CN112945917B - 基于芘取代化合物的荧光阵列传感器及其构建方法与应用 - Google Patents

基于芘取代化合物的荧光阵列传感器及其构建方法与应用 Download PDF

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CN112945917B
CN112945917B CN202110117399.1A CN202110117399A CN112945917B CN 112945917 B CN112945917 B CN 112945917B CN 202110117399 A CN202110117399 A CN 202110117399A CN 112945917 B CN112945917 B CN 112945917B
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韩进松
李飞
许莲
王浩
黄慧
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Abstract

本发明公开了一种基于芘取代化合物的荧光阵列传感器,还公开了所述传感器的构建方法,以及应用。本申请通过合成荧光化合物库进行筛选并构建荧光阵列传感器的方法,可以同时区分不同类别的农药标准品、市售农药、单一农药的不同浓度,以及实际果蔬农产品样品中的农药残留。该方法检测时间不到一分钟、成本低、选择性高、重复性高、且无需专业技术人员。

Description

基于芘取代化合物的荧光阵列传感器及其构建方法与应用
技术领域
本发明涉及荧光快速检测技术,特别是涉及基于芘取代化合物的荧光阵列传感器及其构建方法与应用。
背景技术
农药已广泛用于提高果蔬产量和防治病虫害,同时,农药的滥用、误用等一些不合理的施药方式导致部分附着在蔬果表面,农药及其代谢产物不易降解残留在土壤中被部分蔬果吸收,加剧了农药残留问题的严重性。少量的农药残留并不会引起人体急性中毒,如果长时间食用农药残留超标的农产品,可能存在慢性中毒的风险和威胁,还有可能会诱发恶性肿瘤。农药残留一直是食品(食用农产品)中抽检的重点项目,也常见有蔬菜、水果等检出农药残留不合格的信息公布。
传统的农药检测技术,包括酶抑制法,免疫分析法和色谱法。酶抑制法只能对一类农药的总量进行定性判断,无法区分每种农药各自的浓度水平,而且容易受到农产品基质的干扰而产生假阳性或假阴性,出现误判。免疫分析法具有特异性强、灵敏度高等优点,但是该方法开发成本高、抗体和抗原制备难度大、检测范围窄,不适合现场检测。色谱法检测时间长、仪器昂贵且操作复杂。因此开发一种简便、经济、快速、选择性高的鉴别和检测的方法,已成为食品安全领域的重要目标之一。
阵列传感器是基于对哺乳动物嗅觉系统的认识发展起来的一种有力的分子识别手段,由多个传感单元组成。其原理主要是基于受体分子与分析物的非特异性作用,比如:范德华力、氢键、芳香性、离子键等。该方法具有非特异性响应和交互响应的特点,即传感阵列中每一个传感单元对不同物质都具有不同程度的响应,而各个传感单元对于同一物质也有不同程度的响应。阵列传感器通过各传感单元对样品响应变化产生的特征图谱,实现同时对多种样本的快速识别。这一方法的优点是避免了单一传感器对特异接受体的依赖性,大大拓展了可检测物质的范围,甚至能够实现对结构非常相似的一些物质的区分。理想的阵列传感器既可用于单一物质的准确识别,也可用于混合样品的鉴定。目前,阵列传感器已可用于蛋白质、细菌、细胞、精液等大分子的检测,也可用于重金属,氨基酸,酸碱,爆炸物等小分子的识别,还能用于食品中的饮料,酒,蜂蜜等混合物的识别。荧光阵列传感器因其具有操作简单、灵敏度高、选择性好、实时快速分析、分辨率高等优点,而被广泛应用于生物检测分析、光学成像等领域。目前,已公开的许多阵列传感器用于农药的检测,包括比色阵列传感器和荧光阵列传感器。Zhu等(Zhu et al.Anal Chem 2020,92,7444-7452.)开发了一种基于杂原子掺杂的纳米酶阵列传感器检测农药。Zhu等选用了氮掺杂石墨烯、氮硫共掺杂石墨烯和氧化石墨烯三种具有过氧化物类活性的石墨烯材料,能够催化TMB(3,3',5,5'-四甲基联苯胺)和H2O2反应变蓝。在芳香族农药的作用下,石墨烯纳米酶的活性位点被吸附掩盖,石墨烯的催化活性被抑制,蓝色变浅。Zhang等(Zhang et al.ACS Sens 2020,5,162-170)开发了一种基于卡巴唑的荧光多孔聚合物用于识别和检测水中的各种农药。通过一步聚合反应合成了三种具有不同取代基的卡巴唑的荧光多孔有机聚合物,合成的聚合物对不同农药表现出不同的荧光信号。
但是现有文献报道的阵列传感器往往针对一类农药进行检测、选择性差、灵敏度低。因此,本领域仍然需要开发选择性高、灵敏度高的检测方法。
发明内容
发明目的:针对目前农药“一对一”检测方法的缺陷,本申请针对不同结构类型的农药具有不同区分能力的荧光化合物库,根据识别能力的差异筛选最优的识别元素,获得有效的传感元素,制备得到基于芘取代化合物的荧光阵列传感器,实现“一对多”模式同时检测多种结构类型的农药,涉及有机氯类、有机磷类、氨基甲酸酯类和拟除虫菊酯类,甚至实现快速准确识别农药的类型,以及实际果蔬样本中的农药残留。
