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海洋生物的多样性、活性物质结构的新颖性以及海洋环境的独特性使得海洋生物成为天然抗肿瘤活性物质的重要来源之一。以分子电性距离矢量(MEDV-13)为结构描述子,应用基于预测的变量筛选(VMSP)方法,对44种海洋Fascaplysin类CDK4抑制剂的活性作用数据进行模拟分析,获得一个6变量的定量结构—活性关系(QSAR)模型,而且对样本内部使用LOO(Leave-One-Out)验证方法、外部通过测试集对模型进行了验证。模型相关系数r=0.923 9,LOO交互检验相关系数q=0.878 9,显示模型具有良好的估计能力和对外部样本的预测能力。随后,计算了模型最优子集各变量对生物活性的碎片贡献率,结果显示,影响抑制剂活性的主要分子结构单元为=C-(或-C-)、>C-、>N-、-O-以及二联苯中苯环的位置,苯环在对位时对活性有利。研究亮点:发展小分子CDK4抑制剂是当前癌症治疗的新研究领域。首次使用QSAR方法对44种海洋Fascaplysin类化合物的生物活性与其分子结构之间的定量关系进行研究,且对模型进行了内部验证和外部验证,计算了基团对活性的贡献大小。
The diversity of marine life, the novelty of the active substance structure and the uniqueness of the marine environment make marine life an important source of natural anti-tumor active substances. Using MEDV-13 as the structural descriptor, we used the predictive-based variable screening (VMSP) method to simulate the activity data of 44 Fascaplysin-like CDK4 inhibitors and obtained a 6-variable quantitative Structure-activity relationship (QSAR) model, and the LOO (Leave-One-Out) verification method is used internally in the sample. The model is validated externally by the test set. The model correlation coefficient r = 0.923 9, LOO interaction test correlation coefficient q = 0.878 9, which shows that the model has a good estimation ability and the ability to predict external samples. Subsequently, the contribution of each variable of the model to the subset of bioactive fragments was calculated and the results showed that the main molecular structural units that affect the activity of the inhibitor are = C- (or -C-),> C-,> N-, -O- and biphenyl benzene ring position, the benzene ring in the para-position on the activity of favorable. Research Highlights: The development of small molecule CDK4 inhibitors is currently a new field of cancer therapy. The quantitative relationship between the biological activity of 44 Fascaplysin compounds and their molecular structures was studied using the QSAR method for the first time. The model was internally and externally validated, and the contribution of the groups to the activity was calculated.