CN116705141A - 一种基于cnn-lstm神经网络从核桃酶解产物中筛选阿尔兹海默症预防肽的方法 - Google Patents
一种基于cnn-lstm神经网络从核桃酶解产物中筛选阿尔兹海默症预防肽的方法 Download PDFInfo
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Abstract
本发明属于多肽技术领域,提供了一种基于CNN‑LSTM神经网络从核桃酶解产物中筛选阿尔兹海默症预防肽的方法,本发明利用CNN‑LSTM总结了具有预防阿尔兹海默症功效多肽的特征,用于筛选核桃蛋白酶解产物中具有预防阿尔兹海默症功效的多肽,最终获得四条阿尔兹海默症预防肽。通过小鼠实验验证了预防肽可以改善D型半乳糖诱导的学习和记忆功能障碍,减少海马区神经元的损伤、降低氧化应激、减缓神经炎症和防止胆碱能丢失,进一步预防阿尔兹海默症。同时,也证实了所建立的CNN‑LSTM神经网络在植物源阿尔兹海默症预防肽筛选方面的潜力。
Description
技术领域
本发明涉及多肽领域,尤其涉及一种基于CNN-LSTM神经网络从核桃酶解产物中筛选阿尔兹海默症预防肽的方法。
背景技术
阿尔兹海默症(AD)是一种起因隐匿的中枢神经退化性疾病,严重影响着人类的健康。研究发现,多种因素影响着AD的进展,包括:氧化应激、神经炎症、胆碱能缺失、Aβ蛋白沉积和Tau蛋白神经纤维缠结的形成等。由于早期的AD治疗药物大多是针对单一发病机理进行研发,且AD患者的大脑突触和神经元的损失是不可逆的,导致目前治疗药物的收效甚微。同时,由于AD的早期症状不明显,大多数患者在晚期才被确认,这使得治疗更加困难。因此,尽快做好预防工作是非常关键的,通过早期的干预,如接种疫苗和饮食调理等,将降低患病的风险。大量数据表明,饮食与健康之间的联系十分紧密。生酮饮食是指摄取高比例脂肪、低比例碳水化合物、蛋白质和其他营养的饮食方式,已在上世纪用于治疗儿童难治性癫痫病。近期研究表明,生酮饮食可能是痴呆患者的福音。地中海饮食是以种类丰富的植物食品为基础,包括大量水果、蔬菜、土豆、五谷杂粮、豆类、坚果、种子等,被证实可以保护大脑免受血管损伤,降低发生中风和记忆力减退的风险。由此可见,饮食调理是预防神经性疾病的理想方案。
研究发现,在AD的早期阶段,常伴有氧化应激、神经炎症和胆碱能缺失的发生。通过日常食用具有抗氧化、消炎和防止胆碱能缺失的食物,有利于预防AD的发生。从植物中获得的多肽具有丰富的氨基酸种类和多样的生物活性,拥有多种针对AD病理发展的功效,可以为人体提供丰富的营养和疾病预防能力。到目前为止,已经从植物源多肽中发现了大量抗氧化、消炎和防止胆碱能缺失的多肽,通过食用植物源多肽是预防AD的理想策略。
植物源多肽通常由植物蛋白分解而来,这伴随着大量不同序列的肽、普通肽和活性肽的产生,如何鉴定和筛选具有预防AD功能的多肽是一个重要的过程。通常情况下,需要鉴定多条植物源AD预防肽序列,并逐个验证后获得具有预防AD功效的多肽,这将消耗大量的精力和金钱,阻碍了植物源AD预防肽的产业化。此外,在大多数已有的报道中,每一条多肽仅仅涉及单一AD发病机制,这和AD药物的开发过程十分类似。这或许就是虽然发现了大量植物源AD预防肽,但还没有一款产品问世的原因,这也阻碍了植物源AD预防肽的发展。
核桃仁中丰富的油脂含量(65.8%)以及多种不饱和脂肪酸,使得核桃可作为植物油的来源之一。核桃粕是核桃仁榨油后的副产物,蛋白质含量超过50%,是十分优质的植物蛋白来源。而且,核桃蛋白中参与学习和记忆的氨基酸(谷氨酸、精氨酸和天冬氨酸)含量超过45%,是生产AD预防肽的优秀选择。但是大多数核桃粕都被用作饲料或者直接丢弃,不仅造成核桃蛋白资源的浪费,也严重阻碍了核桃产业的发展。
