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1.  A toolbox for developing bioinformatics software 
Briefings in Bioinformatics  2011;13(2):244-257.
Creating useful software is a major activity of many scientists, including bioinformaticians. Nevertheless, software development in an academic setting is often unsystematic, which can lead to problems associated with maintenance and long-term availibility. Unfortunately, well-documented software development methodology is difficult to adopt, and technical measures that directly improve bioinformatic programming have not been described comprehensively. We have examined 22 software projects and have identified a set of practices for software development in an academic environment. We found them useful to plan a project, support the involvement of experts (e.g. experimentalists), and to promote higher quality and maintainability of the resulting programs. This article describes 12 techniques that facilitate a quick start into software engineering. We describe 3 of the 22 projects in detail and give many examples to illustrate the usage of particular techniques. We expect this toolbox to be useful for many bioinformatics programming projects and to the training of scientific programmers.
doi:10.1093/bib/bbr035
PMCID: PMC3294241  PMID: 21803787
software development; programming; project management; software quality
2.  Databases and Bioinformatics Tools for the Study of DNA Repair 
DNA is continuously exposed to many different damaging agents such as environmental chemicals, UV light, ionizing radiation, and reactive cellular metabolites. DNA lesions can result in different phenotypical consequences ranging from a number of diseases, including cancer, to cellular malfunction, cell death, or aging. To counteract the deleterious effects of DNA damage, cells have developed various repair systems, including biochemical pathways responsible for the removal of single-strand lesions such as base excision repair (BER) and nucleotide excision repair (NER) or specialized polymerases temporarily taking over lesion-arrested DNA polymerases during the S phase in translesion synthesis (TLS). There are also other mechanisms of DNA repair such as homologous recombination repair (HRR), nonhomologous end-joining repair (NHEJ), or DNA damage response system (DDR). This paper reviews bioinformatics resources specialized in disseminating information about DNA repair pathways, proteins involved in repair mechanisms, damaging agents, and DNA lesions.
doi:10.4061/2011/475718
PMCID: PMC3200286  PMID: 22091405
3.  Identification and modeling of a phosphatase-like domain in a tRNA 2′-O-ribosyl phosphate transferase Rit1p 
Cell Cycle  2011;10(20):3566-3570.
Cytoplasmic initiator tRNAs from plants and fungi are excluded from participating in translational elongation by the presence of a unique 2′-phosphoribosyl modification of purine 64, introduced posttranscriptionally by the enzyme Rit1p. Members of the Rit1p family show no obvious similarity to other proteins or domains, there is no structural information available to guide experimental analyses, and the mechanism of action of this enzyme remains a mystery. Using protein fold recognition, we identified a phosphatase-like domain in the C-terminal part of Rit1p. A comparative model of the C-terminal domain was constructed and used to predict the function of conserved residues and to propose the mechanism of action of Rit1p. The model will facilitate experimental analyses of Rit1p and its interactions with the initiator tRNA substrate.
doi:10.4161/cc.10.20.17857
PMCID: PMC3266182  PMID: 22030622
fold recognition; homology modeling; tRNA modification; Rit1p; bioinformatics
4.  MetalionRNA: computational predictor of metal-binding sites in RNA structures 
Bioinformatics  2011;28(2):198-205.
Motivation: Metal ions are essential for the folding of RNA molecules into stable tertiary structures and are often involved in the catalytic activity of ribozymes. However, the positions of metal ions in RNA 3D structures are difficult to determine experimentally. This motivated us to develop a computational predictor of metal ion sites for RNA structures.
Results: We developed a statistical potential for predicting positions of metal ions (magnesium, sodium and potassium), based on the analysis of binding sites in experimentally solved RNA structures. The MetalionRNA program is available as a web server that predicts metal ions for RNA structures submitted by the user.
Availability: The MetalionRNA web server is accessible at http://metalionrna.genesilico.pl/.
Contact: iamb@genesilico.pl
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btr636
PMCID: PMC3259437  PMID: 22110243
5.  Novel non-specific DNA adenine methyltransferases 
Nucleic Acids Research  2011;40(5):2119-2130.
