CN113109418B - 一种己糖激酶2抑制剂的筛选方法和小分子化合物在制备抗肿瘤药物中的应用 - Google Patents
一种己糖激酶2抑制剂的筛选方法和小分子化合物在制备抗肿瘤药物中的应用 Download PDFInfo
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Abstract
本发明提供了一种己糖激酶2抑制剂的筛选方法和小分子化合物在制备抗肿瘤药物中的应用,筛选方法包括:将候选抑制剂和缓冲液混合,孵育,终止反应,得到反应后溶液;所述缓冲液中包括己糖激酶2和葡萄糖;将反应后溶液和等体积的葡萄糖‑1‑13C混匀,得到待分析物;将待分析物滴加至石墨结构型纳米材料基质表面,干燥后进行MALDI‑MS检测,筛选,得到己糖激酶2抑制剂。该方法以石墨结构型纳米材料为基质,结合MALDI‑MS检测,超快速的筛选检测(5.1小时内分析1836个样品);获得一系列高抑脑瘤生长活性的小分子药物;对接小分子药物药效分析/药代动力学检测,无需转移至其它检测平台。
Description
技术领域
本发明属于分析检测技术领域,尤其涉及一种己糖激酶2抑制剂的筛选方法和小分子化合物在制备抗肿瘤药物中的应用。
背景技术
基质辅助激光解吸电离质谱是一种软电离技术,在快速分析生物大分子 (核酸,蛋白质,多肽等)和聚合物上取得了很大的成功。但是,在MALDI-MS (基质辅助激光解吸电离质谱)中常用的传统有机基质在质荷比低于700时会产生很高背景噪音,干扰质谱分析小分子的信号,并且有机基质倾向于形成随机分布的不同尺寸的晶体(几十微米量级),降低了信号的重现性,因此严重阻碍了MALDI在小分子分析检测及应用方面的发展。
现有技术报道中,无机的纳米材料或无机纳米结构表面已经作为合适的基质被应用在MALDI里替代有机基质,其中包括硅,合金,金属氧化物,碳纳米材料等。它们能克服传统有机基质在低分子量区的背景干扰,但是对于体内小分子的敏感检测和精确成像却很困难,不能用于新药快速筛选。
尽管这些材料在分析小分子上有大改进,但是获得的质谱灵敏度不高且重复性不好,所以在对天然产物、血液、生物样品的分析和直接组织成像的应用上仍有很大缺陷。
计算机筛选到获得目标分子的过程虽快,但是计算机模拟的药物环境中是缺少试剂等实际的实验条件的,这仍然是该方法的不足之处。常用的荧光或紫外吸收方法,需要额外的人工底物修饰或偶联酶,会带来干扰候选药物信号的问题。现有的最优的配有超快梯度常规短柱的LC-MS系统,其在速度上仍有限制,在3.75小时内仅分析768份血样(不包括大量的预处理时间)。
发明内容
有鉴于此,本发明的目的在于提供一种己糖激酶2抑制剂的筛选方法和小分子化合物在制备抗肿瘤药物中的应用,该方法快速且准确度高。
本发明提供了一种己糖激酶2抑制剂的筛选方法,包括以下步骤:
将候选抑制剂和缓冲液混合,孵育,终止反应,得到反应后溶液;所述缓冲液中包括己糖激酶2和葡萄糖;
将反应后溶液和等体积的葡萄糖-1-13C混匀,得到待分析物;
将待分析物滴加至石墨结构型纳米材料基质表面,干燥后进行 MALDI-MS检测,筛选,得到己糖激酶2抑制剂。
在本发明中,所述筛选的条件为:
候选抑制剂水溶液浓度为20μmol/L,己糖激酶2活性的抑制率≥25%;
抑制率=(1-B/A)×100%;
所述A为未加抑制剂的反应前溶液中葡萄糖浓度-未加抑制剂的反应后溶液中葡萄糖浓度;
所述B为加抑制剂的反应前溶液中葡萄糖浓度-加抑制剂的反应后溶液中葡萄糖浓度;
反应溶液中葡萄糖浓度=([葡萄糖+Na]+的质谱信号强度/[葡萄糖-1-13C +Na]+的质谱信号强度)×已知葡萄糖-1-13C浓度。
在本发明中,所述候选抑制剂和缓冲液的体积比为1:1;
所述缓冲液中己糖激酶2的质量和葡萄糖的物质的量比为(0.245~0.255) g:0.5mmol;