技术方案:本申请所述的一种基于芘取代化合物的荧光阵列传感器,其中所述芘取代化合物结构如式I所示:
Figure BDA0002920868050000021
其中:R1基团可独立地选自:任选取代的烷基、任选取代的环烷基、任选取代的烯基、任选取代的炔基、任选取代的芳基、任选取代的杂环基、任选取代的杂链烃基、任选取代的烷氧基、烷基磺酰基、卤素、氰基、羟基、硝基、烷基、卤代烷基;R2基团可独立地选自:任选取代的烷基、任选取代的环烷基、任选取代的烯基、任选取代的炔基、任选取代的芳基、任选取代的杂环基、任选取代的杂链烃基、任选取代的烷氧基、烷基磺酰基、氢、卤素、氰基、羟基、硝基、烷基、卤代烷基;R3基团可独立地选自:任选取代的烷基、任选取代的环烷基、任选取代的烯基、任选取代的炔基、任选取代的芳基、任选取代的杂环基、任选取代的杂链烃基、任选取代的烷氧基、烷基磺酰基、卤素、氰基、羟基、硝基、烷基、卤代烷基;R4基团可独立地选自:单取代或多取代的氢、卤素、三氟甲基、三氟甲氧基、硝基、甲氧基、氨基、羟基、羧基、酸酐、酯基、酰胺基、取代或未取代的C1-C10的直链或支链烷基及环烷基、取代或未取代的氨基或脲基、取代或未取代的直链或支链烷氧基;n为0~10;所述“任选取代的”基团中,取代基选自卤素、羟基、硝基、烷基、羟基烷基、环烷基、烷氧基、磺酰基、杂环基、芳香基;所述“烷基”、“卤代烷基”、“烷基磺酰基”、“烷氧基”中所含的烷基为C1-C20直链或支链烷基;所述“环烷基”为C3-C6环烷基,可选地,所述环烷基包括环丙基、环丁基、环戊基、环己基;所述“芳基”为5-10元芳基;可选地,所述芳基包括苯基、萘基;所述“杂芳基”为含有1-3个选自N、O和S中的杂原子的5-10元杂芳基;所述“杂环基”中的杂环结构为环上含有1-3个选自N、O、S的杂原子的饱和或不饱和的、3-6元单环或多环非芳香环结构;所述“杂链烃基”中的杂链烃结构为C1-C20饱和或不饱和的、链上含1-3个选自N、O、S的杂原子的直链或支链的杂链结构;所述“卤素”包括氟、氯、溴和碘。
优选地:R1基团可独立地选自:C1-C14直链或支链的烷基、取代或未取代的C3-C6环烷基、取代或未取代的芳基或杂芳基、取代或未取代的C3-C6杂环基、直链或支链的C1-C10杂链烃基、支链或支链的C1-C10卤代烷基;R2基团可独立地选自:C1-C12直链或支链的烷基、取代或未取代的C3-C6环烷基、取代或未取代的芳基或杂芳基、取代或未取代的C5或C6杂环基;R3基团可独立地选自:C1-C8直链或支链的烷基、取代或未取代的C3-C6的环烷基、取代或未取代的C3-C6的杂环基、取代或未取代的芳基;R4基团可独立地选自:单取代或多取代的氢、卤素、三氟甲基、三氟甲氧基、硝基、甲氧基、氨基、羟基、羧基、酸酐、酯基、酰胺基、取代或未取代的C1-C10的直链或支链烷基及环烷基、取代或未取代的氨基或脲基、取代或未取代的直链或支链烷氧基;n为0~10;所述“杂芳基”为含有1个选自N、O、S中的杂原子的C5或C6杂芳基;所述“卤素”为氟、氯、溴;所述“芳基”为C5或C6的、单环或双环芳香环结构;所述“杂链烃基”中的杂链烃结构为C1-C6饱和的、链上含1个选自N、O、S的杂原子的杂链结构。
更优选地,R1基团可为:
Figure BDA0002920868050000022
更优选地,R2基团可为:
Figure BDA0002920868050000031
更优选地,R3基团可为:
Figure BDA0002920868050000032
更具体地,本发明涉及化合物优选自如下化合物:
N-(1-环己基-2-氧代-2-((2,4,4-三甲基戊-2-基)氨基)乙基)-N-异戊基-4-(吡喃-1-基)丁酰胺(C596)
N-(2-吗啉代乙基)-N-(1-((2-吗啉代乙基)氨基)-1-氧丁烷-2-基)-4-(1-吡啶基)丁酰胺(C115)
6-羟基-N-(2-吗啉代乙基)-2-(4-(吡啶-1-基)-N-(吡啶-2-基甲基)丁酰胺基)己酰胺(C915)
N-环己基-2-(N-(戊-2-基)-4-(吡啶-1-基)丁酰胺基)三酰胺(C494)
N-(1-(苯并[b]噻吩-2-基)-2-(苄基氨基)-2-氧乙基)-N-(3-(二丁基氨基)丙基)-4-(吡啶-1-基)丁酰胺(C317)
N-(叔丁基)-2-(N-(2-吗啉代乙基)-4-(吡啶-1-基)丁酰胺基)十一碳酰胺(C83)
N-(3-(二丁基氨基)丙基)-N-(1-氧代-4-苯基-1-(((2,4,4-三甲基戊-2-基)氨基)丁-2-基)-4-(吡啶-1-基)丁酰胺(C241)
N-(1-(呋喃-2-基)-2-((2-吗啉代乙基)氨基)-2-氧代乙基)-N-(戊基-3-基)-4-(吡啶-1-基)丁酰胺(C365)
2-(N-丁基-4-(吡啶-1-基)丁酰胺基)-6-羟基-N-(2-吗啉代乙基)己酰胺(C1490)
N-(3-(二丁基氨基)丙基)-N-(1-(4-甲氧基苯基)-2-氧代-2-((2,4,4-三甲基戊-2-基)氨基)乙基)-4-(吡啶-1-基)丁酰胺(C276)
