Biomedical subjects

Stella Veretnik

Publications and source records attributed to Stella Veretnik.

4 recordsLinked to original sources

PubMed2006

Partitioning protein structures into domains: why is it so difficult?

This analysis takes an in-depth look into the difficulties encountered by automatic methods for domain decomposition from three-dimensional structure. The analysis involves a multi-faceted set of criteria including the integrity of secondary structure elements, the tendency toward fragmentation of domains, domain boundary consistency and topology. The strength of the analysis comes from the use of a new comprehensive benchmark dataset, which is based on consensus among experts (CATH, SCOP and AUTHORS of the 3D structures) and covers 30 distinct architectures and 211 distinct topologies as defined by CATH. Furthermore, over 66% of the structures are multi-domain proteins; each domain combination occurring once per dataset. The performance of four automatic domain assignment methods, DomainParser, NCBI, PDP and PUU, is carefully analyzed using this broad spectrum of topology combinations and knowledge of rules and assumptions built into each algorithm. We conclude that it is practically impossible for an automatic method to achieve the level of performance of human experts. However, we propose specific improvements to automatic methods as well as broadening the concept of a structural domain. Such work is prerequisite for establishing improved approaches to domain recognition. (The benchmark dataset is available from http://pdomains.sdsc.edu).

Computational Biology↗

PubMed2004

Toward consistent assignment of structural domains in proteins.

The assignment of protein domains from three-dimensional structure is critically important in understanding protein evolution and function, yet little quality assurance has been performed. Here, the differences in the assignment of structural domains are evaluated using six common assignment methods. Three human expert methods (AUTHORS (authors' annotation), CATH and SCOP) and three fully automated methods (DALI, DomainParser and PDP) are investigated by analysis of individual methods against the author's assignment as well as analysis based on the consensus among groups of methods (only expert, only automatic, combined). The results demonstrate that caution is recommended in using current domain assignments, and indicates where additional work is needed. Specifically, the major factors responsible for conflicting domain assignments between methods, both experts and automatic, are: (1) the definition of very small domains; (2) splitting secondary structures between domains; (3) the size and number of discontinuous domains; (4) closely packed or convoluted domain-domain interfaces; (5) structures with large and complex architectures; and (6) the level of significance placed upon structural, functional and evolutionary concepts in considering structural domain definitions. A web-based resource that focuses on the results of benchmarking and the analysis of domain assignments is available at

Algorithms↗

PubMed2003

The PlantsP and PlantsT Functional Genomics Databases.

PlantsP and PlantsT allow users to quickly gain a global understanding of plant phosphoproteins and plant membrane transporters, respectively, from evolutionary relationships to biochemical function as well as a deep understanding of the molecular biology of individual genes and their products. As one database with two functionally different web interfaces, PlantsP and PlantsT are curated plant-specific databases that combine sequence-derived information with experimental functional-genomics data. PlantsP focuses on proteins involved in the phosphorylation process (i.e., kinases and phosphatases), whereas PlantsT focuses on membrane transport proteins. Experimentally, PlantsP provides a resource for information on a collection of T-DNA insertion mutants (knockouts) in each kinase and phosphatase, primarily in Arabidopsis thaliana, and PlantsT uniquely combines experimental data regarding mineral composition (derived from inductively coupled plasma atomic emission spectroscopy) of mutant and wild-type strains. Both databases provide extensive information on motifs and domains, detailed information contributed by individual experts in their respective fields, and descriptive information drawn directly from the literature. The databases incorporate a unique user annotation and review feature aimed at acquiring expert annotation directly from the plant biology community. PlantsP is available at http://plantsp.sdsc.edu and PlantsT is available at http://plantst.sdsc.edu.

Arabidopsis↗

PubMed2002

The complement of protein phosphatase catalytic subunits encoded in the genome of Arabidopsis.

Reversible protein phosphorylation is critically important in the modulation of a wide variety of cellular functions. Several families of protein phosphatases remove phosphate groups placed on key cellular proteins by protein kinases. The complete genomic sequence of the model plant Arabidopsis permits a comprehensive survey of the phosphatases encoded by this organism. Several errors in the sequencing project gene models were found via analysis of predicted phosphatase coding sequences. Structural sequence probes from aligned and unaligned sequence models, and all-against-all BLAST searches, were used to identify 112 phosphatase catalytic subunit sequences, distributed among the serine (Ser)/threonine (Thr) phosphatases (STs) of the protein phosphatase P (PPP) family, STs of the protein phosphatase M (PPM) family (protein phosphatases 2C [PP2Cs] subfamily), protein tyrosine (Tyr) phosphatases (PTPs), low-M(r) protein Tyr phosphatases, and dual-specificity (Tyr and Ser/Thr) phosphatases (DSPs). The Arabidopsis genome contains an abundance of PP2Cs (69) and a dearth of PTPs (one). Eight sequences were identified as new protein phosphatase candidates: five dual-specificity phosphatases and three PP2Cs. We used phylogenetic analyses to infer clustering patterns reflecting sequence similarity and evolutionary ancestry. These clusters, particularly for the largely unexplored PP2C set, will be a rich source of material for plant biologists, allowing the systematic sampling of protein function by genetic and biochemical means.

Animals↗