发明内容
本发明的目的在于提供一种基于CNN-LSTM神经网络从核桃酶解产物中筛选阿尔兹海默症预防肽的方法,所建立的CNN-LSTM神经网络能够筛选植物源阿尔兹海默症预防肽,采用本发明方法筛选得到的阿尔兹海默症预防肽能够预防阿尔兹海默症。
为了实现上述发明目的,本发明提供以下技术方案:
本发明提供了一种基于CNN-LSTM神经网络从核桃酶解产物中筛选阿尔兹海默症预防肽的方法,包括以下步骤:
(1)从核桃蛋白酶解产物中获得多肽序列,根据置信度>95%,多肽分子量≤1500、谱峰积分面积>1×108、未在uni_walnuts数据库中搜索到对应蛋白来源的多肽序列进行筛选,得到初始数据;
(2)在Web ofScience数据库中筛选具有氧化应激、神经消炎和胆碱能缺失活性的多肽数据,将多肽数据分为训练集和验证集;
(3)将训练集数据输入CNN-LSTM神经网络中,对阿尔兹海默症预防肽的特征进行学习总结,使用验证集数据进行验证,得到阿尔兹海默症预防肽预测模型;
(4)将步骤(1)得到的初始数据输入到步骤(3)获得的预测模型中进行筛选,得到阿尔兹海默症预防肽。
优选的,在步骤(2)获得多肽数据后,分训练集和验证集之前,还包括将所述多肽数据中的氨基酸使用数字替换的步骤。
优选的,所述氨基酸与数字替换的对应关系为Ala,A-1、Cys,C-2、Asp,D-3、Glu,E-4、Phe,F-5、Gly,G-6、His,H-7、Ile,I-8、Lys,K-9、Leu,L-10、Met,M-11、Asn,N-12、Pro,P-13、Gln,Q-14、Arg,R-15、Ser,S-16、Thr,T-17、Val,V-18、Trp,W-19和Tyr,Y-20。
优选的,步骤(4)中所述预防肽根据预测模型输出结果判断是否具备对抗阿尔兹海默症病理的活性,“0”表示多肽不具备对抗阿尔兹海默症病理的活性,“1”表示多肽具备对抗阿尔兹海默症病理的活性。
本发明还提供了具有预防阿尔兹海默症功效的多肽,所述多肽自N端到C端的氨基酸序列如SEQ ID NO.1~SEQ ID NO.4所示,具体如下:
EPEVLR(SEQ ID NO.1):Glu-Pro-Glu-Val-Leu-Arg;
VFPTER(SEQ ID NO.2):Val-Phe-Pro-Thr-Glu-Arg;
EYVTLK(SEQ ID NO.3):Glu-Tyr-Val-Thr-Leu-Lys;
ELEWER(SEQ ID NO.4):Glu-Leu-Glu-Trp-Glu-Arg。
相比于现有技术,本发明的有益效果为:
本发明从核桃蛋白酶解产物中获得了11883多肽,并根据一些与多肽序列无关的特性进行筛选,获得了60条核桃多肽。然后,构建了一种CNN-LSTM神经网络,总结了540条具有不同活性的阿尔兹海默症预防肽的氨基酸特征,并用于预测所筛选的核桃多肽的抗氧化、消炎和防止胆碱能缺失活性,发现4条多肽同时具备这三种活性,体外合成后使用小鼠模型进行验证。根据小鼠行为学实验结果,证实了所筛选的四条多肽均拥有预防阿尔兹海默症的功效;根据脑部海马区HE染色结果,证实了所筛选的4条核桃多肽能有效修复海马区神经元损伤;脑部生化指标的测试,证实了所筛选的核桃多肽可以从抗氧化、消炎和防止胆碱能缺失阻止阿尔兹海默症的发展。本发明所构建的深度学习神经网络可快速有效地获得具有预防阿尔兹海默症功效多肽,有助于核桃肽的发展。
附图说明
图1为CNN-LSTM神经网络的运行流程;
图2为CNN-LSTM神经网络的详细结构;
图3为核桃多肽预测活性韦恩图;
图4为水迷宫实验中小鼠穿越平台次数;
图5为水迷宫实验中小鼠在平台所在象限路程占比;
图6为水迷宫实验中小鼠在平台所在象限有效停留时间;
