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基于结构分类的蛋白质折叠模式识别方法
PROTEIN FOLD RECOGNITION BASED ON STRUCTURAL CLASSIFICATION
【摘要】 对用于折叠模式识别的蛋白质结构数据库进行结构分类,构建了四个分类库:Al-α库,Al-β库,α/β库,α+β库和一个总库,然后分别统计出不同灵敏度的匹配评估函数(平均势)。对不同的平均势,不同结构类型的蛋白进行的检验发现:来源于α/β库的平均势预测能力最强,来源于Al-α库的平均势预测能力最弱;对α/β蛋白的预测成功率最高,对Al-α蛋白的预测成功率最低。这与α/β蛋白结构最规则,Al-α蛋白未加入辅基不能反映出结构的全部特征是相一致的
【Abstract】 The prediction ability of mean force potentials from different protein structural classes was studied. We constructed four classified training databases: All-α database, All-β database, α/β database, α+β database and a general training database. The potential derived from α/β database has the strongest prediction ability, while the potential derived from All-α database has the weakest. α/β proteins can be predicted most successfully than any other classified proteins, while All-α proteins without comprising co-factors is predicted the worst.
【Key words】 Protein fold recognition Structure classification Mean force;
- 【文献出处】 生物物理学报 ,ACTA BIOPHYSICA SINICA , 编辑部邮箱 ,1999年01期
- 【分类号】Q141,Q141
- 【被引频次】16
- 【下载频次】202