所述候选抑制剂的浓度为1μmol/L~1000μmol/L。
在本发明中,所述孵育的温度为35~40℃,孵育的时间为55~65min。
在本发明中,所述MALDI-MS检测采用反射正负离子模式;
MALDI-MS检测的实验参数:
355nm的Nd:YAG激光,激光能量为30%,对应于每脉冲57μJ,激光脉冲持续时间:3ns,激光光斑大小为50~100μm;
每个样本经4次重复测试;每一种质谱累积3000个激光光斑。
在本发明中,所述石墨结构型纳米材料基质(GDs)主要含有羟基(-OH)、羰基(C=O)和环氧基(C-O-C)三种官能团。GDs表面官能团百分比:C-OH,26%; C=O,13%;C-O-C,1%。所述GDs拥有良好分散性,并且粒径分布比较均一大约5-6nm,高度均一(高度大约6nm),表明GDs近似一个立方块体;蜂窝状石墨结构;标准六边形晶体结构;在337nm和355nm处有较强的紫外的吸收,覆盖了MALDI-MS最广泛使用的激光波长。
在本发明中,所述候选抑制剂由以下方法获得:
在质子化状态参数为pH=7.0±2.0,范德华半径的标度因子设为1.0,最大部分原子电荷设为0.25模拟环境下,将所述初步目标化合物与HK2先采用 Glide-SP模式对结合亲和力进行评分和排序,再对得到排名靠前的50000个化合物采用GlideXP对接模式评分,随后采用ACD/ADME软件包预测所选化合物的ADMET性质,对Glide XP对接的1000个排名靠前的化合物进行过滤,去除那些不符合以下规则的化合物:(1)pH=7.0,logP/logD<5.5;(2)违反 Lipinski的五规则<2;(3)违反Opera的药物相似性规则<3;(4)功能官能团没有毒性、反应性或REOS规则定义的其他不良部分;
最后采用Discovery Studio 2.5中的Find Diversity Molecule模块,根据FCFP_4指纹计算出的Tanimoto距离对其余分子进行聚类,得到候选抑制剂。
本发明提供的上述方法能够在质谱检测、质谱成像、蛋白质组学、代谢组学、药物研发、药物分析与应用领域中应用。
在本发明中,上述筛选方法以石墨结构型纳米材料基质作为新型基质,结合MALDI质谱技术对涉及各种小分子的化学反应进行反应物(或产物)鉴定测量,从而筛选具有特定化学结构及活性的小分子化合物;本发明利用上述技术,对特定小分子化合物在活体实验中的吸收摄取、血药浓度、器官分布以及在这些过程中发生的化学结构变化进行监测;本发明利用上述技术结合活体器官三维空间的组织形态学特征,同时对分布于其中的多种小分子进行可视化检测。该方法筛选得到调控肿瘤细胞代谢重编程和抗肿瘤活性的小分子化合物及其衍生物。
本发明通过上述筛选方法筛选得到己糖激酶2抑制剂是小分子化合物,能够应用于抗肿瘤药物的制备中。
本发明还提供了小分子化合物在制备抗肿瘤药物中的应用;
所述小分子化合物具有式1~式45结构:
上述化合物结构组成:以碳链连接两端芳香基为主,碳链中含有酰胺,甲氧基,羟基,芳香基上为卤素取代,羟基,环氧基取代等。
上述化合物中,式6~式14均为式1小分子抑制剂的衍生物,以NH右侧的六元环侧链取代为主,例如甲基、苯环和卤素取代等;式15~式23均为式2 小分子抑制剂的衍生物,以甲酰胺右侧的萘环侧链取代为主,例如甲氧基,五元环取代等。式24~式29均为式3小分子抑制剂的衍生物,NH右侧的苯环苯基取代,苯环上N移位,碳链甲基,苯环取代等。式30~式40均为式4小分子抑制剂的衍生物,NH右侧的碳链取代,苯环上甲基取代等。式41~式45均为式5小分子抑制剂的衍生物,NH右侧的苯环苯基取代,苯环上N移位,碳链甲基,远端苯环取代等。
在本发明中,所述小分子化合物对肿瘤细胞由于发生代谢重编程引起的糖酵解异常中的关键蛋白酶有抑制作用,作为药物分子单独使用或与其它已知药物联合使用来杀伤肿瘤细胞。
在本发明中,所述小分子化合物能够通过抑制肿瘤细胞的代谢异常途径,阻碍其在化疗过程中对受损伤的DNA进行修复的能力;
