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ISSN 1386-6338 (P)
ISSN 1434-3207 (E)
In Silico Biology is a scientific research journal for the advancement of computational models and simulations applied to complex biological phenomena. We publish peer-reviewed leading-edge biological, biomedical and biotechnological research in which computer-based (i.e.,
) modeling and analysis tools are developed and utilized to predict and elucidate dynamics of biological systems, their design and control, and their evolution. Experimental support may also be provided to support the computational analyses.
In Silico Biology aims to advance the knowledge of the principles of organization of living systems. We strive to provide computational frameworks for understanding how observable biological properties arise from complex systems. In particular, we seek for integrative formalisms to decipher cross-talks underlying systems level properties, ultimate aim of multi-scale models.
Studies published in
In Silico Biology generally use theoretical models and computational analysis to gain quantitative insights into regulatory processes and networks, cell physiology and morphology, tissue dynamics and organ systems. Special areas of interest include signal transduction and information processing, gene expression and gene regulatory networks, metabolism, proliferation, differentiation and morphogenesis, among others, and the use of multi-scale modeling to connect molecular and cellular systems to the level of organisms and populations.
In Silico Biology also publishes foundational research in which novel algorithms are developed to facilitate modeling and simulations. Such research must demonstrate application to a concrete biological problem.
In Silico Biology frequently publishes special issues on seminal topics and trends. Special issues are handled by Special Issue Editors appointed by the Editor-in-Chief. Proposals for special issues should be sent to the Editor-in-Chief.
About In Silico Biology
is a pendant to
(in the living system) and
(in the test tube) biological experiments, and implies the gain of insights by computer-based simulations and model analyses.
In Silico Biology (ISB) was founded in 1998 as a purely online journal. IOS Press became the publisher of the printed journal shortly after. Today, ISB is dedicated exclusively to biological systems modeling and multi-scale simulations and is published solely by IOS Press. The previous online publisher, Bioinformation Systems, maintains a website containing studies published between 1998 and 2010 for archival purposes.
We strongly support open communications and encourage researchers to share results and preliminary data with the community. Therefore, results and preliminary data made public through conference presentations, conference proceeding or posting of unrefereed manuscripts on preprint servers will not prohibit publication in ISB. However, authors are required to modify a preprint to include the journal reference (including DOI), and a link to the published article on the ISB website upon publication.
Abstract: Domain finding algorithms are useful to understand overall domain architecture and to propose biological function to gene products. Automated methods of applying these tools to large-scale genome studies often employ stringent thresholds to recognize sequence domains. The realization of additional domains can be tedious involving manual intervention but can lead to better understanding of overall biological function. We propose a multi-step approach for the further examination of unassigned linker regions that exploits…properties such as the conservation of domain architectures of homologous proteins to propose connections. Improved structure prediction is possible starting from initial domain architectures, obtained from simple 'domain finding' techniques, by concentrating on connecting unassigned regions. 254 unassigned regions have been examined in 114 gene products that potentially contain at least one class III adenylyl cyclase domain for a pilot study. Reliable structure prediction was possible for nearly 80% of unassigned regions. New connections were recognized that assign putative structure and function to these regions by indirect searches (26%. Several others (34%) could be associated with three-dimensional models that might pertain to novel folds and new functions with enough structural content and evolutionary conservation. The presence of additional domains will provide further clues to the overall function of the gene products and their recruitment in particular biochemical pathways.
Abstract: The use of sequences from specific organisms for annotation requires that it does not represent great loss of information and that the sequences available suffice for annotation. In order to investigate whether or not sequences from model organisms may suffice for annotation of sequences from the trematode Schistosoma mansoni, we performed local BLAST searches of S. mansoni sequences against other organisms sequences present in the NCBI database nr. Results have been inserted into a relational…database and hits to sequences from three model organisms, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens have been computed and compared to hits to sequences from other organisms present in nr; score values of each alignment have also been registered. Our observations have shown that a large fraction of orthologous proteins exists in the set of sequences from the three model organisms selected, and therefore a similar fraction of transcripts can be annotated when using either nr or model organism datasets. Moreover, hits to model organisms' sequences are largely as informative as nr. Results suggest that model organisms provide a reliable set of sequences to use as a reference database for S. mansoni sequence annotation, showing the clear possibility of using a restricted dataset of expected better quality for functional annotation and therefore supporting secondary database driven annotation approaches.
