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Quantitative structure–activity relationship to predict the anti-malarial activity in a set of new imidazolopiperazines based on artificial neural networks

机译:基于人工神经网络的定量构效关系预测一组新的咪唑并哌嗪类药物的抗疟活性

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摘要

BackgroundAfter years of efforts on the control of malaria, it remains as a most deadly infectious disease. A major problem for the available anti-malarial drugs is the occurrence of drug resistance in Plasmodium. Developing of new compounds or modification of existing anti-malarial drugs is an effective approach to face this challenge. Quantitative structure activity relationship (QSAR) modelling plays an important role in design and modification of anti-malarial compounds by estimation of the activity of the compounds.
机译:背景经过多年的控制疟疾努力,它仍然是最致命的传染病。现有的抗疟疾药物的主要问题是在疟原虫中出现耐药性。开发新化合物或修饰现有抗疟疾药物是应对这一挑战的有效方法。定量结构活性关系(QSAR)建模通过估算化合物的活性在抗疟疾化合物的设计和修饰中起着重要作用。

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