N-(2-(苄基氨基)-1-(4-氯苯基)-2-氧乙基)-N-(戊烷-2-基)-4-(吡啶-1-基)丁酰胺(C522)
N-(1-(4-溴苯基)-2-(环己基氨基)-2-氧代乙基)-N-(2-(2-羟基乙氧基)乙基)-4-(吡啶-1-基)丁酰胺(C2289)
N-丁基-N-(1-((2-吗啉代乙基)氨基)-1-氧丁烷-2-基)-4-(吡啶-1-基)丁酰胺(C1495)
N-(1-(4-溴苯基)-2-(叔丁基氨基)-2-氧代乙基)-N-(戊烷-3-基)-4-(吡啶-1-基)丁酰胺(C448)
N-(2-(苄基氨基)-1-(4-氯苯基)-2-氧乙基)-N-异戊基-4-(吡啶-1-基)丁酰胺(C637)
N-丁基-N-(2-(环己基氨基)-1-(2,3-二氢苯并呋喃-5-基)-2-氧代乙基)-4-(吡啶-1-基)丁酰胺(C1449)
N-(2-(苄基氨基)-1-(3,5-二甲氧基苯基)-2-氧乙基)-N-(3,4-二甲氧基苄基)-4-(吡啶-1-基)丁酰胺(C3082)
N-(1-(4-溴苯基)-2-(环己基氨基)-2-氧代乙基)-N-(2-(甲硫基)乙基)-4-(吡啶-1-基)丁酰胺(C1944)
N-十二烷基-N-(2-氧-1-(吡啶-4-基)-2-(((2,4,4-三甲基戊-2-基)氨基)乙基)-4-(吡啶-1-基)丁酰胺(C3111)
N-(2-(叔丁基氨基)-1-(4-氯苯基)-2-氧代乙基)-N-(2-吗啉代乙基)-4-(吡啶-1-基)丁酰胺(C63)
N-(2-(苄氨基)-2-氧-1-(吡啶-4-基)乙基)-4-(吡啶-1-基)-N-(2,2,2-三氟乙基)丁酰胺(C2077)
N-(2-(苄氨基)-2-氧-1-(吡啶-4-基)乙基)-N-(呋喃-2-基甲基)-4-(吡啶-1-基)丁酰胺(C1962)
N-(2-(苄氨基)-2-氧-1-(吡啶-4-基)乙基)-N-异戊基-4-(吡啶-1-基)丁酰胺(C582)
N-(2-(环己基氨基)-1-(4-氟苯基)-2-氧乙基)-4-(吡啶-1-基)-N-(2,2,2-三氟乙基)丁酰胺(C2129)
N-(1-(苯并[b]噻吩-2-基)-2-氧-2-(((2,4,4-三甲基戊-2-基)氨基)乙基)-N-(2-(甲硫基)乙基)-4-(吡啶-1-基)丁酰胺(C1926)
N-(2-(叔丁基氨基)-1-(萘-2-基)-2-氧代乙基)-N-环戊基-4-(吡啶-1-基)丁酰胺(C1688)
N-(1-(苄氨基)-1-氧丁烷-2-基)-N-丁基-4-(吡啶-1-基)丁酰胺(C1942)
N-(叔丁基)-2-(4-(吡啶-1-基)-N-(2,2,2-三氟乙基)丁酰胺基)己酰胺(C2098)
N-(1-(4-溴苯基)-2-((2-吗啉代乙基)氨基)-2-氧代乙基)-N-(戊烷-2-基)-4-(吡啶-1-基)丁酰胺(C565)
N-(2-(苄氨基)-1-(4-溴苯基)-2-氧乙基)-N-丁基-4-(吡喃基-1-基)丁酰胺(C1482)
N-(2-(苄基氨基)-1-(4-氯苯基)-2-氧乙基)-N-丁基-4-(吡啶-1-基)丁酰胺(C1442)
N-(1-(4-溴苯基)-2-(叔丁基氨基)-2-氧代乙基)-N-环丙基-4-(吡啶-1-基)丁酰胺(C1138)
N-(1-(苄氨基)-1-氧丁烷-2-基)-N-环丙基-4-(吡啶-1-基)丁酰胺(C1147)
N-苄基-2-(4-(吡啶-1-基)-N-(2,2,2-三氟乙基)丁酰胺基)己酰胺(C2097)
N-(1-(苄氨基)-1-氧丁烷-2-基)-N-丙基-4-(吡啶-1-基)丁酰胺(C1262)
N-(2-(苄基氨基)-1-(4-溴苯基)-2-氧乙基)-N-(2-甲氧基乙基)-4-(吡啶-1-基)丁酰胺(C1597)
N-(2-(叔丁基氨基)-1-(4-羟苯基)乙基)-N-(((S)-2,3-二羟丙基)-4-(吡啶-1-基)丁酰胺(C1728)
N-丁基-N-(2-(环己基氨基)-1-(呋喃-2-基)-2-氧代乙基)-4-(吡啶-1-基)丁酰胺(C1399)
N-(1-(苯并[b]噻吩-2-基)-2-(叔丁基氨基)-2-氧代乙基)-N-丁基-4-(吡喃基-1-基)丁酰胺(C1468)
N-环戊基-N-(2-氧代-1-(4-(吡咯烷-1-基)苯基)-2-((2,4,4-三甲基戊基-2-基)氨基)乙基)-4-(吡啶-1-基)丁酰胺(C1706)
N-(2-(苄基氨基)-1-(4-甲氧基苯基)-2-氧代乙基)-4-(吡啶-1-基)-N-(2,2,2-三氟乙基)丁酰胺(C2117)
N-环戊基-N-(2-((2-吗啉代乙基)氨基)-1-(4-硝基苯基)-2-氧代乙基)-4-(吡啶-1-基)丁酰胺(C1685)
N-((S)-2,3-二羟丙基)-N-(1-(呋喃-2-基)-2-((2-吗啉代乙基)氨基)-2-氧代乙基)-4-(py-1-基)丁酰胺(C1745)
N-(2-(叔丁基氨基)-1-(4-羟基苯基)-2-氧代乙基)-4-(吡啶-1-基)-N-(2,2,2-三氟乙基)丁酰胺(C2073)
N-苄基-6-羟基-2-(N-(2-羟乙基)-4-(吡啶-1-基)丁酰胺基)己酰胺(C1372)