Abstract: Sequence based homology studies play an important role in evolutionary tracing and classification of proteins. Various methods are available to analyze biological sequence information. However, with the advent of proteomics era, there is a growing demand for analysis of huge amount of biological sequence information, and it has become necessary to have programs that would provide speedy analysis. ISHAN has been developed as a homology analysis package, built on various sequence analysis tools viz FASTA, ALIGN,…CLUSTALW, PHYLIP and CODONW (for DNA sequences). This JAVA application offers the user choice of analysis tools. For testing, ISHAN was applied to perform phylogenetic analysis for sets of Caspase 3 DNA sequences and NF- κB p105 amino acid sequences. By integrating several tools it has made analysis much faster and reduced manual intervention.
Abstract: Genomics and proteomics have added valuable information to our knowledgebase of the human biological system including the discovery of therapeutic targets and disease biomarkers. However, molecular profiling studies commonly result in the identification of novel proteins of unknown localization. A class of proteins of special interest is membrane proteins, in particular plasma membrane proteins. Despite their biological and medical significance, the 3-dimensional structures of less than 1% of plasma membrane proteins have…been determined. In order to aid in identification of membrane proteins, a number of computational methods have been developed. These tools operate by predicting the presence of transmembrane segments. Here, we utilized five topology prediction methods (TMHMM, SOSUI, waveTM, HMMTOP, and TopPred II) in order to estimate the ratio of integral membrane proteins in the human proteome. These methods employ different algorithms and include a newly-developed method (waveTM) that has yet to be tested on a large proteome database. Since these tools are prone for error mainly as a result of falsely predicting signal peptides as transmembrane segments, we have utilized an additional method, SignalP. Based on our analyses, the ratio of human proteins with transmembrane segments is estimated to fall between 15% and 39% with a consensus of 13%. Agreement among the programs is reduced further when both a positive identification of a membrane protein and the number of transmembrane segments per protein are considered. Such a broad range of prediction depends on the selectivity of the individual method in predicting integral membrane proteins. These methods can play a critical role in determining protein structure and, hence, identifying suitable drug targets in humans.
Abstract: Membrane organization describes the relationship of proteins to the membrane, that is, whether the protein crosses the membrane or is integral to the membrane and its orientation with respect to the membrane. Membrane organization is determined primarily by the presence of two features which target proteins to the secretory pathway: the endoplasmic reticulum signal peptide and the α-helical transmembrane domain. In order to generate membrane organization annotation of high quality, confidence and…throughput, the Membrane Organization (MemO) pipeline was developed, incorporating consensus feature prediction modules with integration and annotation rules derived from biological observations. The pipeline classifies proteins into six categories based on the presence or absence of predicted features: Soluble, intracellular proteins; Soluble, secreted proteins; Type I membrane proteins; Type II membrane proteins; Multi-span membrane proteins and Glycosylphosphatidylinositol anchored membrane proteins. The MemO pipeline represents an integrated strategy for the application of state-of-the-art bioinformatics tools to the annotation of protein membrane organization, a property which adds biological context to the large quantities of protein sequence information available.
Abstract: Synthetic Biology is a field involving synthesis of novel biological systems which are not generally found in nature. It has brought a new paradigm in science as it has enabled scientists to create life from the scratch, hence helping better understand the principles of biology. The viability of living organisms that use unnatural molecules is also being explored. Unconventional projects such as DNA playing tic-tac-toe, bacterial photographic film, etc. are taking biology to its extremes. The…field holds a promise for mass production of cheap drugs and programming bacteria to seek-and-destroy tumors in the body. However, the complexity of biological systems make the field a challenging one. In addition to this, there are other major technical and ethical challenges which need to be addressed before the field realizes its true potential.
