摘要
酸碱离解常数(pKa)在理解受体与药物反应和药物如何选择辅料上起着重要的作用。因此,在药物前期的开发中,能有效地预测pKa值可很好地降低开发成本,降低资源消耗。本文通过运用定量构效关系的方法(QSAR)对脂肪醇的数据库展开研究,以进行pKa值的预测。一共选用了253种各类描述符,包含原子键的性质的描述符48个,分子整体描述符205个,其中重点描述符为原子键的性质类描述符。采取多元线性回归的方法对数据进行研究。该预测模型能取得较好的效果,可以应用于药物的前期开发中。
The acid-base dissociation constants（pKa） plays an important role in understanding reaction with receptor amd drug,selection of drug excipient.So in the early development of the drug,effective prediction of pKa value can reduce development costs,consumption of resources.The pKa value of aliphatic alcohols was predicted using the method of quantitative structure activity relationship（QSAR）.It chooses the 253 descriptors, including 48 properties descriptor of the atom bond,205 molecular overall descriptor,and key descriptors were descriptor of properties of the atom bond.The date was analyzed by multiple linear regression method in this paper. The prediction model could achieve good results when used to the early development of drugs.
出处
《精细与专用化学品》
CAS
2011年第9期55-57,共3页
Fine and Specialty Chemicals
关键词
pKa预测
多元线性回归
描述符
pKa prediction
multiple linear regression（MLR）
descriptors