所述小分子化合物能够突破血脑屏障的限制,在通常药物难以到达的肿瘤部位被摄取和富集。
在本发明中,在单次给药或连续多次给药的情况下,对取血量小于10微升的样品进行药物分子的质谱定量分析,能够实现单只模型动物即可完成药代动力学(血药浓度-时间曲线)的数据采集。所述药指的是小分子化合物。
本发明提供了一种己糖激酶2抑制剂的筛选方法,包括以下步骤:将候选抑制剂和缓冲液混合,孵育,终止反应,得到反应后溶液;所述缓冲液中包括己糖激酶2和葡萄糖;将反应后溶液和等体积的葡萄糖-1-13C混匀,得到待分析物;将待分析物滴加至石墨结构型纳米材料基质表面,干燥后进行 MALDI-MS检测,筛选,得到己糖激酶2抑制剂。该方法以石墨结构型纳米材料为基质,结合MALDI-MS检测,超快速的筛选检测(5.1小时内分析1836 个样品);获得一系列高抑脑瘤生长活性的小分子药物;对接小分子药物药效分析,无需转移至其它检测平台。
附图说明
图1为高通量筛选己糖激酶2(HK2)候选抑制剂的GLMSD平台示意图;
图2为38种候选抑制剂在4种不同浓度下对HK2的抑制率;
图3中(a)为化合物8的结构式,(b)为化合物8从比色试剂盒和GLMSD 获得的HK2酶的抑制曲线,以及(c)为通过GLMSD平台检测到的四种浓度的化合物8中HK2活性的原始数据;
图4中(a)为化合物11的结构式,(b)为化合物8从比色试剂盒和GLMSD 获得的HK2酶的抑制曲线,以及(c)为通过GLMSD平台检测到的四种浓度的化合物11中HK2活性的原始数据;
图5中(a)为化合物13的结构式,(b)为化合物8从比色试剂盒和GLMSD 获得的HK2酶的抑制曲线,以及(c)为通过GLMSD平台检测到的四种浓度的化合物13中HK2活性的原始数据;
图6中(a)为化合物21的结构式,(b)为化合物8从比色试剂盒和GLMSD 获得的HK2酶的抑制曲线,以及(c)为通过GLMSD平台检测到的四种浓度的化合物21中HK2活性的原始数据;
图7中(a)为化合物27的结构式,(b)为化合物8从比色试剂盒和GLMSD 获得的HK2酶的抑制曲线,以及(c)为通过GLMSD平台检测到的四种浓度的化合物27中HK2活性的原始数据;
图8-1为TMZ药代动力学数据;
图8-2为化合物27的药代动力学数据;
图9为药物和代谢物(化合物27:m/z 499,乳酸:m/z 113)在脑组织切片中的MSI图像;
图10中(b)为裸鼠经各种治疗消除原发肿瘤后的U87MG皮下肿瘤生长曲线,误差棒代表平均值±s.d,(n=6);(c)为接受各种治疗后患有皮下U87MG 肿瘤的小鼠的存活率(每组n=6);(d)为具有代表性的生物发光图像;
图11为化合物27对脑神经胶质瘤细胞U87的抗增殖活性;
图12中(e)为通过Glide XP对接模拟预测的comp-27-HK复合物的结合结构示意图;(f)为具有氢键和强疏水相互作用的复合27-HK配合物的结合模式的二维示意图;
图13为化合物27和3-Br在每个残基上的相互作用分数(Eintcompd 27-Eint3-Br)的差异;
图14为化合物8、化合物11、化合物13和化合物21对脑神经胶质瘤细胞U87的抗增殖活性测试图;
图15为Compound 27治疗后胶质瘤U87细胞重编程代谢途径的正常化;
图16为流式细胞仪分析compd27诱发的U87细胞凋亡(Annexin V-FITC/PI染色)。
具体实施方式
为了进一步说明本发明,下面结合实施例对本发明提供的一种己糖激酶2 抑制剂的筛选方法和小分子化合物在制备抗肿瘤药物中的应用进行详细地描述,但不能将它们理解为对本发明保护范围的限定。
实施例1
38种候选抑制剂的来源:
2、化合物与HK2对接模拟(精度模式:标准精度(SP)和超精度(XP)) 都是由的Glide制作(质子化状态参数为pH=7.0±2.0,范德华半径的标度因子设为1.0,最大部分原子电荷设为0.25。)
