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Decoding the vital segments in human ATP-dependent RNA helicase


Vandana Kamjula, Ananya Kanneganti, Rohan Metla, Kusuma Nidamanuri, Sudarshan Idupulapati, Ashish Runthala*



Department of Biotechnology, KoneruLakshmaiah Education Foundation, Vaddeswaram, AP, India



Email: ashish.runthala@gmail.com. *Corresponding Author


Article Type

Research Article



Received January 22, 2020; Accepted February 20, 2020; Published February 29, 2020



An analysis of the ATP-dependent RNA helicase using known functionally close analogs help disclose the structural and functional information of the enzyme. The enzyme plays several interlinked biological functions and there is an urgent need to interpret its key activesite
residues to infer function and establish role. The human protein q96c10.1 is annotated using tools such as interpro, go and cdd. The physicochemical properties are estimated using the tool protparam. We describe the enzyme protein model developed using modeller to
identify active site residues. We used consurf to estimate the structural conservation and is evolutionary relationship is inferred using known close sequence homologs. The active site is predicted using castp and its topological flexibility is estimated through cabs-flex. The
protein is annotated as a hydrolase using available data and ddx58 is found as its top-ranked interacting protein partner. We show that about 124 residues are found to be highly conserved among 259 homologs, clustered in 7 clades with the active-site showing low sequence conservation. It is further shown that only 9 loci among the 42 active-site residues are conserved with limited structural fluctuation from the wild type structure. Thus, we document various useful information linked to function, sequence similarity and phylogeny of the enzyme for annotation as potential helicase as designated by uniprot. Data shows limited degree of conserved sequence segments with topological flexibility unlike in other subfamily members of the protein.



RNA helicase, innate immunity, motif, MODELLER, flexibility



Kamjula et al. Bioinformation 16(2): 160-170 (2020)


Edited by

P Kangueane






Biomedical Informatics



This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.