The mom gene of bacteriophage Mu encodes an enzyme that converts adenine to N6-(1-acetamido)-adenine in the phage DNA and thereby protects the viral genome from cleavage by a wide variety of restriction endonucleases. Mu-like prophage sequences present in Haemophilus influenzae Rd (FluMu), Neisseria meningitidis type A strain Z2491 (Pnme1) and H. influenzae biotype aegyptius ATCC 11116 do not possess a Mom-encoding gene. Instead, at the position occupied by mom in Mu they carry an unrelated gene that encodes a protein with homology to DNA adenine N6-methyltransferases (hin1523, nma1821, hia5, respectively). Products of the hin1523, hia5 and nma1821 genes modify adenine residues to N6-methyladenine, both in vitro and in vivo. All of these enzymes catalyzed extensive DNA methylation; most notably the Hia5 protein caused the methylation of 61% of the adenines in λ DNA. Kinetic analysis of oligonucleotide methylation suggests that all adenine residues in DNA, with the possible exception of poly(A)-tracts, constitute substrates for the Hia5 and Hin1523 enzymes. Their potential ‘sequence specificity’ could be summarized as AB or BA (where B = C, G or T). Plasmid DNA isolated from Escherichia coli cells overexpressing these novel DNA methyltransferases was resistant to cleavage by many restriction enzymes sensitive to adenine methylation.
doi:10.1093/nar/gkr1039
PMCID: PMC3299994  PMID: 22102579
6.  DARS-RNP and QUASI-RNP: New statistical potentials for protein-RNA docking 
BMC Bioinformatics  2011;12:348.
Background
Protein-RNA interactions play fundamental roles in many biological processes. Understanding the molecular mechanism of protein-RNA recognition and formation of protein-RNA complexes is a major challenge in structural biology. Unfortunately, the experimental determination of protein-RNA complexes is tedious and difficult, both by X-ray crystallography and NMR. For many interacting proteins and RNAs the individual structures are available, enabling computational prediction of complex structures by computational docking. However, methods for protein-RNA docking remain scarce, in particular in comparison to the numerous methods for protein-protein docking.
Results
We developed two medium-resolution, knowledge-based potentials for scoring protein-RNA models obtained by docking: the quasi-chemical potential (QUASI-RNP) and the Decoys As the Reference State potential (DARS-RNP). Both potentials use a coarse-grained representation for both RNA and protein molecules and are capable of dealing with RNA structures with posttranscriptionally modified residues. We compared the discriminative power of DARS-RNP and QUASI-RNP for selecting rigid-body docking poses with the potentials previously developed by the Varani and Fernandez groups.
Conclusions
In both bound and unbound docking tests, DARS-RNP showed the highest ability to identify native-like structures. Python implementations of DARS-RNP and QUASI-RNP are freely available for download at http://iimcb.genesilico.pl/RNP/
doi:10.1186/1471-2105-12-348
PMCID: PMC3179970  PMID: 21851628
RNA; protein; RNP; macromolecular docking; complex modeling; structural bioinformatics
7.  Evidence for an evolutionary antagonism between Mrr and Type III modification systems 
Nucleic Acids Research  2011;39(14):5991-6001.
The Mrr protein of Escherichia coli is a laterally acquired Type IV restriction endonuclease with specificity for methylated DNA. While Mrr nuclease activity can be elicited by high-pressure stress in E. coli MG1655, its (over)expression per se does not confer any obvious toxicity. In this study, however, we discovered that Mrr of E. coli MG1655 causes distinct genotoxicity when expressed in Salmonella typhimurium LT2. Genetic screening enabled us to contribute this toxicity entirely to the presence of the endogenous Type III restriction modification system (StyLTI) of S. typhimurium LT2. The StyLTI system consists of the Mod DNA methyltransferase and the Res restriction endonuclease, and we revealed that expression of the LT2 mod gene was sufficient to trigger Mrr activity in E. coli MG1655. Moreover, we could demonstrate that horizontal acquisition of the MG1655 mrr locus can drive the loss of endogenous Mod functionality present in S. typhimurium LT2 and E. coli ED1a, and observed a strong anti-correlation between close homologues of MG1655 mrr and LT2 mod in the genome database. This apparent evolutionary antagonism is further discussed in the light of a possible role for Mrr as defense mechanism against the establishment of epigenetic regulation by foreign DNA methyltransferases.
doi:10.1093/nar/gkr219
PMCID: PMC3152355  PMID: 21504983
8.  2′-O-ribose methylation of cap2 in human: function and evolution in a horizontally mobile family 
Nucleic Acids Research  2011;39(11):4756-4768.