图7为跳台实验中小鼠的错误次数;
图8为跳台实验中小鼠的第一次潜伏期;
图9为小鼠脑组织海马区HE染色切片图;
图10为小鼠脑组织CAT活性;
图11为小鼠脑组织IL-1β含量;
图12为小鼠脑组织AChE活性。
具体实施方式
下面结合实施例对本发明提供的技术方案进行详细的说明,但是不能把它们理解为对本发明保护范围的限定。
实施例1
本实施例提供了一种基于CNN-LSTM神经网络从核桃酶解产物中筛选阿尔兹海默症预防肽的方法,包括以下步骤:
(1)获得核桃蛋白酶解产物,酶解产物的制备方法参照申请号为202111312857.3,发明名称为“一种用于预防阿尔兹海默症的核桃多肽及其应用”的发明专利记载。核桃蛋白酶解产物经过Thermo Scientific Orbitrap Fusion Eclipse Tribrid质谱仪鉴定和PEAKS X pro软件分析,获得了11883条不同序列的肽,根据一些与序列无关的条件进行初步筛选:ALC(%)是指PEAKS X pro软件分析结果中平均置信度,一般大于80%比较可靠,大于95%则非常可靠,所以ALC大于95%用于进一步筛选。小的或短的肽序列很容易被人体吸收,它们被认为是抗阿尔兹海默症作用的良好候选者。因此选择分子量≤1500的多肽。此外,高含量的多肽更有价值,质谱峰积分面积最小值被设定为1×108。未知来源的肽序列更具研究价值,选择未在uni_walnuts数据库中搜索到蛋白来源的肽;共筛选出60条多肽序列。
(2)在Web ofScience核心合集中分别输入(氧化应激、神经消炎和胆碱能缺失)+(多肽)+(阿尔兹海默症)作为检索关键词,获得了540条具有不同活性的多肽,并随机排列。将多肽中的氨基酸(A、C、D、E、F、G、H、I、K、L、M、N、P、Q、R、S、T、V、W、Y)分别使用(1、2、3、4、5、6、7、8、9、10、11、12、13、14、15、16、17、18、19、20)进行替换,构成CNN-LSTM神经网络的数据样本,其中随机选取85%作为训练集,剩余15%作为验证集。
(3)CNN-LSTM神经网络是通过Matlab软件实现,其主要流程和结构如图1和图2所示。阿尔兹海默症预防肽的氨基酸序列被数字替换后作为CNN-LSTM神经网络的输入,通过对训练集中多肽的特征进行学习总结,并对验证集的多肽进行验证,输出“0”和“1”,“0”表示多肽不具备对抗阿尔兹海默症病理的活性,“1”则表示有。CNN擅长感知数据集的局部属性,而LSTM则更注重整体信息。通过结合CNN和LSTM来发挥它们的优势将是有益的,这更适合于处理基于肽的样本。采用多尺度核的CNN来提取肽的特征。为了防止过度拟合,采用了最大池化操作,ReLU被用作激活单元。LSTM被用来通过隐藏单元分析序列流。全连接层被用作分类模块。经过验证后得知,上述模型对阿尔兹海默症预防肽的抗氧化、消炎和防止胆碱能缺失活性分别获得了0.750、0.873和0.725的准确率,具有较高的准确率,可用于验证所筛选的核桃多肽活性。
(4)根据步骤(3)获得的预测模型对步骤(1)得到的60条多肽序列进行分析与预测,预测结果如图3所示,从60条核桃多肽中分别获得了31、21和9条具有抗氧化、消炎和防止胆碱能缺失活性的多肽。其中有四条多肽同时具有这三种活性,分别是EPEVLR、VFPTER、EYVTLK和ELEWER,体外合成后用于小鼠实验,得到的预防肽自N端到C端的氨基酸序列如下所示:
EPEVLR(SEQ ID NO.1):Glu-Pro-Glu-Val-Leu-Arg;
VFPTER(SEQ ID NO.2):Val-Phe-Pro-Thr-Glu-Arg;
EYVTLK(SEQ ID NO.3):Glu-Tyr-Val-Thr-Leu-Lys;
