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    A computational model to predict the structural and functional consequences of missense mutations in O6-methylguanine DNA methyltransferase

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    Date
    2019-02-26
    Author
    Thirumal Kumar, D
    Mendonca, Enid
    Priyadharshini Christy, J
    George Priya Doss, C
    Zayed, Hatem
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    Abstract
    DNA repair mechanism is a process through which the cell repairs its damaged DNA. Although there are several mechanisms involved in the DNA repair mechanisms, the direct reversal method is the simplest and does not require a reference template, in which the guanine bases are often methylated, and the methyl guanine methyl transferase protein (MGMT) reverses them. The mutations occurring in the MGMT protein might result in dysfunction of such DNA repair mechanism. In this study, we attempted to evaluate the impact of six missense mutations (Y114E, Y114A, R128G, R128A, R128K, and C145A) at three active-site positions (Y114, C145, and R128) as this might hinder the DNA binding to the protein. These six mutations were subjected to pathogenicity, stability, and conservation analysis using online servers such as PredictSNP, iStable, and ConSurf, respectively. From the predictions, all the six mutations were almost predicted to be significant. Considering true positives, true negatives, false positives, and false negatives, three mutations (Y114E, R128G, and C145A) showed "loss of DNA repair activity," and were analyzed further using molecular dynamics simulations (MDS) using GROMACS for 50ns. MDS run showed that the C145A mutant demonstrated higher structural deviation, decreased compactness, and the binding patterns. The Y114E mutant showed almost a null effect from the structural analysis. Finally, the R128G mutant showed structural variations in between the C145A and Y114E mutations of MGMT protein. We believe that the observed findings in this computational approach might further pave a way of providing better treatment measures by understanding the DNA repair mechanisms.
    DOI/handle
    http://dx.doi.org/10.1016/bs.apcsb.2018.11.006
    http://hdl.handle.net/10576/11370
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    • Biomedical Sciences [‎796‎ items ]

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