Biomedical subjects

Rajdeep Das

Publications and source records attributed to Rajdeep Das.

4 recordsLinked to original sources

PubMed2006

Computational prediction of methylation status in human genomic sequences.

Epigenetic effects in mammals depend largely on heritable genomic methylation patterns. We describe a computational pattern recognition method that is used to predict the methylation landscape of human brain DNA. This method can be applied both to CpG islands and to non-CpG island regions. It computes the methylation propensity for an 800-bp region centered on a CpG dinucleotide based on specific sequence features within the region. We tested several classifiers for classification performance, including K means clustering, linear discriminant analysis, logistic regression, and support vector machine. The best performing classifier used the support vector machine approach. Our program (called hdfinder) presently has a prediction accuracy of 86%, as validated with CpG regions for which methylation status has been experimentally determined. Using hdfinder, we have depicted the entire genomic methylation patterns for all 22 human autosomes.

Algorithms↗

PubMed2005

Large-scale structure of genomic methylation patterns.

The mammalian genome depends on patterns of methylated cytosines for normal function, but the relationship between genomic methylation patterns and the underlying sequence is unclear. We have characterized the methylation landscape of the human genome by global analysis of patterns of CpG depletion and by direct sequencing of 3073 unmethylated domains and 2565 methylated domains from human brain DNA. The genome was found to consist of short (<4 kb) unmethylated domains embedded in a matrix of long methylated domains. Unmethylated domains were enriched in promoters, CpG islands, and first exons, while methylated domains comprised interspersed and tandem-repeated sequences, exons other than first exons, and non-annotated single-copy sequences that are depleted in the CpG dinucleotide. The enrichment of regulatory sequences in the relatively small unmethylated compartment suggests that cytosine methylation constrains the effective size of the genome through the selective exposure of regulatory sequences. This buffers regulatory networks against changes in total genome size and provides an explanation for the C value paradox, which concerns the wide variations in genome size that scale independently of gene number. This suggestion is compatible with the finding that cytosine methylation is universal among large-genome eukaryotes, while many eukaryotes with genome sizes <5 x 10(8) bp do not methylate their DNA.

Animals↗

PubMed2004

A method using active-site sequence conservation to find functional shifts in protein families: application to the enzymes of central metabolism, leading to the identification of an anomalous isocitrate dehydrogenase in pathogens.

We have introduced a method to identify functional shifts in protein families. Our method is based on the calculation of an active-site conservation ratio, which we call the "ASC ratio." For a structurally based alignment of a protein family, this ratio is the average sequence similarity of the active-site region compared to the full-length protein. The active-site region is defined as all the residues within a certain radius of the known functionally important groups. Using our method, we have analyzed enzymes of central metabolism from a large number of genomes (35). We found that for most of the enzymes, the active-site region is more highly conserved than the full-length sequence. However, for three tricarboxylic acid (TCA)-cycle enzymes, active-site sequences are considerably more diverged (than full-length ones). In particular, we were able to identify in six pathogens a novel isocitrate dehydrogenase that has very low sequence similarity around the active site. Detailed sequence-structure analysis indicates that while the active-site structure of isocitrate dehydrogenase is most likely similar between pathogens and nonpathogens, the unusual sequence divergence could result from an extra domain added at the N-terminus. This domain has a leucine-rich motif similar one in the Yersinia pestis cytotoxin and may therefore confer additional pathogenic functions.

Amino Acid Motifs↗

PubMed2003

Strategies for structural proteomics of prokaryotes: Quantifying the advantages of studying orthologous proteins and of using both NMR and X-ray crystallography approaches.

Only about half of non-membrane-bound proteins encoded by either bacterial or archaeal genomes are soluble when expressed in Escherichia coli (Yee et al., Proc Natl Acad Sci USA 2002;99:1825-1830; Christendat et al., Prog Biophys Mol Biol 200;73:339-345). This property limits genome-scale functional and structural proteomics studies, which depend on having a recombinant, soluble version of each protein. An emerging strategy to increase the probability of deriving a soluble derivative of a protein is to study different sequence homologues of the same protein, including representatives from thermophilic organisms, based on the assumption that the stability of these proteins will facilitate structural analysis. To estimate the relative merits of this strategy, we compared the recombinant expression, solubility, and suitability for structural analysis by NMR and/or X-ray crystallography for 68 pairs of homologous proteins from E. coli and Thermotoga maritima. A sample suitable for structural studies was obtained for 62 of the 68 pairs of homologs under standardized growth and purification procedures. Fourteen (eight E. coli and six T. maritima proteins) samples generated NMR spectra of a quality suitable for structure determination and 30 (14 E. coli and 16 T. maritima proteins) samples formed crystals. Only three (one E. coli and two T. maritima proteins) samples both crystallized and had excellent NMR properties. The conclusions from this work are: (1) The inclusion of even a single ortholog of a target protein increases the number of samples for structural studies almost twofold; (2) there was no clear advantage to the use of thermophilic proteins to generate samples for structural studies; and (3) for the small proteins analyzed here, the use of both NMR and crystallography approaches almost doubled the number of samples for structural studies.

Archaeal Proteins↗