Keywords: Synthetic biology, life engineering, bioengineering
Abstract: In the archaea, some tRNA precursors contain intron(s) not only in the anticodon loop region but also in diverse sites of the gene (intron-containing tRNA or cis-spliced tRNA). The parasite Nanoarchaeum equitans, a member of the Nanoarchaeota kingdom, creates functional tRNA from separate genes, one encoding the 5'-half and the other the 3'-half (split tRNA or trans-spliced tRNA). Although recent genome projects have revealed a huge amount of nucleotide sequence data in the…archaea, a comprehensive methodology for intron-containing and split tRNA searching is yet to be established. We therefore developed SPLITS, which is aimed at searching for any type of tRNA gene and is especially focused on intron-containing tRNAs or split tRNAs at the genome level. SPLITS initially predicts the bulge-helix-bulge splicing motif (a well-known, required structure in archaeal pre-tRNA introns) to determine and remove the intronic regions of tRNA genes. The intron-removed DNA sequences are automatically queried to tRNAscan-SE. SPLITS can predict known tRNAs with single introns located at unconventional sites on the genes (100%, tRNAs with double introns (85.7%, and known split tRNAs (100%). Our program will be very useful for identifying novel tRNA genes after completion of genome projects. The SPLITS source code is freely downloadable at http://splits.iab.keio.ac.jp/.
Abstract: In silico prediction of protein subcellular localization based on amino acid sequence can reveal valuable information about the protein's innate roles in the cell. Unfortunately, such prediction is made difficult because of complex protein sorting signals. Some prediction methods are based on searching for similar proteins with known localization, assuming that known homologs exist. However, it may not perform well on proteins with no known homolog. In contrast, machine learning-based approaches attempt to infer a predictive…model that describes the protein sorting signals. Alas, in doing so, it does not take advantage of known homologs (if they exist) by doing a simple "table lookup". Here, we capture the best of both worlds by combining both approaches. On a dataset with 12 locations, similarity-based and machine learning independently achieve an accuracy of 83.8% and 72.6%, respectively. Our hybrid approach yields an improved accuracy of 85.9%. We compared our method with three other methods' published results. For two of the methods, we used their published datasets for comparison. For the third we used the 12 location dataset. The Error Correcting Output Code algorithm was used to construct our predictive model. This algorithm gives attention to all the classes regardless of number of instances and led to high accuracy among each of the classes and a high prediction rate overall. We also illustrated how the machine learning classifier we use, built over a meaningful set of features can produce interpretable rules that may provide valuable insights into complex protein sorting mechanisms.
Abstract: Homology modeling of the catalase, CatC cloned and sequenced from rice (Oryza sativa L., cv Ratna an Indica cultivar) has been performed based on the crystal structure of the catalase CatF (PDB code 1m7s) by using the software MODELLER. With the aid of molecular mechanics and molecular dynamics methods, the final model is obtained and is further assessed by PROCHECK and VERIFY – 3D graph, which show that the final refined model is reliable. With this…model, a flexible docking study with the hydrogen peroxide, the substrate for catalase, is performed and the results indicate that Arg310, Asp343 and Arg346 in catalase are three important determinant residues in binding as they have strong hydrogen bonding contacts with the substrate. These hydrogen-bonding interactions play an important role for the stability of the complex. Our results may be helpful for further experimental investigations.
Abstract: This paper presents a computer aided design method useful for simulation of a set of proteolytic cleavages upon target proteins obtained from the Brookhaven Data Bank. The method was developed by using algorithms that are able to interface themselves with other software environments, in order to assist computer analyses in the molecular modelling field, and allowing the generation of molecular libraries containing protein fragments produced by simulated proteolysis. These libraries include structures that differ for…several amino acid deletions upon specified regions of the primary sequence. Target residues chosen for the simulation are compatible with enzymatic proteolysis methods used in conventional laboratory procedures. Furthermore, algorithms were able to identify a set of chemical-physical properties of the starting proteins, leading the simulation to find out the most suitable residues for proteolysis. The goal of these strategies is to generate fragments that are leaded to maintain the native-like condition of starting molecules, avoiding loss of conformational characteristics of the original tertiary structure. Proteins chosen for generating proteolytic libraries were represented by naphthalene 1,2 dioxygenase and Rigidoporus lignosus laccase.
Keywords: Molecular library generation, molecular modelling, closed loops, virtual proteolysis, screening and fragmentation, leading proteins, target amino acids, hydrophobic profile, secondary structure, sequence comparison, folding pathway, PDB files, NDO, RI laccase, 3D structures detection, enzymatic cleavage, protein design, laboratory procedures, soil bioremedation