Understanding the Impact of Dis3 Cancer-Associated Mutations by in Silico Structure Modeling

Understanding the Impact of Dis3 Cancer-Associated Mutations by in Silico Structure Modeling Publisher

Fazel E¹ ; Fattahpour S² ; Abdali H^{2, 3} ; Nasiri J⁴ ; Sedghi M^{1, 2}

Show Affiliations

1. Medical Genetics Laboratory, Alzahra University Hospital, Isfahan University of Medical Sciences, Isfahan, Iran
2. Craniofacial and Cleft Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
3. Department of Surgery, School of Medicine, Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
4. Department of Pediatric Neurology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

Source: Gene Reports Published:2020

Abstract

DIS3 gene is reported as a driver gene specifically mutated in a few cancer types including multiple myeloma. Unraveling the molecular effects of DIS3 mutations on protein structure may provide insights into the functional effect of different substitutions. Hence, the aim of this study is to analyze the structural and functional consequences of hotspot mutations in DIS3 by using various sequence and structure-based bioinformatics methods. In addition to sequence-based programs, the effect of hotspot mutations on protein stability and the overall pathogenicity was investigated using SDM and Missense3D. Moreover, mutations were modeled on protein structure using UCSF Chimera. Changes in residue interactions after mutations were investigated using RINalyzer. In total 6 positions in DIS3 are reported as hotspot positions. Our analysis showed all hotspots were located in highly conserved positions and their substitution resulted in clashes or disruption in interaction with the Mg2+ or nucleic acid. Our findings confirmed analysis of the residue interaction network provides a better insight into the functional and structural impact of the DIS3 mutations. We expect our analysis will be used for designing future experimental evaluation of the mutations in DIS3 gene and it will also help evaluate other cancer driver genes' mutations. © 2020 Elsevier Inc.

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Style	Citing Format
MLA	Fazel E, et al.. "Understanding the Impact of Dis3 Cancer-Associated Mutations by in Silico Structure Modeling." Gene Reports, vol. 20, no. , 2020, pp. -.
APA	Fazel E, Fattahpour S, Abdali H, Nasiri J, Sedghi M (2020). Understanding the Impact of Dis3 Cancer-Associated Mutations by in Silico Structure Modeling. Gene Reports, 20(), -.
Chicago	Fazel E, Fattahpour S, Abdali H, Nasiri J, Sedghi M. "Understanding the Impact of Dis3 Cancer-Associated Mutations by in Silico Structure Modeling." Gene Reports 20, no. (2020): -.
Harvard	Fazel E et al. (2020) 'Understanding the Impact of Dis3 Cancer-Associated Mutations by in Silico Structure Modeling', Gene Reports, 20(), pp. -.
Vancouver	Fazel E, Fattahpour S, Abdali H, Nasiri J, Sedghi M. Understanding the Impact of Dis3 Cancer-Associated Mutations by in Silico Structure Modeling. Gene Reports. 2020;20():-.
BibTex	@article{ author = {Fazel E and Fattahpour S and Abdali H and Nasiri J and Sedghi M}, title = {Understanding the Impact of Dis3 Cancer-Associated Mutations by in Silico Structure Modeling}, journal = {Gene Reports}, volume = {20}, number = {}, pages = {-}, year = {2020} }
RIS	TY - JOUR AU - Fazel E AU - Fattahpour S AU - Abdali H AU - Nasiri J AU - Sedghi M TI - Understanding the Impact of Dis3 Cancer-Associated Mutations by in Silico Structure Modeling JO - Gene Reports VL - 20 IS - SP - EP - PY - 2020 ER -

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