高等学校化学学报 ›› 2000, Vol. 21 ›› Issue (1): 41.

• 论文 • 上一篇    下一篇

CPSA与疏水性参数的遗传算法及神经网络法研究

郭明, 刘文杰, 徐尊   

  1. 塔里木农垦大学基础课部, 阿拉尔 843300
  • 收稿日期:1999-04-29 出版日期:2000-01-24 发布日期:2000-01-24
  • 通讯作者: 郭 明(1967年出生),男,硕士,副教授,主要从事化学计量学研究.
  • 基金资助:

    国家自然科学基金(批准号:29767001);新疆生产建设兵团科学技术委员会科研基金

Studies on the QSPR Between Charged Partial Surface Area and lgP of Organic Compounds Using Genetic Algorithm and Neural Network

GUO Ming, LIU Wen-Jie, XU Zun   

  1. Department of Basic Course, Tarim University of Agricultural Reclamation, Alar 843300, China
  • Received:1999-04-29 Online:2000-01-24 Published:2000-01-24

摘要: 用分子力学计算出“净”原子表面积,并利用量子化学方法计算出化合物的电荷加权部分表面积(CP-SA).在用遗传算法和神经网络法对改进的CPSA与有机醇类化合物的疏水性参数作相关分析时发现,改进的CPSA可有效地用于构效关系研究,且算法简洁易行,两种多元统计方法均得到了满意的结果.

关键词: 电荷加权部分表面积, lgP, 醇类, 遗传算法, 神经网络法

Abstract: The original calculation methods of Charged Partial Surface Area(CPSA) are very complex because of considering many factors of environment, the calculation about the contribution in surface area of atom to molecular in these methods are solvent accessible area. In this paper, we improved the algorithm of CPSA and calculated the “nickel” surface area of atom using molecular mechanics and the CPSA of compounds by quantum chemistry. The satisfactory result of correlation analyze between lgP and improved CPSA of alcohol demonstrates that our algorithm is simple and effective, both genetic algorithm and neural network are well used in this research.

Key words: Charged partial surface area, lgP, Alcohol, Genetic algorithm, Neural network

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