首页> 外文期刊>International journal of computational biology and drug design >Predicting multiple binding modes using a kernel method based on a vector space model molecular descriptor.
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Predicting multiple binding modes using a kernel method based on a vector space model molecular descriptor.

机译:使用基于向量空间模型分子描述符的核方法预测多种结合模式。

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摘要

We describe the use of our Vector Space Model Molecular Descriptor (VSMMD), based on a Vector Space Model (VSM) that is suitable for kernel studies in Quantitative Structure-Activity Relationship (QSAR) modelling. Our experiments provide convincing comparative empirical evidence that this kernel method can provide sufficient discrimination to predict various biological activities of a molecule with reasonable accuracy. Furthermore, together with a kernel feature space algorithm, experiments also provide convincing empirical evidence that our VSMMD can provide sufficient information to identify different binding modes with high accuracy.
机译:我们基于向量空间模型(VSM)描述了向量空间模型分子描述符(VSMMD)的使用,该模型适合于定量结构-活动关系(QSAR)建模中的内核研究。我们的实验提供了令人信服的比较经验证据,该核方法可以提供足够的判别力,以合理的准确性预测分子的各种生物学活性。此外,结合内核特征空间算法,实验还提供了令人信服的经验证据,表明我们的VSMMD可以提供足够的信息来高精度识别不同的绑定模式。

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