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Chittibabu Guda

Publications and source records attributed to Chittibabu Guda.

12 recordsLinked to original sources
PubMed2005

CZH proteins: a new family of Rho-GEFs.

The Rho family of small GTPases are important regulators of multiple cellular activities and, most notably, reorganization of the actin cytoskeleton. Dbl-homology (DH)-domain-containing proteins are the classical guanine nucleotide exchange factors (GEFs) responsible for activation of Rho GTPases. However, members of a newly discovered family can also act as Rho-GEFs. These CZH proteins include: CDM (Ced-5, Dock180 and Myoblast city) proteins, which activate Rac; and zizimin proteins, which activate Cdc42. The family contains 11 mammalian proteins and has members in many other eukaryotes. The GEF activity is carried out by a novel, DH-unrelated domain named the DOCKER, CZH2 or DHR2 domain. CZH proteins have been implicated in cell migration, phagocytosis of apoptotic cells, T-cell activation and neurite outgrowth, and probably arose relatively early in eukaryotic evolution.

Animals↗
PubMed2005

pTARGET [corrected] a new method for predicting protein subcellular localization in eukaryotes.

MOTIVATION: There is a scarcity of efficient computational methods for predicting protein subcellular localization in eukaryotes. Currently available methods are inadequate for genome-scale predictions with several limitations. Here, we present a new prediction method, pTARGET that can predict proteins targeted to nine different subcellular locations in the eukaryotic animal species. RESULTS: The nine subcellular locations predicted by pTARGET include cytoplasm, endoplasmic reticulum, extracellular/secretory, golgi, lysosomes, mitochondria, nucleus, plasma membrane and peroxisomes. Predictions are based on the location-specific protein functional domains and the amino acid compositional differences across different subcellular locations. Overall, this method can predict 68-87% of the true positives at accuracy rates of 96-99%. Comparison of the prediction performance against PSORT showed that pTARGET prediction rates are higher by 11-60% in 6 of the 8 locations tested. Besides, the pTARGET method is robust enough for genome-scale prediction of protein subcellular localizations since, it does not rely on the presence of signal or target peptides. AVAILABILITY: A public web server based on the pTARGET method is accessible at the URL http://bioinformatics.albany.edu/~ptarget. Datasets used for developing pTARGET can be downloaded from this web server. Source code will be available on request from the corresponding author.

Algorithms↗
PubMed2004

MITOPRED: a web server for the prediction of mitochondrial proteins.

MITOPRED web server enables prediction of nucleus-encoded mitochondrial proteins in all eukaryotic species. Predictions are made using a new algorithm based primarily on Pfam domain occurrence patterns in mitochondrial and non-mitochondrial locations. Pre-calculated predictions are instantly accessible for proteomes of Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila, Homo sapiens, Mus musculus and Arabidopsis species as well as all the eukaryotic sequences in the Swiss-Prot and TrEMBL databases. Queries, at different confidence levels, can be made through four distinct options: (i) entering Swiss-Prot/TrEMBL accession numbers; (ii) uploading a local file with such accession numbers; (iii) entering protein sequences; (iv) uploading a local file containing protein sequences in FASTA format. Automated updates are scheduled for the pre-calculated prediction database so as to provide access to the most current data. The server, its documentation and the data are available from http://mitopred.sdsc.edu.

Algorithms↗
PubMed2004

SledgeHMMER: a web server for batch searching the Pfam database.

The SledgeHMMER web server is intended for genome-scale searching of the Pfam database without having to install this database and the HMMER software locally. The server implements a parallelized version of hmmpfam, the program used for searching the Pfam HMM database. Pfam search results have been calculated for the entire Swiss-Prot and TrEmbl database sequences (approximately 1.2 million) on 256 processors of IA64-based teragrid machines. The Pfam database can be searched in local, glocal or merged mode, using either gathering or E-value thresholds. Query sequences are first matched against the pre-calculated entries to retrieve results, and those without matches are processed through a new search process. Results are emailed in a space-delimited tabular format upon completion of the search. While most other Pfam-searching web servers set a limit of one sequence per query, this server processes batch sequences with no limit on the number of input sequences. The web server and downloadable data are accessible from http://SledgeHmmer.sdsc.edu.

Algorithms↗
PubMed2004

CE-MC: a multiple protein structure alignment server.

CE-MC server (http://cemc.sdsc.edu) provides a web-based facility for the alignment of multiple protein structures based on C-alpha coordinate distances, using combinatorial extension (CE) and Monte Carlo (MC) optimization methods. Alignments are possible for user-selected PDB (Protein Data Bank) chains as well as for user-uploaded structures or the combination of the two. The whole process of generating multiple structure alignments involves three distinct steps, i.e. all-to-all pairwise alignment using the CE algorithm, iterative global optimization of a multiple alignment using the MC algorithm and formatting MC results using the JOY program. The server can be used to get multiple alignments for up to 25 protein structural chains with the flexibility of uploading multiple coordinate files and performing multiple structure alignment for user-selected PDB chains. For large-scale jobs and local installation of the CE-MC program, users can download the source code and precompiled binaries from the web server.

Algorithms↗
PubMed2004

MITOPRED: a genome-scale method for prediction of nucleus-encoded mitochondrial proteins.

MOTIVATION: Currently available methods for the prediction of subcellular location of mitochondrial proteins rely largely on the presence of mitochondrial targeting signals in the protein sequences. However, a large fraction of mitochondrial proteins lack such signals, making those tools ineffective for genome-scale prediction of mitochondria-targeted proteins. Here, we propose a method for genome-scale prediction of nucleus-encoded mitochondrial proteins. The new method, MITOPRED, is based on the Pfam domain occurrence patterns and the amino acid compositional differences between mitochondrial and non-mitochondrial proteins. RESULTS: MITOPRED could predict mitochondrial proteins with 100% specificity at a 44% sensitivity rate and with 67% specificity at 99% sensitivity. Additionally, it was sufficiently robust to predict mitochondrial proteins across different eukaryotic species with similar accuracy. Based on Matthews correlation coefficient measure, the prediction performance of MITOPRED is clearly superior (0.73) to those of the two popular methods TargetP (0.51) and PSORT (0.53). Using this method, we predicted the nucleus-encoded mitochondrial proteins from six complete genomes (three invertebrate, two vertebrate and one plant species) and estimated the total number in each genome. In human, our method estimated the existence of 1362 mitochondrial proteins corresponding to 4.8% of the total proteome. AVAILABILITY: MITOPRED program is freely accessible at http://mitopred.sdsc.edu. Source code is available on request from the authors. SUPPLEMENTARY INFORMATION: Training data sets are also available at http://mitopred.sdsc.edu

Algorithms↗
PubMed2002

Structural genomics of the Thermotoga maritima proteome implemented in a high-throughput structure determination pipeline.

Structural genomics is emerging as a principal approach to define protein structure-function relationships. To apply this approach on a genomic scale, novel methods and technologies must be developed to determine large numbers of structures. We describe the design and implementation of a high-throughput structural genomics pipeline and its application to the proteome of the thermophilic bacterium Thermotoga maritima. By using this pipeline, we successfully cloned and attempted expression of 1,376 of the predicted 1,877 genes (73%) and have identified crystallization conditions for 432 proteins, comprising 23% of the T. maritima proteome. Representative structures from TM0423 glycerol dehydrogenase and TM0449 thymidylate synthase-complementing protein are presented as examples of final outputs from the pipeline.

Cloning, Molecular↗