共 11 条
PARM: A genetic evolved algorithm to predict bioactivity
被引:45
作者:
Chen, HM
[1
]
Zhou, JJ
[1
]
Xie, GR
[1
]
机构:
[1] Chinese Acad Sci, Lab Comp Chem, Inst Chem Met, Beijing 100080, Peoples R China
来源:
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES
|
1998年
/
38卷
/
02期
关键词:
D O I:
10.1021/ci970004w
中图分类号:
O6 [化学];
学科分类号:
0703 ;
摘要:
Based on Waiters' GERM (Genetic Evolved Receptor Model) algorithm, an improved algorithm FARM (Pseudo Atomic Receptor Model) was put forward. PARM uses a combination of a genetic algorithm and a cross-validation technique to produce an atomic-level pseudoreceptor model, based on a set of known structure-activity relationships. During the genetic process, an artificial interfering method, which is based on a complementary principle of ligand-receptor interaction, was used to accelerate the search speed. The evolved models show a high correlation between intermolecular energy and bioactivity and can predict the bioactivity of an unknown molecule by interpolating in the regression equation of the structure-activity relationship. This algorithm was applied to two systems and produced reasonable results.
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页码:243 / 250
页数:8
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