摘要
为在体外迅速检测血管紧张素转化酶抑制剂(ACEI)的抑制活性,选用96孔板,以呋喃丙烯酰三肽(FAPGG)为模拟底物,通过检测血管紧张素转化酶(ACE)酶解FAPGG生成N-[3-(呋喃)丙稀醇酰]-2-苯丙氨酸(FAP)和双甘氨肽(GG)后340 nm处吸光值的下降衡量ACE的活性,采用加入ACEI前后ACE的活性变化衡量ACEI的活性。考察了不同缓冲体系、Cl-浓度、ACE酶活性(ACE酶浓度)、缓冲体系的pH值等对上述检测模型反应体系的影响,建立了高通量降血压肽活性体外检测方法,本方法最多可同时检测96个样品的ACE抑制活性,上机分析时间仅需10 s。不同批次活性平行测定的相对标准偏差均小于0.001%,p=0.667>0.05,各测定结果无显著差异,重现性好,精密度较高。采用本方法测定了商品血管紧张素转化酶抑制剂Captopril的IC50值为16.19 nmol/L,与文献报道的测定结果一致。
A high throughput method for the determination of angiotensin converting enzyme(ACE) inhibitory activity,using 96-well plate technology,has been developed.Hydrolysis of N-[3-(2-furyl)acryloyl[L-phenylalanyl-glycyl-glycine(FAPGG) to N-[3-(2-furyl)acryloyl]-L-phenylalanine(FAP) and glycyl-glycine(GG) by ACE was quantified by measuring the decrease in absorbance at 340 nm to evaluate the activity of ACE.The percentage inhibition of angiotensin converting enzyme inhibitory(ACEI) was determined by comparing the results of control and test samples.The effects of different buffer systems,chloride ion concentration,ACE activity(ACE enzyme concentration),pH value of buffer system on the test of the activity of angiotensin converting enzyme inhibitors in vitro model reaction system of detection were investigated.The new method can detect ACE inhibitory activity of no more than 96 ACEI samples in 10 s or so on microplate-reader for ELISA.For different batches of sample,the RSD was less than 0.001%,p=0.667(0.05),which shows no significant difference between the results measured.The method is simple,accurate,stable,and reliable in antihyperten-sive peptide in vitro inhibitory activity of ACE measured.The method was used to detect a famous angiotensin converting enzyme inhibitors product named Captopril and a IC50 value(Half inhibitory concentration) of 16.19 nmol/L was obtained,which is consistent with the results have been reported in extensive literature.
出处
《分析化学》
SCIE
CAS
CSCD
北大核心
2012年第1期129-134,共6页
Chinese Journal of Analytical Chemistry
关键词
高通量
血管紧张素转化酶抑制剂
活性检测
High-throughput
Angiotensin converting enzyme inhibitors
Activity detection