Cartesian genetic programming and the post docking filtering problem

被引：4

作者：

Garmendia-Doval, AB

Miller, JF

Morley, SD

机构：

来源：

GENETIC PROGRAMMING THEORY AND PRACTICE II | 2005年 / 8卷

关键词：

Cartesian genetic programming; molecular docking prediction; virtual screening; machine learning; genetic programming; evolutionary algorithms; neutral evolution;

D O I：

10.1007/0-387-23254-0_14

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Structure-based virtual screening is a technology increasingly used in drug discovery. Although successful at estimating binding modes for input ligands, these technologies are less successful at ranking true hits correctly by binding free energy. This chapter presents the automated removal of false positives from virtual hit sets, by evolving a post docking filter using Cartesian Genetic Programming(CGP). We also investigate characteristics of CGP for this problem and confirm the absence of bloat and the usefulness of neutral drift.

引用

页码：225 / 244

页数：20

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