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AuthorAgrahari, Ashish Kumar
AuthorDoss, George Priya C
AuthorSiva, R
AuthorMagesh, R
AuthorZayed, Hatem
Available date2019-03-28T05:49:49Z
Publication Date2019-03-01
Publication NameJournal of Theoretical Biologyen_US
Identifierhttp://dx.doi.org/10.1016/j.jtbi.2019.03.003
CitationAgrahari, Ashish Kumar et al. Molecular insights of the G2019S substitution in LRRK2 kinase domain associated with Parkinson's disease: A molecular dynamics simulation approach. Journal of Theoretical Biology, Volume 469 , pp. 163 - 171 .
ISSN0022-5193
URIhttp://hdl.handle.net/10576/11455
AbstractThe G2019S substitution in the Leucine-rich repeat kinase 2 (LRRK2) is significantly associated with Parkinson's disease (PD). This substitution was identified in both familial and sporadic forms of PD with a higher frequency. Few computational studies have reported the impact of G2019S substitution on inhibitors of the kinase domain of LRRK2. However, no computational study deeply investigated the possible impact of the G2019S substitution on the kinase domain in its Apo conformation. Therefore, in this study, we used 200 ns molecular dynamic simulation using the GROMACS 5.1.4 package software to investigate the impact of the G2019S substitution on the structure of the kinase domain of LRRK2. Our results indicate that the G2019S substitution affects the dynamics and stability of LRRK2 by decreasing the flexibility and increasing the compactness of the kinase domain and showing its tendency to be in an active conformation for long time interval because of the high energy barrier between active and inactive conformation. This study predicts the molecular pathogenicity mechanism of the G2019S on patients with PD and provides a potential platform for developing therapeutics for patients with PD that harbor this amino acid substitution.
Languageen
PublisherElsevier
SubjectDYG
SubjectG2019S
SubjectKinase domain
SubjectLRRK2
SubjectMolecular dynamics simulation
SubjectPD
TitleMolecular insights of the G2019S substitution in LRRK2 kinase domain associated with Parkinson's disease: A molecular dynamics simulation approach.
TypeArticle
Pagination163-171
Volume Number469
dc.identifier.essn 1095-8541


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