By a News Reporter-Staff News Editor at Information Technology Newsweekly -- Research findings on Bioinformatics are discussed in a new report. According to news reporting from Taipei, Taiwan, by VerticalNews journalists, research stated, "Since membrane protein structures are challenging to crystallize, computational approaches are essential for elucidating the sequence-to-structure relationships. Structural modeling of membrane proteins requires a multidimensional approach, and one critical geometric parameter is the rotational angle of transmembrane helices."
The news correspondents obtained a quote from the research from the Institute of Information Science, "Rotational angles of transmembrane helices are characterized by their folded structures and could be inferred by the hydrophobic moment; however, the folding mechanism of membrane proteins is not yet fully understood. The rotational angle of a transmembrane helix is related to the exposed surface of a transmembrane helix, since lipid exposure gives the degree of accessibility of each residue in lipid environment. To the best of our knowledge, there have been few advances in investigating whether an environment descriptor of lipid exposure could infer a geometric parameter of rotational angle. Here, we present an analysis of the relationship between rotational angles and lipid exposure and a support-vector-machine method, called TMexpo, for predicting both structural features from sequences. First, we observed from the development set of 89 protein chains that the lipid exposure, i.e., the relative accessible surface area (rASA) of residues in the lipid environment, generated from high-resolution protein structures could infer the rotational angles with a mean absolute angular error (MAAE) of 46.32?. More importantly, the predicted rASA from TMexpo achieved an MAAE of 51.05?, which is better than 71.47? obtained by the best of the compared hydrophobicity scales. Lastly, TMexpo outperformed the compared methods in rASA prediction on the independent test set of 21 protein chains and achieved an overall Matthew's correlation coefficient, accuracy, sensitivity, specificity, and precision of 0.51, 75.26%, 81.30%, 69.15%, and 72.73%, respectively. TMexpo is publicly available at http://bio-cluster.iis.sinica.edu.tw/TMexpo. TMexpo can better predict rASA and rotational angles than the compared methods. When rotational angles can be accurately predicted, free modeling of transmembrane protein structures in turn may benefit from a reduced complexity in ensembles with a significantly less number of packing arrangements."
According to the news reporters, the research concluded: "Furthermore, sequence-based prediction of both rotational angle and lipid exposure can provide essential information when high-resolution structures are unavailable and contribute to experimental design to elucidate transmembrane protein functions."
For more information on this research see: Lipid exposure prediction enhances the inference of rotational angles of transmembrane helices. Bmc Bioinformatics, 2013;14():304. (BioMed Central - www.biomedcentral.com/; Bmc Bioinformatics - www.biomedcentral.com/bmcbioinformatics/)
Our news journalists report that additional information may be obtained by contacting J.S. Lai, Institute of Information Science, Academia Sinica, Taipei, Taiwan. Additional authors for this research include C.W. Cheng, A. Lo, T.Y. Sung and W.L Hsu.
Keywords for this news article include: Asia, Taipei, Taiwan, Bioinformatics.
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