Biomedical subjects

Saraswathi Abhiman

Publications and source records attributed to Saraswathi Abhiman.

4 recordsLinked to original sources

PubMed2006

Prediction of function divergence in protein families using the substitution rate variation parameter alpha.

Protein families typically embody a range of related functions and may thus be decomposed into subfamilies with, for example, distinct substrate specificities. Detection of functionally divergent subfamilies is possible by methods for recognizing branches of adaptive evolution in a gene tree. As the number of genome sequences is growing rapidly, it is highly desirable to automatically detect subfamily function divergence. To this end, we here introduce a method for large-scale prediction of function divergence within protein families. It is called the alpha shift measure (ASM) as it is based on detecting a shift in the shape parameter (alpha [alpha]) of the substitution rate gamma distribution. Four different methods for estimating alpha were investigated. We benchmarked the accuracy of ASM using function annotation from Enzyme Commission numbers within Pfam protein families divided into subfamilies by the automatic tree-based method BETE. In a test using 563 subfamily pairs in 162 families, ASM outperformed functional site-based methods using rate or conservation shifting (rate shift measure [RSM] and conservation shift measure [CSM]). The best results were obtained using the "GZ-Gamma" method for estimating alpha. By combining ASM with RSM and CSM using linear discriminant analysis, the prediction accuracy was further improved.

Algorithms↗

PubMed2005

Large-scale prediction of function shift in protein families with a focus on enzymatic function.

Protein function shift can be predicted from sequence comparisons, either using positive selection signals or evolutionary rate estimation. None of the methods have been validated on large datasets, however. Here we investigate existing and novel methods for protein function shift prediction, and benchmark the accuracy against a large dataset of proteins with known enzymatic functions. Function change was predicted between subfamilies by identifying two kinds of sites in a multiple sequence alignment: Conservation-Shifting Sites (CSS), which are conserved in two subfamilies using two different amino acid types, and Rate-Shifting Sites (RSS), which have different evolutionary rates in two subfamilies. CSS were predicted by a new entropy-based method, and RSS using the Rate-Shift program. In principle, the more CSS and RSS between two subfamilies, the more likely a function shift between them. A test dataset was built by extracting subfamilies from Pfam with different EC numbers that belong to the same domain family. Subfamilies were generated automatically using a phylogenetic tree-based program, BETE. The dataset comprised 997 subfamily pairs with four or more members per subfamily. We observed a significant increase in CSS and RSS for subfamily comparisons with different EC numbers compared to cases with same EC numbers. The discrimination was better using RSS than CSS, and was more pronounced for larger families. Combining RSS and CSS by discriminant analysis improved classification accuracy to 71%. The method was applied to the Pfam database and the results are available at http://FunShift.cgb.ki.se. A closer examination of some superfamily comparisons showed that single EC numbers sometimes embody distinct functional classes. Hence, the measured accuracy of function shift is underestimated.

Amino Acid Sequence↗

PubMed2005

FunShift: a database of function shift analysis on protein subfamilies.

Members of a protein family normally have a general biochemical function in common, but frequently one or more subgroups have evolved a slightly different function, such as different substrate specificity. It is important to detect such function shifts for a more accurate functional annotation. The FunShift database described here is a compilation of function shift analysis performed between subfamilies in protein families. It consists of two main components: (i) subfamilies derived from protein domain families and (ii) pairwise subfamily comparisons analyzed for function shift. The present release, FunShift 12, was derived from Pfam 12 and consists of 151,934 subfamilies derived from 7300 families. We carried out function shift analysis by two complementary methods on families with up to 500 members. From a total of 179,210 subfamily pairs, 62,384 were predicted to be functionally shifted in 2881 families. Each subfamily pair is provided with a markup of probable functional specificity-determining sites. Tools for searching and exploring the data are provided to make this database a valuable resource for protein function annotation. Knowledge of these functionally important sites will be useful for experimental biologists performing functional mutation studies. FunShift is available at http://FunShift.cgb.ki.se.

Databases, Protein↗

PubMed2003

Hepatitis C virus internal ribosome entry site-mediated translation is stimulated by specific interaction of independent regions of human La autoantigen.

The human La autoantigen has been shown to interact with the internal ribosome entry site (IRES) of hepatitis C virus (HCV) in vitro. Using a yeast three-hybrid system, we demonstrated that, in addition to full-length La protein, both N- and C-terminal halves were able to interact with HCV IRES in vivo. The exogenous addition of purified full-length and truncated La proteins in rabbit reticulocyte lysate showed dose-dependent stimulation of HCV IRES-mediated translation. However, an additive effect was achieved adding the terminal halves together in the reaction, suggesting that both might play critical roles in achieving full stimulatory activity of the full-length La protein. Using computational analysis, three-dimensional structures of the RNA recognition motifs (RRM) of the La protein were independently modeled. Of the three putative RRMs, RRM2 was predicted to have a good binding pocket for the interaction with the HCV IRES around the GCAC motif near the initiator AUG and RRM3 binds perhaps in a different location. This observation was further investigated by the filter-binding and toe-printing assays. The results presented here strongly suggest that both the N- and C-terminal halves can interact independently with the HCV IRES and are involved in stimulating internal initiation of translation.

Amino Acid Sequence↗