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摘要近年来细菌的耐药性由于抗生素的广泛使用日益严重。目前世界上的许多制药公司和药物化学家正在努力研制、设计筛选出具有化学结构和新作用靶点的新型抗菌药来解决耐药菌感染的问题。经过了30多年的研究而研发了新一类抗菌药物利奈唑胺。本文运用计算机辅助药物设计的方法，通过3D-QSAR模型, 分子对接和药效团模拟的结果，设计出高效的利奈唑胺类似物。本论文在进行分子的叠合之前首先对50个训练集分子及15个测试集分子进行了surflex-dock对接，在分子对接完成之后通过查看配体打分值及氢键作用数，选择打分值最高的配体重新建立数据集进行分子的叠合。最终获得的复合物的编号为3DLL，分别与G2044和A2430形成2个氢键，氢键的距离分别为2.70A°和2.89A°,与U2485，U2563，U2564形成p-π共轭。在PLS结果分析中，CoMFA模型交叉验证等值q² =0.770，其非交叉验证相关等值R²=0.918，标准偏差为0.031，数据组间的平均平方误差与数据组内部的平均平方误差的比值F为126.173。CoMSIA模型的交叉验证等值q²=0.676，此外相关等值R²=0.966，标准偏差为0.021，数据组间的平均平方误差与数据组内部的平均平方误差的比值F为200.892。结果表明该模型均具有较好的统计学稳定性和预测能力，可根据该模型进行新型的分子设计。在新分子设计中，根据模板分子27设计了21个新分子，其中1-8号分子的Total score都高于模板分子，11号分子的CoMFA预测值和CoMSIA预测值都优于模板分子的值。因此，设计的分子活性要优于模板分子。30028
- 上一篇：Polo-Like激酶4(PLK4)抑制剂作为潜在可口服抗癌药的计算机辅助药物设计研究
- 下一篇：羧基化多壁碳纳米管促进类芬顿体系催化降解阿替洛尔
毕业论文关键词： 3D-QSAR；利奈唑胺；分子对接；药效团；计算机辅助药物设计
The molecular design of Rina thiazole amine analogues as antibacterial drug
Abstract In recent years, the bacterial resistance has become increasingly serious due to the widespread use of antibiotics.In the world, many pharmaceutical companies and pharmaceutical chemists are trying to develop, design and screen out with chemical structure and new target of new antibacterial agents to solve problems of drug resistant bacteria infection. After 30 years of research and development of a new class of antibiotics linezolid.In this paper, the use of computer aided drug design method, through the 3D-QSAR model. The results of molecular docking and pharmacophore modeling, design, linezolid analogues. In this paper, the molecular stack together before first to 50 training set molecules and 15 testing set molecules were sufiex docking, by viewing ligand scoring value and hydrogen bonding interactions in number after the completion of the molecular docking, choose the score of the highest ligand to re-establish a data set of molecular composite. As 3DLL ultimately get the complex number, respectively, and G2044 A2430 formed two hydrogen, hydrogen bond distances were 2.70A° and 2.89A°, and U2485, U2563, U2564 formed p-πconjugated. In the analysis of the results for PLS, the CoMFA model cross validation equivalent q²=0.770, the non cross validated correlation equivalent R²=0.918. The standard deviation was 0.031 and the ratio of the mean square error of the data between groups mean square error and data set of internal F is 126.173. The CoMSIA model cross validation equivalent q²=0.676. In addition related equivalent R²=0.966, standard deviation is 0.021, the ratio of the mean square error of the data between groups mean square error and data set of internal F is 200.892. Results show that the model has good statistical stability and predictive ability, according to the model of molecular design of novel. In the design of the new molecule, according to the template molecule 27 designed 21 new molecules, which 1-8 molecular total score are higher than the template molecule, 11 molecular CoMFA predicted value and CoMSIA prediction values are better than those of the template values. Therefore, the molecular activity of the design is better than the template molecules.
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