PredictSuperFam-PSS-3D1D: A server for predicting superfamily for the annotation of twilight zone protein sequences.

Autor: Muthuvel Prasath K; Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli 620 024, Tamil Nadu, India., Ganesan K; Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600 036, Tamil Nadu, India., Parthasarathy S; Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli 620 024, Tamil Nadu, India. Electronic address: partha@bdu.ac.in.
Jazyk: angličtina
Zdroj: Journal of structural biology [J Struct Biol] 2020 May 01; Vol. 210 (2), pp. 107479. Date of Electronic Publication: 2020 Feb 17.
DOI: 10.1016/j.jsb.2020.107479
Abstrakt: Annotation of twilight zone protein sequences has been hitherto attempted by predicting the fold of the given sequence. We report here the PredictSuperFam-PSS-3D1D method, which predicts the superfamily for a given twilight zone (TZ) protein sequence. Earlier, we have reported that adding predicted secondary structure information into the threading methods could improve fold prediction especially for the TZ protein sequences. In this study, we have analysed the application of the same method to predict superfamilies. Here, in this method, the twilight zone protein sequence is threaded with the 3D1D profiles of the known protein superfamilies library. In addition, weightage for the predicted secondary structure (PSS) is also employed. The performance of the method is benchmarked with twilight zone sequences. In the benchmarks, 62 and 65 percentages of superfamily predictions are obtained with GOR IV and NPS@ predicted secondary structures, respectively. Receiver Operating Characteristic (ROC) curves indicate that the method is sensitive in predicting the superfamilies. A case study has been conducted with the hypothetical protein sequences of Schistosoma haematobium (Blood Fluke) using this method and the results are analyzed. Our method predicts the superfamily for TZ sequences for which, methods based on sequence similarity alone are inadequate. A web server has been developed for our method and it is available online at http://bioinfo.bdu.ac.in/psfpss.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2020 Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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