The 5′ cap of human messenger RNA consists of an inverted 7-methylguanosine linked to the first transcribed nucleotide by a unique 5′–5′ triphosphate bond followed by 2′-O-ribose methylation of the first and often the second transcribed nucleotides, likely serving to modify efficiency of transcript processing, translation and stability. We report the validation of a human enzyme that methylates the ribose of the second transcribed nucleotide encoded by FTSJD1, henceforth renamed HMTR2 to reflect function. Purified recombinant hMTr2 protein transfers a methyl group from S-adenosylmethionine to the 2′-O-ribose of the second nucleotide of messenger RNA and small nuclear RNA. Neither N7 methylation of the guanosine cap nor 2′-O-ribose methylation of the first transcribed nucleotide are required for hMTr2, but the presence of cap1 methylation increases hMTr2 activity. The hMTr2 protein is distributed throughout the nucleus and cytosol, in contrast to the nuclear hMTr1. The details of how and why specific transcripts undergo modification with these ribose methylations remains to be elucidated. The 2′-O-ribose RNA cap methyltransferases are present in varying combinations in most eukaryotic and many viral genomes. With the capping enzymes in hand their biological purpose can be ascertained.
doi:10.1093/nar/gkr038
PMCID: PMC3113572  PMID: 21310715
9.  ModeRNA: a tool for comparative modeling of RNA 3D structure 
Nucleic Acids Research  2011;39(10):4007-4022.
RNA is a large group of functionally important biomacromolecules. In striking analogy to proteins, the function of RNA depends on its structure and dynamics, which in turn is encoded in the linear sequence. However, while there are numerous methods for computational prediction of protein three-dimensional (3D) structure from sequence, with comparative modeling being the most reliable approach, there are very few such methods for RNA. Here, we present ModeRNA, a software tool for comparative modeling of RNA 3D structures. As an input, ModeRNA requires a 3D structure of a template RNA molecule, and a sequence alignment between the target to be modeled and the template. It must be emphasized that a good alignment is required for successful modeling, and for large and complex RNA molecules the development of a good alignment usually requires manual adjustments of the input data based on previous expertise of the respective RNA family. ModeRNA can model post-transcriptional modifications, a functionally important feature analogous to post-translational modifications in proteins. ModeRNA can also model DNA structures or use them as templates. It is equipped with many functions for merging fragments of different nucleic acid structures into a single model and analyzing their geometry. Windows and UNIX implementations of ModeRNA with comprehensive documentation and a tutorial are freely available.
doi:10.1093/nar/gkq1320
PMCID: PMC3105415  PMID: 21300639
10.  RNA and protein 3D structure modeling: similarities and differences 
Journal of Molecular Modeling  2011;17(9):2325-2336.
In analogy to proteins, the function of RNA depends on its structure and dynamics, which are encoded in the linear sequence. While there are numerous methods for computational prediction of protein 3D structure from sequence, there have been very few such methods for RNA. This review discusses template-based and template-free approaches for macromolecular structure prediction, with special emphasis on comparison between the already tried-and-tested methods for protein structure modeling and the very recently developed “protein-like” modeling methods for RNA. We highlight analogies between many successful methods for modeling of these two types of biological macromolecules and argue that RNA 3D structure can be modeled using “protein-like” methodology. We also highlight the areas where the differences between RNA and proteins require the development of RNA-specific solutions.
FigureApproaches for predicting RNA structure. Top: Template-free modeling. Bottom: Template-based modeling
doi:10.1007/s00894-010-0951-x
PMCID: PMC3168752  PMID: 21258831
Assessment; Prediction; RNA; Structure; Tertiary

Results 1-10 (10)