N-(1-(4-溴苯基)-2-((2-吗啉代乙基)氨基)-2-氧代乙基)-4-(吡啶-1-基)-N-(吡啶-2-基甲基)丁酰胺(C910)
N-(1-(苄氨基)-1-氧丁烷-2-基)-N-环戊基-4-(吡啶-1-基)丁酰胺(C1722)
N-(1-(苯并[b]噻吩-2-基)-2-氧-2-(((2,4,4-三甲基戊-2-基)氨基)乙基)-N-(2-甲氧基乙基)-4-(吡啶-1-基)丁酰胺(C1581)
N-(2-(苄氨基)-1-(4-甲氧基苯基)-2-氧乙基)-N-环戊基-4-(吡喃基-1-基)丁酰胺(C1657)
N-(2-(叔丁基氨基)-1-(4-羟苯基)-2-氧代乙基)-N-(戊-2-基)-4-(吡喃基-1-基)丁酰胺(C463)
N-(2-(苄氨基)-1-(4-溴苯基)-2-氧乙基)-N-异戊基-4-(吡喃基-1-基)丁酰胺(C677)
N-(2-(苄基氨基)-1-(3,5-二甲氧基苯基)-2-氧乙基)-N-(戊烷-3-基)-4-(吡啶-1-基)丁酰胺(C437)
2-(N-(2-吗啉代乙基)-4-(吡啶-1-基)丁酰胺基)-N-(2,4,4-三甲基戊基-2-基)十一碳酰胺(C81)
N-(1-(苄氨基)-1-氧丁烷-2-基)-N-丁基-4-(吡啶-1-基)丁酰胺(C1942)
N-丁基-N-(1-(呋喃-2-基)-2-氧-2-(((2,4,4-三甲基戊-2-基)氨基)乙基)-4-((-1-基)丁酰胺(C1396)
N-丁基-N-(2-(叔丁基氨基)-1-(2,3-二氢苯并呋喃-5-基)-2-氧代乙基)-4-(吡啶-1-基)丁酰胺(C1448)
N-(2-(苄氨基)-2-氧-1-(吡啶-4-基)乙基)-N-(3-(二丁基氨基)丙基)-4-(吡啶-1-基)丁酰胺(C237)
N-((S)-2,3-二羟丙基)-N-(2-氧-1-(吡啶-4-基)-2-((2,4,4-三甲基戊-2-基)氨基)乙基)-4-(吡啶-1-基)丁酰胺(C1731)
N-(1-(4-氯苯基)-2-((2-吗啉代乙基)氨基)-2-氧代乙基)-N-环戊基-4-(吡啶-1-基)丁酰胺(C1675)
N-(2-(苄基氨基)-1-(3,5-二甲氧基苯基)-2-氧乙基)-N-(2-甲氧基乙基)-4-(吡啶-1-基)丁酰胺(C1587)
N-(2-(叔丁基氨基)-1-(呋喃-2-基)-2-氧代乙基)-4-(吡啶-1-基)-N-(2,2,2-三氟乙基)丁酰胺(C2088)
N-(1-(4-甲氧基苯基)-2-氧代-2-((2,4,4-三甲基戊-2-基)氨基)乙基)-N-(戊-2-基)-4-(吡啶-1-基)丁酰胺(C506)
N-苄基-2-(4-(吡啶-1-基)-N-(2,2,2-三氟乙基)丁酰胺(C2102)
N-(2-(环己基氨基)-1-(4-硝基苯基)-2-氧代乙基)-N-环戊基-4-(吡啶-1-基)丁酰胺(C1684)
N-(2-(环己基氨基)-1-(4-甲氧基苯基)-2-氧代乙基)-4-(吡啶-1-基)-N-(2,2,2-三氟乙基)丁酰胺(C2119)
N-(2-(苄基氨基)-1-(4-硝基苯基)-2-氧乙基)-N-环戊基-4-(吡啶-1-基)丁酰胺(C1682)
N-(2-(苄氨基)-1-(4-羟苯基)-2-氧乙基)-N-((R-2,3-二羟丙基)-4-(吡啶-1-基)丁酰胺(C1727)
N-苄基-2-(N-环戊基-4-(吡啶-1-基)丁酰胺基)十一碳酰胺(C1692)
N-(3,4-二甲氧基苄基)-N-(1-((2-吗啉代乙基)氨基)-1-氧丁烷-2-基)-4-(吡喃基-1-基)丁酰胺(C3105)
N-(叔丁基)-2-(N-(3-(二丁基氨基)丙基)-4-(吡啶-1-基)丁酰胺基)-6-羟基己酰胺(C338)
N-(1-(环己基氨基)-1-氧丁烷-2-基)-N-(2-羟乙基)-4-(吡啶-1-基)丁酰胺(C1379)
N-(1-(苯并[b]噻吩-2-基)-2-(叔丁基氨基)-2-氧代乙基)-N-(戊基-3-基)-4-(吡啶-1-基)丁酰胺(C433)
N-(1-(4-溴苯基)-2-氧-2-(((2,4,4-三甲基戊-2-基)氨基)乙基)-N-(3,4-二甲氧基苄基)-4-(吡啶-1-基)丁酰胺(C3091)
N-(1-(4-氯苯基)-2-氧-2-(((2,4,4-三甲基戊-2-基)氨基)乙基)-N-十二烷基-4-(吡喃-1-基)丁酰胺(C3166)
N-(2-(环己基氨基)-1-(4-羟基苯基)-2-氧乙基)-N-十二烷基-4-(吡喃-1-基)丁酰胺(C3109)
N-(2-(苄氨基)-2-氧-1-(吡啶-4-基)乙基)-N-十二烷基-4-(吡啶-1-基)丁酰胺(C3112)
N-(2-(环己基氨基)-2-氧代-1-(吡啶-4-基)乙基)-N-十二烷基-4-(吡啶-1-基)丁酰胺(C3114)
N-(1-(4-溴苯基)-2-((2-吗啉代乙基)氨基)-2-氧代乙基)-N-丁基-4-(吡啶-1-基)丁酰胺(C1485)
N-(2-(苄基氨基)-1-(4-硝基苯基)-2-氧乙基)-N-丁基-4-(吡啶-1-基)丁酰胺(C1452)
N-(2-吗啉代乙基)-2-(4-(吡啶-1-基)-N-(2,2,2-三氟乙基)丁酰胺基)己酰胺(C2100)
