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目的验证利用基于人工免疫智能系统的计算机辅助设计抗感染中药新复方的可行性。方法选取《伤寒论》中所载之经方作为中药复方训练样本,金黄色葡萄球菌腹腔感染实验动物模型ig给予各中药复方,取含药血清观察其抑菌效果,按抑菌力大小给以相应编码;将这些复方中各味中药的药性特征进行编码,输入一个神经网络,用人工免疫系统实现各神经元之间的连接权值优化,使之具备实现中药复方药性特征和抑菌力之间非线性映射的能力,提取出抗金黄色葡萄球菌感染的中药复方的组方规律;然后由计算机随机生成复方,由系统根据预测的抑菌能力取排名靠前者输出得到计算机设计的抗感染中药复方,进行动物实验验证。结果经过验证,计算机所设计的复方可以有效提高小鼠含药血清抗金黄色葡萄球菌的能力。结论初步证明,计算机可以用于辅助设计抗感染中药新复方。
Objective To verify the feasibility of using computer-aided design based on artificial immune intelligence system to design a new compound for anti-infective Chinese medicine. METHODS: The Chinese medicine prescription contained in “Treatise on Febrile Diseases” was selected as a training sample of traditional Chinese medicine compound. The experimental animal model of peritoneal infection of Staphylococcus aureus was given ig to each Chinese herbal compound. The antibacterial effect was observed by taking the drug-containing serum, and the antibacterial effect was given by the antibacterial force. Corresponding coding; The medicinal properties of each Chinese herbal compound in these compounds are coded, entered into a neural network, and artificial neural systems are used to optimize the connection weights among various neurons so that they can achieve the medicinal properties and antibacterial properties of traditional Chinese medicines. The ability of non-linear mapping to extract the prescription of the traditional Chinese medicine compound against Staphylococcus aureus infection; then randomly generated compound by the computer, the system according to the predicted antibacterial ability to take the top of the output to get the computer designed anti-infection Chinese medicine compound, animal experiments to verify. Results After verification, the computer-designed compound can effectively improve the ability of mice containing drug-resistant serum against Staphylococcus aureus. Conclusions Preliminary proof that the computer can be used to assist in the design of new compounds for anti-infective Chinese medicine.