Lefranc, Marie-Paule | Biau, Gérard

Article Type: Research Article

Abstract: The diversity of immunoglobulin (IG) and T cell receptor (TR) chains depends on several mechanisms: combinatorial diversity, which is a consequence of the number of V, D and J genes and the N-REGION diversity, which creates an extensive and clonal somatic diversity at the V-J and V-D-J junctions. For the IG, the diversity is further increased by somatic hypermutations. The number of different junctions per chain and per individual is estimated to be 10^{12} . …We have chosen the human TRAV-TRAJ junctions as an example in order to characterize the required criteria for a standardized analysis of the IG and TR V-J and V-D-J junctions, based on the IMGT-ONTOLOGY concepts, and to serve as a first IMGT junction reference set (IMGT®, http://imgt.cines.fr). We performed a thorough statistical analysis of 212 human rearranged TRAV-TRAJ sequences, which were aligned and analysed by the integrated IMGT/V-QUEST software, which includes IMGT/JunctionAnalysis, then manually expert-verified. Furthermore, we compared these 212 sequences with 37 other human TRAV-TRAJ junction sequences for which some particularities (potential sequence polymorphisms, sequencing errors, etc.) did not allow IMGT/JunctionAnalysis to provide the correct biological results, according to expert verification. Using statistical learning, we constructed an automatic warning system to predict if new, automatically analysed TRAV-TRAJ sequences should be manually re-checked. We estimated the robustness of this automatic warning system. Show more

Keywords: IMGT, T cell receptor, TRAV, TRAJ, variable gene, joining gene, junction, immunoglobulin, antibody, DNA rearrangement, IMGT/V-QUEST, IMGT/JunctionAnalysis, IMGT-ONTOLOGY, statistical learning, classification, k-Nearest Neighbors

Citation: In Silico Biology, vol. 6, no. 6, pp. 573-588, 2006

Authors: Brylinski, Michal | Kochanczyk, Marek | Konieczny, Leszek | Roterman, Irena

Article Type: Research Article

Abstract: Methods for biological function recognition in silico appeared to be useful also for identifying characteristics of structure-to-function relations. The introduction of a three-dimensional Gauss function was assumed to represent the hydrophobic core in a protein molecule. The discrepancy between idealized "fuzzy oil-drop" and the observed one in real proteins appeared to be localized in the ligation site or in the area of biological function related part of protein molecule. The examples of proteins presented …in this paper reveal that the structure-function relation can be evaluated and characterized also using the profile of the difference in value between idealized and real hydrophobicity distribution along the polypeptide chain. The specificity of particular polypeptide chain fragments in respect to their biological function and their specific participation in active site creation is discussed in this paper. The scale allowing comparison of different proteins in respect to their ligand-binding sites characteristics is introduced. Show more

Keywords: Hydrophobicity, biological function, active site, proteins of unknown biological function

Citation: In Silico Biology, vol. 6, no. 6, pp. 589-600, 2006

Authors: Joy, Saju | Nair, Parvathy S. | Hariharan, Ramkumar | Pillai, M. Radhakrishna

Article Type: Research Article

Abstract: Molecular docking and virtual screening based on molecular docking have become an integral part of many modern structure-based drug discovery efforts. Hence, it becomes a useful endeavor to evaluate existing docking programs, which can assist in the choice of the most suitable docking algorithm for any particular study. The objective of the current study was to evaluate the ability of ArgusLab 4.0, a relatively new molecular modeling package in which molecular docking is implemented, to reproduce …crystallographic binding orientations and to compare its accuracy with that of a well established commercial package, GOLD. The study also aimed to evaluate the effect of the nature of the binding site and ligand properties on docking accuracy. The three dimensional structures of a carefully chosen set of 75 pharmaceutically relevant protein-ligand complexes were used for the comparative study. The study revealed that the commercial package outperforms the freely available docking engine in almost all the parameters tested. However, the study also revealed that although lagging behind in accuracy, results from ArgusLab are biologically meaningful. This taken together with the fact that ArgusLab has an easy to use graphical user interface, means that it can be employed as an effective teaching tool to demonstrate molecular docking to beginners in this area. Show more

Keywords: Molecular docking, argusLab, GOLD, docking accuracy, protein-ligand complex

Citation: In Silico Biology, vol. 6, no. 6, pp. 601-605, 2006