曾采用德国Gasteiger教授研究组中PEOP的计算方法，对每个分子结构.doc

ADRIANA.Code 软件 ADRIANA.Code 软件不但可以计算通常的分子全局描述符和分子的形状描述符，还采用德国Gasteiger教授研究组中PEOP的计算方法，对每个分子结构中各个原子的σ电荷， 电荷， σ+ 电荷，σ电负性， 电负性，孤对电子电势等方面进行了具体的计算，在此基础上利用各种数学转化函数即可产生基于原子某一方面性质（比如：σ电荷）的多种二维和三维结构分子描述符。它们包括：二维自相关系数 2D AUTOCORR ,三维自相关系数 3D AUTOCORR , 基于电子衍射编码的三维分子结构表征 3D MoRse code ，基于径向分布函数编码的三维分子结构表征 3D RDF code 等参数。这些描述符可以全面的表征分子的形状、极性、电荷、电负性等基本性质，它们与分子的物理化学性质密切相关。实践证明，这些描述符可以用来成功地预测化合物的许多物化性质及生物活性，比如：化合物水溶解度[1]的预测，药物肠吸收 HIA [2]的预测，药物血脑屏障系数 BBB [3]的预测，药物生物利用度[4]的预测，化合物的毒性预测[5]，以及极光激酶Aurora-A抑制剂生物活性[5]的预测。 参考文献 [1] a Yan, A.X. and Gasteiger, J., Prediction of Aqueous Solubility of Organic Compounds Based on a 3D Structure Representation, Journal of Chemical Information and Computer Science, 2003, 43 2 , 429-434. b Yan, A.X. and Gasteiger, J., Prediction of Aqueous Solubility of Organic Compounds by Topological Descriptors, QSAR Combinatorial Science, 2003, 22 8 , 821-829. c Yan, A.X., Gasteiger, J., Krug M. and Anzali S., Linear and nonlinear functions on modeling of aqueous solubility of organic compounds by two structure representation methods, Journal of Computer-Aided Molecular Design, 2004, 18 2 ,75-87. [2] Yan, A.X., Wang, Z., Cai Z., Prediction of Human Intestinal Absorption by GA Feature Selection and Support Vector Machine Regression, International Journal of Molecular Sciences, 2008, 9 10 , 1961-1976. [3] Wang, Z., Yan, A.X., Yuan, Q.P. Classification of blood-brain barrier permeation by Kohonen’s self-organizing Neural Network KohNN and Support Vector Machine SVM , QSAR ?Combinatorial?Science, 2009, 28 9 , 989-994. [4] Wang, Z., Yan, A.X., Yuan, Q.P., Gasteiger, J. Explorations into Modeling Human Oral Bioavailability, European Journal of Medicinal Chemistry, 2008, 43 11 , 2442-2452. [5] Hu, X.Y., Yan, A.X., In silico prediction of rhabdomyolysis of compounds by self-organizing map and support vector machine. Toxicology in Vitro, 2011, 25 8 , 2017-2024. [6] Yan, A.X., Chong, Y, Wang, L., Hu, X.Y., Wang, K. Prediction of Biological Activity of