Biomedical subjects

N Siew

Publications and source records attributed to N Siew.

5 recordsLinked to original sources

PubMed2001

Genomic-scale comparison of sequence- and structure-based methods of function prediction: does structure provide additional insight?

A function annotation method using the sequence-to-structure-to-function paradigm is applied to the identification of all disulfide oxidoreductases in the Saccharomyces cerevisiae genome. The method identifies 27 sequences as potential disulfide oxidoreductases. All previously known thioredoxins, glutaredoxins, and disulfide isomerases are correctly identified. Three of the 27 predictions are probable false-positives. Three novel predictions, which subsequently have been experimentally validated, are presented. Two additional novel predictions suggest a disulfide oxidoreductase regulatory mechanism for two subunits (OST3 and OST6) of the yeast oligosaccharyltransferase complex. Based on homology, this prediction can be extended to a potential tumor suppressor gene, N33, in humans, whose biochemical function was not previously known. Attempts to obtain a folded, active N33 construct to test the prediction were unsuccessful. The results show that structure prediction coupled with biochemically relevant structural motifs is a powerful method for the function annotation of genome sequences and can provide more detailed, robust predictions than function prediction methods that rely on sequence comparison alone.

Algorithms↗

PubMed2000

MaxSub: an automated measure for the assessment of protein structure prediction quality.

MOTIVATION: Evaluating the accuracy of predicted models is critical for assessing structure prediction methods. Because this problem is not trivial, a large number of different assessment measures have been proposed by various authors, and it has already become an active subfield of research (Moult et al. (1997,1999) and CAFASP (Fischer et al. 1999) prediction experiments have demonstrated that it has been difficult to choose one single, 'best' method to be used in the evaluation. Consequently, the CASP3 evaluation was carried out using an extensive set of especially developed numerical measures, coupled with human-expert intervention. As part of our efforts towards a higher level of automation in the structure prediction field, here we investigate the suitability of a fully automated, simple, objective, quantitative and reproducible method that can be used in the automatic assessment of models in the upcoming CAFASP2 experiment. Such a method should (a) produce one single number that measures the quality of a predicted model and (b) perform similarly to human-expert evaluations. RESULTS: MaxSub is a new and independently developed method that further builds and extends some of the evaluation methods introduced at CASP3. MaxSub aims at identifying the largest subset of C(alpha) atoms of a model that superimpose 'well' over the experimental structure, and produces a single normalized score that represents the quality of the model. Because there exists no evaluation method for assessment measures of predicted models, it is not easy to evaluate how good our new measure is. Even though an exact comparison of MaxSub and the CASP3 assessment is not straightforward, here we use a test-bed extracted from the CASP3 fold-recognition models. A rough qualitative comparison of the performance of MaxSub vis-a-vis the human-expert assessment carried out at CASP3 shows that there is a good agreement for the more accurate models and for the better predicting groups. As expected, some differences were observed among the medium to poor models and groups. Overall, the top six predicting groups ranked using the fully automated MaxSub are also the top six groups ranked at CASP3. We conclude that MaxSub is a suitable method for the automatic evaluation of models.

Algorithms↗

PubMed2000

A novel computational method for predicting the transmembrane structure of G-protein coupled receptors: application to human C5aR and C3aR.

A novel algorithm was applied to the sequences of bacteriorhodopsin (BRh), of rhodopsin (Rh), and of the two human anaphylatoxin receptors, C5a-receptor (hC5aR) and C3a-receptor (hC3aR), that predicts their transmembrane domains (TMD) according to energy criteria alone, on the basis of their sequences and a template structure for each. Two consecutive criteria were applied for the predictions: the first is hydrophobicity of a sequence of residues, which determines the candidate stretches of residues that form one of the transmembrane helices. The second criterion is an energy function composed of inter residue contact energies, of hydrophobic contributions due to membrane exposure and of the interactions of a few residues with the phospholipid head groups. The sequence of candidate residues for each helix is longer than that of the template, and is finally determined by threading each of the candidate stretches on each of the template helices and evaluating the energy for all possible configurations. Contact energies between residues were taken from a database (Miyazawa S and Jernigan RL (1996) J Mol Biol 256 623-44). The algorithm predicts well the TMD structure of BRh based on its own template, and the TMD structure of Rh conforms well with the model of Baldwin et al (Baldwin JM Schertler GFX and Unger VM (1997) J Biol Chem 272 144-64). Results for the construction of the TMD of hC5aR and hC3aR were compared, employing the template structure of Rh. Most of the results for these receptors are in accord with alignments and with mutation experiments on hC5aR and hC3aR. The predictions may serve as a basis for future mutagenesis experiments of these receptors.

Algorithms↗

PubMed1999

Structure-based functional motif identifies a potential disulfide oxidoreductase active site in the serine/threonine protein phosphatase-1 subfamily.

In previous work, 3-dimensional descriptors of protein function ('fuzzy functional forms') were used to identify disulfide oxidoreductase active sites in high-resolution protein structures. During this analysis, a potential disulfide oxidoreductase active site in the serine/threonine protein phosphatase-1 (PP1) crystal structure was discovered. In PP1, the potential redox active site is located in close proximity to the phosphatase active site. This result is interesting in view of literature suggesting that serine/threonine phosphatases could be subject to redox control mechanisms within the cell; however, the actual source of this control is unknown. Additional analysis presented here shows that the putative oxidoreductase active site is highly conserved in the serine/threonine phosphatase-1 subfamily, but not in the serine/threonine phosphatase-2A or -2B subfamilies. These results demonstrate the significant advantages of using structure-based motifs for protein functional site identification. First, a putative disulfide oxidoreductase active site has been identified in serine-threonine phosphatases using a descriptor built from the glutaredoxin/thioredoxin family, proteins that have no apparent evolutionary relationship whatsoever to the PP1 proteins. Second, the proximity of the putative disulfide oxidoreductase active site to the phosphatase active site provides evidence toward a regulatory control mechanism. No sequence-based method could provide either piece of information.

Amino Acid Sequence↗

PubMedDate not supplied

Enhanced functional annotation of protein sequences via the use of structural descriptors.

In order to circumvent limitations of sequence based methods in the process of making functional predictions for proteins, we have developed a methodology that uses a sequence-to-structure-to-function paradigm. First, an approximate three-dimensional structure is predicted. Then, a three-dimensional descriptor of the functional site, termed a Fuzzy Functional Form, or FFF, is used to screen the structure for the presence of the functional site of interest (Fetrow et al., 1998; Fetrow and Skolnick, 1998). Previously, a disulfide oxidoreductase FFF was developed and applied to predicted structures obtained from a small structural database. Here, using a substantially larger structural database, we expand the analysis of the disulfide oxidoreductase FFF to the B. subtilis genome. To ascertain the performance of the FFF, its results are compared to those obtained using both the sequence alignment method BLAST and three local sequence motif databases: PRINTS, Prosite, and Blocks. The FFF method is then compared in detail to Blocks and it is shown that the FFF is more flexible and sensitive in finding a specific function in a set of unknown proteins. In addition, the estimated false positive rate of function prediction is significantly lower using the FFF structural motif, rather than the standard sequence motif methods. We also present a second FFF and describe a specific example of the results of its whole-genome application to D. melanogaster using a newer threading algorithm. Our results from all of these studies indicate that the addition of three-dimensional structural information adds significant value in the prediction of biochemical function of genomic sequences.

Algorithms↗