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  • 标题:Activity and toxicity modelling of some NCI selected compounds against leukemia P388ADR cell line using genetic algorithm-multiple linear regressions
  • 本地全文:下载
  • 作者:David Ebuka Arthur ; Adamu Uzairu ; Paul Mamza
  • 期刊名称:Journal of King Saud University - Science
  • 印刷版ISSN:1018-3647
  • 出版年度:2020
  • 卷号:32
  • 期号:1
  • 页码:324-331
  • DOI:10.1016/j.jksus.2018.05.023
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Graphical abstractDisplay OmittedAbstractCancer-causing nature is one of the toxicological endpoints bringing about the most elevated concern. Likewise, the standard bioassays in rodents used to survey the cancer-mitigating capability of chemicals and medications are expensive and require the sacrifice of animals. Thus, we have endeavored the development of a worldwide QSAR model utilizing an information set of 85 compounds, including drugs for their anti-leukemia potential. Considering expansive number of information focuses with different structural elements utilized for model development (ntraining = 68) and model validation (ntest = 17), the model developed in this study has an encouraging statistical quality (leave-one-out Q2 = 0.833, R2pred = 0.716) for pLC50 and (leave-one-out Q2 = 0.744, R2pred = 0.614) for pGI50. Our developed model suggests that the absence of methanal fragments, low dipole moment and presence of some 2D autocorrelated molecular descriptors reduces the carcinogenicity. Branching, size and shape are found to be crucial factors for drug-mitigating carcinogenicity.
  • 关键词:QSAR;Multiple linear regression;Drugs;Genetic algorithm;Validation;Molecular descriptors
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