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MIA-QSAR modeling of the anti-HIV-1 protease activities and cytotoxicities of ritonavir analogs.

机译:利托那韦类似物的抗HIV-1蛋白酶活性和细胞毒性的MIA-QSAR建模。

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Drug-likeness and toxicity prediction of compounds are so important as to estimate their bioactivities. In rational design of drugs, looking for safe rather than only highly active synthetic targets has increasingly became mandatory. In this context, structure-based methods to model toxicities of drug-like compounds arise as fundamental tasks to achieve safer drugs. Accordingly, the MIA-QSAR method, which has been widely applied to model bioactivities of several classes of compounds, can also be used to predict toxicities of drug-like compounds. In fact, the MIA-based approach has shown to be accurate to model bioactivities, boiling points, NMR chemical shifts and electrophoretic profiles, but it has been used to model cytotoxicities for the first time in this work, in order to contribute for studies to develop safer drugs. The QSAR modeling of bioactivities (pEC50) and cytotoxicities (CCIC50) of a series of HIV-1 protease inhibitors, some ritonavir derivatives, is reported in this work using the MIA-QSAR approach. The statistical quality of both models indicates that pEC50 and CCIC50 of ritonavir analogs can be reliably predicted using this method; therefore, improved drugs can be designed.
机译:化合物的药物相似性和毒性预测是如此重要,以至于估计其生物活性。在药物的合理设计中,寻找安全而不是仅高度活跃的合成靶标已变得越来越强制。在这种情况下,用于模拟药物样化合物毒性的基于结构的方法成为实现更安全药物的基本任务。因此,已经广泛用于模拟几类化合物的生物活性的MIA-QSAR方法也可以用于预测药物样化合物的毒性。实际上,基于MIA的方法已被证明可以精确地模拟生物活性,沸点,NMR化学位移和电泳图谱,但是在这项工作中,它首次被用于模拟细胞毒性,从而有助于研究开发更安全的药物。在这项工作中,使用MIA-QSAR方法报道了一系列HIV-1蛋白酶抑制剂(一些利托那韦衍生物)的生物活性(pEC50)和细胞毒性(CCIC50)的QSAR建模。两种模型的统计质量均表明,使用该方法可以可靠地预测利托那韦类似物的pEC50和CCIC50。因此,可以设计出改进的药物。

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