N-(1-((2-吗啉代乙基)氨基)-1-氧丁烷-2-基)-4-(吡啶-1-基)-N-(吡啶-2-基甲基)丁酰胺(C920)
N-苄基-2-(4-(吡啶-1-基)-N-(2,2,2-三氟乙基)丁酰胺基)壬酰胺(C2112)
N-(2-氧-1-(吡啶-4-基)-2-(((2,4,4-三甲基戊-2-基)氨基)乙基)-N-(戊-2-基)-4-(吡啶-1-基)丁酰胺(C466)
N-(1-(苯并[b]噻吩-2-基)-2-(苄基氨基)-2-氧乙基)-N-(2-(甲硫基)乙基)-4-(吡啶-1-基)丁酰胺(C1927)
N-(2-(苄基氨基)-1-(3,5-二甲氧基苯基)-2-氧乙基)-N-丁基-4-(吡啶-1-基)丁酰胺(C1472)
N-(2-(叔丁基氨基)-1-(4-甲氧基苯基)-2-氧代乙基)-4-(吡啶-1-基)-N-(2,2,2-三氟乙基)丁酰胺(C2118)
N-(1-(4-溴苯基)-2-(叔丁基氨基)-2-氧代乙基)-4-(吡啶-1-基)-N-(2-(吡咯烷-1-基)乙基)丁酰胺(C793)
N-(2-(苄氨基)-1-(呋喃-2-基)-2-氧代乙基)-N-环戊基-4-(吡啶-1-基)丁酰胺(C1627)
N-(2-(苄氨基)-2-氧-1-(吡啶-4-基)乙基)-N-丙基-4-(吡啶-1-基)丁酰胺(1157)
N-(2-(苄基氨基)-1-(4-溴苯基)-2-氧乙基)-N-(3,4-二甲氧基苄基)-4-(吡啶-1-基)丁酰胺(C3092)
N-(2-(苄基氨基)-1-(4-氟苯基)-2-氧乙基)-4-(吡啶-1-基)-N-(2,2,2-三氟乙基)丁酰胺(C2127)
N-(1-(苯并[b]噻吩-2-基)-2-(叔丁基氨基)-2-氧代乙基)-N-(3-(二丁基氨基)丙基)-4-(吡啶-1-基)丁酰胺(C318)
N-苄基-2-(N-(戊-2-基)-4-(吡啶-1-基)丁酰胺(C492)
N-(2-(苄基氨基)-1-(呋喃-2-基)-2-氧代乙基)-N-(戊烷-3-基)-4-(吡啶-1-基)丁酰胺(C362)
N-(1-(苯并[b]噻吩-2-基)-2-(叔丁基氨基)-2-氧代乙基)-N-环戊基-4-(吡啶-1-基)丁酰胺(C1698)
N-(2-(环己基氨基)-1-(萘-2-基)-2-氧代乙基)-N-环戊基-4-(吡啶-1-基)丁酰胺(C1689)
N-(2-(叔丁基氨基)-1-(4-硝基苯基)-2-氧代乙基)-N-环戊基-4-(吡啶-1-基)丁酰胺(C1683)
N-(1-(苯并[b]噻吩-2-基)-2-((2-吗啉代乙基)氨基)-2-氧代乙基)-N-(3-(二丁基氨基)丙基)-4-(吡啶-1-基)丁酰胺(C320)
N-(2-(苄氨基)-1-(萘-2-基)-2-氧代乙基)-N-环戊基-4-(吡啶-1-基)丁酰胺(C1687)
N-环己基-2-(N-(2-吗啉代乙基)-4-(吡啶-1-基)丁酰胺基)十一碳酰胺(C84)。
表1优选的100个荧光化合物
Figure BDA0002920868050000051
Figure BDA0002920868050000061
Figure BDA0002920868050000071
Figure BDA0002920868050000081
Figure BDA0002920868050000091
如上所述的荧光阵列传感器的快速筛选及构建方法是:合成的化合物按荧光强度从高到低进行排序,依次对十二种农药进行检测(表1),通过层次聚类分析(HCA),对所有识别元素进行筛选,选取其中识别能力最强,效果最佳的三个荧光化合物(C115、C596、C915),用于构建荧光微阵列传感器。
本申请还公开了所述荧光阵列传感器在农药检测中的应用。
如上所述区分农药标准品的方法是:将上述筛选所得的荧光识别元素用缓冲液(pH=4.0-11.0)稀释至终浓度为0.1-100μM,制备得到阵列传感单元。
优化的阵列传感单元的构建为:将上述筛选所得的荧光识别元素用PBS(pH=7.0)缓冲液稀释至终浓度为12μM(加入样本后最终浓度为9μM),制备得到阵列传感单元,依次加入十种农药标准品溶液(检测范围为0.001-10mM,农药最佳识别响应终浓度为0.5mM),包括毒死蜱(Chl)、水胺硫磷(Iso)、丙溴磷(Prof)、草甘膦(Gly)、腐霉利(Proc)、DDT(Dic)、百克敏(Pyr)、氟氯氰菊酯(Cyf)、溴氰菊酯(Del)、氟虫腈(Fip),震摇5秒,每种农药与单一阵列传感单元重复测试六次,记录荧光变化信号。
如上所述区分市售农药样品的方法是:选取七种市售农药,包括丙溴磷(Prof-s)、草甘膦(Gly-s)、腐霉利(Proc-s)、百克敏(Pyr-s)、多菌灵(Car-s)、高效氟氯氰菊酯(Cyh-s)、溴氰菊酯(Del-s),基于上述农药标准品的检测浓度为0.5mM,市售农药按有效成分的含量,配制成相应有效成分浓度为2mM的贮备液,按上述类似测试方法进行检测,记录荧光变化信号。