ELEWER(SEQ ID NO.4):Glu-Leu-Glu-Trp-Glu-Arg。
实施例2
本实施例对实施例1筛选得到的阿尔兹海默症预防肽进行活性测试,方法如下:
(1)固相合成多肽
采用Fmoc固相多肽合成策略进行多肽的合成,以Fmoc-AA-Wang树脂为起始固相载体,无水DMF为反应溶剂,利用乙醇胺除去氨基末端Fmoc保护基,HBTU、HoBt及N-甲基吗啉为活化剂,活化Fmoc保护氨基酸的羧基,并与树脂上游离的氨基偶联。偶联结束后,采用三氟乙酸脱掉侧链保护基,并从树脂上裂解得到游离多肽。利用半制备反相液相色谱纯化固相合成多肽,反相液相色谱的流动相为:A:0.1%TFA/水,B:0.1%TFA/乙腈,流动相条件为:0%~90%B/30min~90%B/10min,色谱柱为:依利特5μm 10.0mm×250mm C18,进样量为100μL,流速为1mL/min,检测波长为220nm,利用LC-MS/MS鉴定组分的氨基酸序列,得到四条预防肽。
(2)核桃多肽预防阿尔兹海默症活性的测试
通过小鼠实验验证上述得到的四条预防肽的活性。小鼠隔离检疫一周并进行适应性饲养,随机分为6组:正常对照组(Control)、模型组(Model)、多肽组(EPEVLR、VFPTER、EYVTLK和ELEWER组)。模型组和多肽组小鼠先进行D型半乳糖(D-gal)造模处理,两组小鼠接受500mg/kg/d连续皮下注射8周,自第5周开始,模型组同时灌胃生理盐水,多肽组分别同时灌胃EPEVLR、VFPTER、EYVTLK和ELEWER,正常组自由进食。饲养结束后,通过行为学实验验证核桃多肽预防阿尔兹海默症的功效。
行为学实验:小鼠的行为学实验主要分为跳台实验和水迷宫实验。训练四天后,开始测试。跳台实验结束30min后开始水迷宫实验。
水迷宫实验:水迷宫直径1.2m,高0.5m,站台直径0.09m,高0.3m,站台隐藏于水面之下1cm左右。向水池内注入自来水,水池的温度需要维持在23℃左右。参数设定为:游泳时间(60s)、平台上停留时间(10s)、选择小鼠实验模式,调整红线圆圈使之分别准确框定水池及平台范围。选择平台所在象限的对位象限为研究象限,将小鼠放入水中,立即用软件记录小鼠自入水、寻找平台到稳定爬上平台所需时间。小鼠若能在60s内爬上站台并稳定站立3s,记录所需时间;若入水后60s内未能找到站台则记录潜伏期为60s,并将小鼠引导上站台稳定站立15s后拿下来,休息60s再进行下一次训练。
跳台实验:跳台为长方形反射箱,共有八个区域,底部铺以可通适当电流的铜栅。每个小的区间有一个高和直径均为4.5cm的小平台。设置参数为:时间(5min)、刺激强度(0.6mA)。将小鼠放在铜栅上,待其情绪稳定后通电,记录每只小鼠受到电击的次数(错误次数),第一次跳下的时间(潜伏期)。
小鼠水迷宫实验结果如图4~8所示,由图4~8可知,模型组通过D-gal造模后,其水迷宫实验中穿越平台次数、平台所在象限路程占比以及平台所在象限有效停留时间较空白对照组均明显降低,跳台实验中错误次数明显增加,第一次潜伏期也明显低于空白组,表明小鼠老化模型造模成功。核桃多肽EPEVLR、VFPTER、EYVTLK和ELEWER灌胃后的小鼠,其行为学实验相关指标均十分接近空白对照组,表明所得到的四条核桃多肽均具有预防阿尔兹海默症的功效。
(3)小鼠脑组织海马区HE染色
小鼠经过行为学活性测试后,处死前12h对小鼠进行断食但不断水操作。浓度为2%~3%异氟烷对小鼠进行吸入式麻醉。小鼠麻醉后,断颈椎处死。取小鼠大脑组织用生理盐水冲洗,将其放置在4%多聚甲醛溶液中进行后固定。固定后,使用石蜡对其进行包埋处理,获得组织石蜡包埋蜡块。然后对石蜡块进行切片,设置切片厚度为4μm。使用苏木素(Hematoxylin)-伊红(Eosin)染色法组织切片染色,在显微镜明场下面观察海马区神经元损伤情况。
