从分子极性表面积预测β-受体阻断剂的血浆蛋白结合率

Predicting drug-protein binding of Beta-adrenoceptor blocking agents from polar molecular surface areas

目的从分子极性表面积和分子量预测药物的血浆蛋白结合率。方法根据半经验自洽场分子轨道AM1法得到的优化构型用Monte Carlo法计算得到分子量和分子极性表面积。用逐步多元回归分析法建立从药物的分子量、分子极性表面积预测14种β-受体阻断剂的血浆蛋白结合率的数学模型。回归方程采用statistics60软件做逐步多元回归分析得到。结果β-受体阻断剂的血浆蛋白结合率与分子量(MW)、氢键给体表面积(SH)和氢键受体表面积(So,N)具有良好的相关性,回归方程为:fb=1.89-6.50×10-2So.N+6.24×10-4SH2+1.41×10-4MW*So.N(n=13,R=0.8891)。结论β-受体阻断剂的血浆蛋白结合率与分子量和分子极性表面积密切相关。从分子极性表面积预测药物血浆蛋白结合率具有方便快捷的优点,可用于相关的药动学参数的研究。

OBJECTIVE To predict the percentage of drug-protein binding from polar molecular surface areas and molecular weight. METHODS Mont Carlo method was used to obtain the molecular weight and polar molecular surface areas from their minimum energy conformations obtained fromthe optimization of the standard molecular geome - try with the semiempirical self-consistent field molecular orbital calculation Am; method. The stepwise multiple regression analysis was used to establish the model of predicting Beta-adrenoceptor blocking agents bound to human serum albumin from molecular weight and polar molecular surface areas. The stepwise multiple regression analysis with statistics60 was used to obtain the correlation equations. RESULTS Both molecular weight（MW） ,the surface area of hydrogen bond donor （ Su） and the surface area of hydrogen bond acceptor （ So. N） are well correlated with Beta-adrenoceptor blocking agents bound to human serum albumin. The correlation equation is fb = 1.89 -6. 50 ×10^-2 Sα.N＋6.24×10^-4 SH2 ＋1.41 ×10^-4 MW＊So.N（n=13,R=0. 8891）.CONCLUSION Drug-protein binding is closely related with the drugg molecular weight and polar molecular surface areas. The advantage of this research is that polar molecular surface areas can be computed simply and quickly. It also infer this method may be used to study other pharmacokinetics parameters.