如上所述区分单一农药标准品浓度的定量检测的方法是:选取两种农药(Chl、Pyr)分别配制系列浓度(0.04mM、0.2mM、0.4mM、1mM、2mM、3mM、4mM、5mM),移取不同浓度的农药标准品储备液(农药标准品的最终检测浓度为0.01mM、0.05mM、0.1mM、0.25mM、0.5mM、0.75mM、1mM、1.25mM),按上述类似测试方法进行检测,记录荧光变化信号。
如上所述区分果蔬样品中农药残留的方法是:选取10个大小一致的草莓,分别用市售农药浸泡1h,取出,自然晾干,加入甲醇进行提取,每3分钟晃动一次,10分钟后取上层清液,按上述类似测试方法进行检测,记录荧光变化信号。
利用层次聚类分析对化合物库与十二种农药的荧光数据进行分析,筛选出能够区分所有农药的贡献最大的几个荧光化合物,用于构建全新荧光阵列传感器。利用线性判别分析等多种算法对阵列传感单元与农药作用的荧光数据进行处理,对数据矩阵进行分类,得到农药的二维或三维阵列可视化指纹图谱,实现可视化识别。将得到的二维或三维阵列区分指纹图谱用作模型对未知的样本进行检测,并计算未知样本预测的准确率,实现对农药的区分和检测。
本申请基于Ugi反应合成一系列不同物理化学性质取代的芘类识别元素,基于与农药的信号变化筛选具有较优反应的识别元素,构建荧光阵列传感器用于检测农药。具体的,利用Ugi反应合成3335个化合物的荧光化合物库,经过多步筛选,获得识别能力最强的荧光化合物,用于构建荧光阵列传感器,利用荧光阵列传感器的不同传感单元与不同农药作用方式的差异,包括毒死蜱(Chl)、水胺硫磷(Iso)、丙溴磷(Prof)、草甘膦(Gly)、腐霉利(Proc)、DDT(Dic)、百克敏(Pyr)、氟氯氰菊酯(Cyf)、溴氰菊酯(Del)、氟虫腈(Fip),测定每个传感单元与农药作用的相对荧光强度,利用线性判别分析、主成分分析及多种机器学习算法对荧光数据进行处理,获得较优的识别模型,实现对不同类型农药的快速区分和检测。同时通过构建的模型,预测未知样本,实现未知农药样本的快速识别。
有益效果:本申请通过合成荧光化合物库进行筛选并构建荧光阵列传感器,筛选所得的荧光阵列传感器制备方法简单、成本低,选择性高、灵敏度高、检测时间短,对多种农药具有同时检测和识别的能力,可以同时区分不同类别的农药标准品、市售农药、单一农药的不同浓度,以及实际果蔬农产品样品中的农药残留。该方法检测时间不到一分钟、重复性高、且无需专业技术人员。
附图说明
图1是基于Ugi反应合成的化合物按荧光强度值从高到低进行排序,前100个化合物与12种农药标准品荧光响应的HCA图;
图2是荧光阵列传感器对农药标准品的荧光响应信号;
图3是荧光阵列传感器对农药标准品快速识别的可视化图(LDA);
图4是荧光阵列传感器对市售农药的荧光响应信号;
图5是荧光阵列传感器对市售农药快速识别的可视化图(LDA);
图6是荧光阵列传感器对不同浓度的毒死蜱的荧光响应信号;
图7是荧光阵列传感器对不同浓度的毒死蜱的可视化图(LDA);
图8是荧光阵列传感器对不同浓度的百克敏的荧光响应信号;
图9是荧光阵列传感器对不同浓度的百克敏的可视化图(LDA);
图10是荧光阵列传感器对实际样品中农药残留的荧光响应信号;
图11是荧光阵列传感器对实际样品中农药残留的可视化图(LDA)。
具体实施方式
为了使本发明的目的、技术方案及优点更加清楚明白,以下结合附图及具体实施方式,对本发明进行进一步详细说明
下述实施例中所使用的实验方法如无特殊说明,均为常规方法;下述实施例中所用的试剂、材料等,如无特殊说明,均可从商业途径得到。
实施例1基于芘取代的化合物库的合成方法
下述实施例中所采用的Ugi反应组合化学按照如下所示的合成路线,通过下述步骤的方法制备得到:
Figure BDA0002920868050000111
R1基团为:
Figure BDA0002920868050000112
R2基团为:
Figure BDA0002920868050000113
R3基团为:
Figure BDA0002920868050000114
实施例22N-(1-环己基-2-氧代-2-((2,4,4-三甲基戊-2-基)氨基)乙基)-N-异戊基-4-(吡喃基-1-基)丁酰胺(C596)的制备:
Figure BDA0002920868050000121
在反应瓶中加入1-芘丁酸(288.34mg,,1mmol),3-甲基-1-丁胺(87.16mg,1mmol),环己基甲醛(112.17mg,1mmol),2-异氰基-2,4,4-三甲基戊烷(139.24mg,1mmol),溶解于1mL甲醇中,室温搅拌反应4h,薄层制备分离得到C596。MS(ESI)m/z:609.44(M+H)+1H NMR(300MHz,Chloroform-d)δ8.30(d,J=9.3Hz,1H),8.21-8.04(m,4H),8.00(d,J=12.1Hz,3H),7.87(d,J=7.8Hz,1H),4.12(q,J=7.1Hz,2H),3.67(d,J=5.3Hz,1H),3.42(t,J=7.7Hz,2H),2.61-2.46(m,2H),2.17(s,19H),1.67(dp,J=29.9,7.6,7.2Hz,1H),1.26(t,J=7.2Hz,4H),0.87(d,J=6.2Hz,2H).
