Diabetes mellitus caused by mutations in human insulin : analysis of impaired receptor binding of insulins Wakayama, Los Angeles and Chicago using pharmacoinformatics

dc.contributor.authorIslam, Md Ataul
dc.contributor.authorBhayye, Sagar
dc.contributor.authorAdeniyi, Adebayo A.
dc.contributor.authorSoliman, Mahmoud E.S.
dc.contributor.authorPillay, Tahir S.
dc.date.accessioned2017-05-12T10:17:16Z
dc.date.issued2017-03
dc.description.abstractSeveral naturally occuring mutations in the human insulin gene are associated with diabetes mellitus. The three known mutant molecules, Wakayama, Los Angeles and Chicago were evaluated using molecular docking and molecular dynamics (MD) to analyse mechanisms of deprived binding affinity for insulin receptor (IR). Insulin Wakayama, is a variant in which valine at position A3 is substituted by leucine, while in insulin Los Angeles and Chicago, phenylalanine at position B24 and B25 are replaced by serine and leucine respectively. These mutations show radical changes in binding affinity for insulin receptor. The ZDOCK server was used for molecular docking while AMBER 14 was used for the molecular dynamics study. The published crystal structure of insulin receptor bound to natural insulin was also used for molecular dynamics. The binding interactions and molecular dynamics trajectories clearly explained the critical factors for deprived binding to the insulin receptor. The surface area around position A3 was increased when valine was substituted by leucine, while at position B24 and B25 aromatic amino acid phenylalanine replaced by non-aromatic serine and leucine might be responsible for fewer binding interactions at the binding site of insulin receptor that leads to instability of the complex. In the MD simulation the normal mode analysis (NMA), rmsd trajectories and prediction of fluctuation indicated instability of complexes with mutant insulin in order of insulin native insulin < insulin Chicago < insulin Los Angeles < insulin Wakayama molecules which corresponds to the biological evidence of the differing affinities of the mutant insulins for the IR.en_ZA
dc.description.departmentChemical Pathologyen_ZA
dc.description.embargo2018-03-31
dc.description.librarianhb2017en_ZA
dc.description.sponsorshipThe University of Pretoria Vice Chancellor’s postdoctoral fellowship and National Research Foundation (NRF), South Africa Innovation postdoctoral fellowship schemes.en_ZA
dc.description.urihttp://www.tandfonline.com/loi/tbsd20en_ZA
dc.identifier.citationMd Ataul Islam, Sagar Bhayye, Adebayo A. Adeniyi, Mahmoud E.S. Soliman & Tahir S. Pillay (2017) Diabetes mellitus caused by mutations in human insulin: analysis of impaired receptor binding of insulins Wakayama, Los Angeles and Chicago using pharmacoinformatics, Journal of Biomolecular Structure and Dynamics, 35:4, 724-737, DOI: 10.1080/07391102.2016.1160258.en_ZA
dc.identifier.issn0739-1102 (print)
dc.identifier.issn1538-0254 (online)
dc.identifier.other10.1080/07391102.2016.1160258
dc.identifier.urihttp://hdl.handle.net/2263/60344
dc.language.isoenen_ZA
dc.publisherTaylor and Francisen_ZA
dc.rights© 2016 Informa UK Limited, trading as Taylor & Francis Group. This is an electronic version of an article published in Journal of Biomolecular Structure and Dynamics, vol. 35, no. 4, pp. 724-737, 2017. doi : 10.1080/07391102.2016.1160258. Journal of Biomolecular Structure and Dynamics is available online at : http://www.tandfonline.com/loi/tbsd20.en_ZA
dc.subjectInsulinen_ZA
dc.subjectProtein-protein dockingen_ZA
dc.subjectZDOCKen_ZA
dc.subjectMolecular dockingen_ZA
dc.subjectMolecular dynamics (MD)en_ZA
dc.subjectDiabetes mellitusen_ZA
dc.subjectInsulin receptor (IR)en_ZA
dc.subjectDiabetes mellitus (DM)en_ZA
dc.subject.otherHealth sciences articles SDG-03
dc.subject.otherSDG-03: Good health and well-being
dc.subject.otherHealth sciences articles SDG-17
dc.subject.otherSDG-17: Partnerships for the goals
dc.titleDiabetes mellitus caused by mutations in human insulin : analysis of impaired receptor binding of insulins Wakayama, Los Angeles and Chicago using pharmacoinformaticsen_ZA
dc.typePostprint Articleen_ZA

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