结果如图9所示,灌胃核桃多肽小鼠脑部海马区的神经元损伤数量明显低于模型组,表明EPEVLR、VFPTER、EYVTLK和ELEWER可减少脑部神经元损伤。
(4)小鼠脑组织生化指标测试
分别对小鼠脑组织中氧化应激、炎症和胆碱能缺失相关指标进行测试,测试指标为过氧化氢酶活性(CAT)、白细胞介素-1(IL-1β)和乙酰胆碱酯酶活性(AChE)。所有指标均按照Elasa试剂盒(购自上海原鑫生物公司)说明书进行。
结果如图10~12所示,筛选的多肽组小鼠脑组织CAT活性明显高于模型组,AChE活性明显低于模型组;IL-1β指标中,除了EYVTLK组IL-1β含量与模型组无明显差别外,EPEVLR、VFPTER和ELEWER组小鼠脑组织中IL-1β明显低于模型组。表明EPEVLR、VFPTER和ELEWER可从抗氧化、消炎和防止胆碱能缺失预防阿尔兹海默症,EYVTLK则可从抗氧化和防止胆碱能缺失预防阿尔兹海默症。
由以上实施例和实验例可知,本发明提供了一种基于CNN-LSTM神经网络从核桃酶解产物中筛选阿尔兹海默症预防肽的方法,所建立的CNN-LSTM神经网络能够筛选植物源阿尔兹海默症预防肽,采用本发明方法筛选得到的阿尔兹海默症预防肽能够预防阿尔兹海默症。
以上所述仅是本发明的优选实施方式,应当指出,对于本技术领域的普通技术人员来说,在不脱离本发明原理的前提下,还可以做出若干改进和润饰,这些改进和润饰也应视为本发明的保护范围。
Claims (5)
1.一种基于CNN-LSTM神经网络从核桃酶解产物中筛选阿尔兹海默症预防肽的方法,其特征在于,包括以下步骤:
(1)从核桃蛋白酶解产物中获得多肽序列,根据置信度>95%,多肽分子量≤1500、谱峰积分面积>1×108、未在uni_walnuts数据库中搜索到对应蛋白来源的多肽序列进行筛选,得到初始数据;
(2)在Web ofScience数据库中筛选具有氧化应激、神经消炎和胆碱能缺失活性的多肽数据,将多肽数据分为训练集和验证集;
(3)将训练集数据输入CNN-LSTM神经网络中,对阿尔兹海默症预防肽的特征进行学习总结,使用验证集数据进行验证,得到阿尔兹海默症预防肽预测模型;
(4)将步骤(1)得到的初始数据输入到步骤(3)获得的预测模型中进行筛选,得到阿尔兹海默症预防肽。
2.根据权利要求1所述的筛选阿尔兹海默症预防肽的方法,其特征在于,在步骤(2)获得多肽数据后,分训练集和验证集之前,还包括将所述多肽数据中的氨基酸使用数字替换的步骤。
3.根据权利要求2所述的筛选阿尔兹海默症预防肽的方法,其特征在于,所述氨基酸与数字替换的对应关系为Ala,A-1、Cys,C-2、Asp,D-3、Glu,E-4、Phe,F-5、Gly,G-6、His,H-7、Ile,I-8、Lys,K-9、Leu,L-10、Met,M-11、Asn,N-12、Pro,P-13、Gln,Q-14、Arg,R-15、Ser,S-16、Thr,T-17、Val,V-18、Trp,W-19和Tyr,Y-20。
4.根据权利要求1所述的筛选阿尔兹海默症预防肽的方法,其特征在于,步骤(4)中所述预防肽根据预测模型输出结果判断是否具备对抗阿尔兹海默症病理的活性,“0”表示多肽不具备对抗阿尔兹海默症病理的活性,“1”表示多肽具备对抗阿尔兹海默症病理的活性。
5.具有预防阿尔兹海默症功效的多肽,其特征在于,所述多肽自C端到N端的氨基酸序列如SEQ ID NO.1~SEQ ID NO.4所示。
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