实施例3-101列表1中编号2-100的化合物制备
列表1中编号2-100的化合物合成,可根据实施例1中所示的相应原料,参照实施例2的合成方法,应用相似条件制备得到。
实施例102荧光阵列传感器体系的筛选以及构建
基于Ugi反应合成的化合物按荧光强度从高到低进行排序,选择前100个荧光化合物,分别移取10μL化合物储备液用10mL 0.1mM的PBS(pH=7.0)缓冲液稀释至10μM,得到阵列传感单元,摇匀,备用。
荧光阵列传感器体系的筛选方法是:选取十二种农药,包括有机磷类、有机氯类、氨基甲酸酯类、拟除虫菊酯类(表1),将十二种农药以DMSO作溶剂分别配制成浓度为1mM(农药的终浓度为0.1mM)。在384孔板中,分别移取8μL 1mM的农药和72μL阵列传感单元,每个阵列传感单元与单一农药重复测试3次。激发波长为340nm,在发射波长为386nm处测得的荧光响应信号,扣除背景发射,以相对荧光强度变化为检测信号(I-I0/I0)(
表2)。所得的荧光信号进行层次聚类分析(HCA)(图1),选取距离差距最大的六个化合物(C317、C115、C915、C365、C596、C83),将这六个化合物与十二种农药测得的荧光响应数据进行线性判别分析(LDA),Classification Matrix(Cases in row categoriesclassified into columns)表明对农药区分的准确率达到100%(表3)。
表1十二种农药标准品。
Figure BDA0002920868050000122
Figure BDA0002920868050000131
表2六个阵列传感识别元素对十二种农药标准品的荧光响应数据矩阵(重复测试3次)。
Figure BDA0002920868050000132
Figure BDA0002920868050000141
表3 Classification Matrix六个阵列传感识别元素对十二种农药标准品的识别准确率(重复测试3次)。
Figure BDA0002920868050000142
基于上述的筛选结果,进一步利用筛选所得的六个化合物构建LDA模型:分别移取72μL阵列传感识别元素,对十二种农药进行测试,每个农药标准品与单一阵列传感识别元素重复测试6次,记录十二种农药与六个传感单元的荧光响应信号(表4),通过LDA算法构建可视化模型,Classification Matrix(Cases in row categories classified intocolumns)表明六个阵列传感单元对十二种农药的区分准确率仅86%(表5)。
表4六个阵列传感识别元素对十二种农药标准品的荧光响应数据矩阵(重复测试6次)。
Figure BDA0002920868050000143
Figure BDA0002920868050000151
表5 Classification Matrix六个阵列传感识别元素对十二种农药标准品的识别准确率(重复测试6次)。
Figure BDA0002920868050000152
实施例103荧光阵列传感器体系的优化
基于上述筛选结果具体实施过程中的差异,进一步对阵列传感器以及农药检测浓度进行优化。调节阵列传感单元的pH(pH=11、pH=3)、增大检测浓度(0.5mM),通过对实验数据运用多种算法进行分析,最终将阵列传感单元的个数从6个优化为3个,农药检测浓度从0.1mM增大到0.5mM,同时识别10个不同种类的农药。
三个阵列传感单元对十种农药进行分析,重复测试6次,记录荧光变化信号(表6),图2显示三个阵列传感单元对不同的农药标准品具有不同的荧光响应。在统计分析软件中使用LDA对荧光数据进行处理并分析,三个阵列传感单元能将十种农药标准品进行区分(图3),Classification Matrix(Cases in row categories classified into columns)表明对十种农药标准品的区分准确率为100%(表7)。
表6三个阵列传感识别元素对十种农药标准品的荧光响应数据矩阵。
Figure BDA0002920868050000161
Figure BDA0002920868050000171
表7 Classification Matrix三个阵列传感识别元素对十种农药标准品的识别准确率。
Figure BDA0002920868050000172
阵列传感器对未知农药样本的区分能力:将十种农药随机顺序进行盲测,共盲测40个未知样品。按照上述步骤进行测试,记录相对荧光强度变化(表8)。再利用线性判别分析,验证模型测试未知样品的能力,区分农药的种类。测试40个未知样本,正确检测出39个样本,准确率为97.5%。
表8阵列传感器对未知农药标准品样本的荧光响应数据矩阵。
Figure BDA0002920868050000173
Figure BDA0002920868050000181
实施例104优化后的荧光阵列传感器用于市售农药的区分
选取了七种市售农药,基于上述农药标准品的检测浓度为0.5mM,市售农药按照有效成分的含量,配制成相应有效成分浓度为2mM的贮备液。
区分不同种类市售农药的方法是:取150μL阵列传感单元和50μL市售农药储备液(市售农药的最终检测浓度为0.5mM),包括丙溴磷(Prof-s)、草甘膦(Gly-s)、腐霉利(Proc-s)、百克敏(Pyr-s)、多菌灵(Car-s)、高效氟氯氰菊酯(Cyh-s)、溴氰菊酯(Del-s)。激发波长为340nm,在发射波长为386nm处测得阵列传感单元与市售农药的荧光强度,以相对荧光强度变化为检测信号(I-I0/I0)。每个阵列传感单元与单一市售农药测试6次,记录三个传感单元对不同市售农药的荧光响应(表9),图4显示三个阵列传感单元对不同的市售农药具有不同的荧光响应。在统计分析软件中使用LDA对荧光数据进行处理并分析,三个阵列传感单元能将十种市售农药进行区分(图5),Classification Matrix(Cases in row categoriesclassified into columns)表明对市售农药区分的准确率达到100%(
表10)。
表9阵列传感器对市售农药样本的荧光响应数据矩阵。
Figure BDA0002920868050000182
Figure BDA0002920868050000191
表10 Classification Matrix市售农药样本的识别准确率。
Figure BDA0002920868050000192
阵列传感器对未知市售农药的区分能力:将七种市售农药随机顺序进行盲测,共盲测28个未知样品。按照上述步骤进行测试,记录相对荧光强度变化。再利用线性判别分析,验证模型测试未知样品的能力,区分市售农药的种类。测试28个未知样本,正确检测出28个样本,准确率为100%(表11)。
表11阵列传感器对未知市售农药样本的荧光响应数据矩阵。
Figure BDA0002920868050000193
实施例105优化后的荧光阵列传感器用于农药浓度的分析
阵列传感器对不同浓度农药的区分能力:选取两种农药(毒死蜱、百克敏)分别配制系列浓度(0.04mM、0.2mM、0.4mM、1mM、2mM、3mM、4mM、5mM),移取不同浓度的农药储备液50μL(农药的最终检测浓度为0.01mM、0.05mM、0.1mM、0.25mM、0.5mM、0.75mM、1mM、1.25mM),加入150μL的阵列传感单元,单一阵列传感单元与每个浓度重复测试6次。激发波长为340nm,在发射波长为386nm处测得阵列传感单元与农药的荧光强度,以相对荧光强度变化为检测信号(I-I0/I0)。获得8个浓度毒死蜱的荧光变化信号(表12),图6显示三个阵列传感单元对不同浓度毒死蜱具有不同的荧光响应。在统计分析软件中使用LDA对荧光数据进行处理并分析,三个阵列传感单元能将不同浓度毒死蜱进行区分(图7),Classification Matrix(Cases in row categories classified into columns)表明对8个浓度毒死蜱的区分准确率为100%(表13)。同样,获得8个浓度百克敏的荧光变化信号(表14),图8显示三个阵列传感单元对不同浓度百克敏具有不同的荧光响应,利用LDA对荧光数据进行处理,三个阵列传感单元能将不同浓度百克敏进行区分(图9),Classification Matrix(Cases in rowcategories classified into columns)表明对8个浓度百克敏的区分准确率为100%(表15)。
表12阵列传感器对不同浓度毒死蜱的荧光响应数据矩阵。
Figure BDA0002920868050000201
表13 Classification Matrix不同浓度毒死蜱的识别准确率。
Figure BDA0002920868050000202
Figure BDA0002920868050000211
表14阵列传感器对不同浓度百克敏的荧光响应数据矩阵。
Figure BDA0002920868050000212
表15 Classification Matrix不同浓度百克敏的识别准确率。
Figure BDA0002920868050000213
Figure BDA0002920868050000221
阵列传感器对未知浓度农药的区分能力:将8个浓度的毒死蜱随机顺序进行盲测,共盲测32个未知样品。按照上述步骤进行测试,记录相对荧光强度变化(表16)。再利用线性判别分析,验证模型测试未知样品的能力,区分农药的浓度。测试32个未知样本,正确检测出30个样本,准确率为93.75%。另外,按同样的方法对8个浓度的百克敏进行盲测(表17),准确率为93.75%。
表16阵列传感器对未知浓度毒死蜱的荧光响应数据矩阵。
Figure BDA0002920868050000222
表17阵列传感器对未知浓度百克敏的荧光响应数据矩阵。
Figure BDA0002920868050000223
Figure BDA0002920868050000231
实施例106优化后的荧光阵列传感器用于果蔬样品中农药残留的识别
如上所述区分实际样品中农药残留的方法是:选取10个大小一致的草莓,分别加入市售高效氟氯氰菊酯浸泡1h,确保样本表面充分接触到农药,取出,自然晾干,加入15mL甲醇进行提取,每3分钟晃动一次,10分钟后取上层清液。其余2种市售农药(丙溴磷、溴氰菊酯)按同样方法进行浸泡和提取,最终共得到30个处理后的样本。每种农药选择6个样本,共18个样本,每个样本与单一阵列传感器测试一次,以蒸馏水作为对照组。激发波长为340nm,在发射波长为386nm处测得阵列传感单元与草莓农药残留样本的荧光强度,以相对荧光强度变化为检测信号(I-I0/I0)(表18),图10显示三个阵列传感单元对不同草莓农药残留具有不同的荧光响应。在统计分析软件中使用LDA对荧光数据进行处理并分析,三个阵列传感单元能将不同草莓农药残留进行区分(图11),Classification Matrix(Cases in rowcategories classified into columns)表明对草莓农药残留区分的准确率达到100%(表19)。
表18阵列传感器对草莓农药残留的荧光响应数据矩阵。
Figure BDA0002920868050000232
表19 Classification Matrix草莓农药残留的识别准确率。
Figure BDA0002920868050000233
Figure BDA0002920868050000241
荧光阵列传感器对未知农药残留样本的区分能力:将3种草莓农药残留样本随机顺序进行盲测,蒸馏水做对照,共盲测16个未知样品。按照上述步骤进行测试,记录相对荧光强度变化(表20)。再利用线性判别分析,验证模型测试未知样品的能力,区分草莓农药残留样本。测试16个未知样本,正确检测出15个样本,准确率为93.75%。
表20阵列传感器未知草莓农药残留样本的荧光响应数据。
Figure BDA0002920868050000242
综上,本申请利用Ugi反应快速合成三千多个识别元素的荧光化合物库,按荧光强度值从高到低进行排序,并根据HCA算法筛选农药识别数据,最终得到农药区分效果较好的荧光化合物用于构建荧光阵列传感器。该阵列传感器用于同时检测多种农药以及识别果蔬农产品样品中的农药残留。包括有机磷类(毒死蜱、水胺硫磷、丙溴磷、草甘膦)、有机氯类(腐霉利、DDT)、氨基甲酸酯类(百克敏)、拟除虫菊酯类农药(氟氯氰菊酯、溴氰菊酯)以及其他类(氟虫腈)。该阵列传感器对十种农药的区分准确率为100%,避免了常用的农药检测技术只能对某一类农药的总量进行检测的局限性,对未知样本的区分准确率为97.5%;对七种市售农药区分准确率为100%,对未知市售农药样本的区分准确率为100%;对不同浓度的农药区分准确率为100%,预测准确率为93.75%;进一步用于检测实际样品中的农药残留,实际样品中的农药残留区分准确率为100%,预测准确率为91.25%。本发明提供了一种通过高通量筛选化合物库并构建荧光阵列传感器的方法。该阵列传感器能够准确区分多种农药标准品、市售农药和单一农药的不同浓度,以及成功识别实际样品中的农药残留。

Claims (6)

1.一种基于芘取代化合物的荧光阵列传感器,其特征在于,所述芘取代化合物结构如式I所示:
Figure FDA0004174067470000011
其中,
R1基团为:
Figure FDA0004174067470000012
R2基团为:
Figure FDA0004174067470000013
R3基团为:
Figure FDA0004174067470000014
R4基团选自:氢;
n为0~10。
2.根据权利要求1所述的基于芘取代化合物的荧光阵列传感器,其特征在于,芘取代化合物选自以下化合物:
Figure FDA0004174067470000015
Figure FDA0004174067470000021
Figure FDA0004174067470000031
Figure FDA0004174067470000041
Figure FDA0004174067470000051
3.权利要求1所述荧光阵列传感器在农药检测中的应用。
4.根据权利要求3所述应用,其特征在于,将芘取代化合物用缓冲液稀释至终浓度为0.1-100μM,制备得到阵列传感单元,依次加入农药标准品溶液,震摇记录荧光变化信号。
5.根据权利要求3所述应用,其特征在于,所述农药包括有机氯类、有机磷类、氨基甲酸酯类和拟除虫菊酯类农药。
6.根据权利要求3所述应用,其特征在于,所述农药包括毒死蜱Chl、水胺硫磷Iso、丙溴磷Prof、草甘膦Gly、腐霉利Proc、滴滴涕、百克敏Pyr、氟氯氰菊酯Cyf、溴氰菊酯Del、氟虫腈Fip。
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