具体对接过程:将所有化合物与HK2结构对接,用Glide-SP模式对结合亲和力进行评分和排序。然后,排名靠前的50000个分子用GlideXP对接模式评分。随后应用ACD/ADME软件包预测所选化合物的ADMET性质,对Glide XP对接的1000个排名靠前的化合物进行过滤,去除那些不符合以下规则的化合物:(1)pH=7.0,logP/logD<5.5;(2)违反Lipinski的五规则<2;(3)违反 Opera的药物相似性规则<3;(4)功能官能团没有毒性、反应性或REOS规则定义的其他不良部分。然后,使用Discovery Studio 2.5中的Find Diversity Molecule模块,根据FCFP_4指纹计算出的Tanimoto距离对其余分子进行聚类。最后,从Specs库中购买了40个对接分数最低的命中化合物;
所述40个化合物的结构式如下:
上述化合物中,化合物2和化合物33,化合物34因水溶性不好,进行排除,剩余37种化合物作为候选抑制剂继续进行测试;在50μL反应缓冲液中进行HK2活性试验,该缓冲液由10mM葡萄糖、1.2mM ATP(腺嘌呤核苷三磷酸)、2.5μLHK2(0.1mg/mL)和25mMTris-HCl缓冲液以及5mMMgCl2组成,pH值为7.5。加入不同浓度的37种候选抑制剂,反应缓冲液和候选抑制剂的体积比为1:1,候选抑制剂的浓度根据实验需要选择1μmol/L、 10μmol/L、100μmol/L和1mmol/L中的浓度,反应混合物在置于加热振荡反应器上,37℃孵育60分钟。通过添加TFA(三氟乙酸终止剂)至最终浓度2%(v/v) 停止反应。每个小分子抑制剂均有3次平行实验。取终止反应后的溶液加入等体积的0.5mM葡萄糖-1-13C混匀后,取1μL作为待分析样品进行质谱检测。
GDs的制备步骤A):石墨点的合成
最初的石墨点是由电化学腐蚀的方法得到的。首先将两根石墨棒(99.99%, AlfaAesar Co.Ltd)平行的插入去离子水中,一个作为阳极,一个作为阴极,同时保证两极之间的静态电压为30V。整个电解过程持续两周,并且持续保持高强度的磁力搅拌,然后产生最初始的石墨量子点。但是此时的石墨量子点溶液中还混杂着大块的石墨颗粒,所以需要经过过滤和高速离心(22000rpm,30 min),获得粒径均一且水溶性非常好的石墨点。
步骤B):还原石墨点的制备
硼氢化钠还原是一个温和的过程,在室温下发生并且选择性的只还原羰基(C=O)和环氧基。具体步骤如下:称取获得的石墨点300mg溶于300mL 水中,然后加入适量的硼氢化钠(浓度分别为150mM)。在室温条件下,磁力搅拌反应6小时。然后使用透析袋透析3天,获得还原的石墨点(GDs)。最后将产物在60℃的烘箱中干燥12小时。
GDs以1mg/mL的浓度分散在水中作为待用基质溶液。采用快干法制样:先将1μL的基质溶液滴加到靶板上,1万伏电场的高磁场室温自然干燥后再将 1μL待分析样品滴加到干燥的基质表面,待样品自然干燥后直接进行质谱分析:
MALDI-MS仪器采用的是Bruker Ultraflex III TOF/TOF质谱仪,主要采用反射正负离子模式。仪器参数为355nm的Nd:YAG激光,激光能量为30%,对应于每脉冲57μJ(激光脉冲持续时间:3ns),激光光斑大小约为是50~100 μm,每个样本都经过4次的重复测试,每一种质谱都累积3000个激光光斑。所有样品均在相同的仪器条件下测量。
质谱分析后根据以下筛选条件进行筛选:
候选抑制剂水溶液浓度为20μmol/L,己糖激酶2活性的抑制率≥25%;
抑制率=(1-B/A)×100%;
所述A为未加抑制剂的反应前溶液中葡萄糖浓度-未加抑制剂的反应后溶液中葡萄糖浓度;
所述B为加抑制剂的反应前溶液中葡萄糖浓度-加抑制剂的反应后溶液中葡萄糖浓度;
反应溶液中葡萄糖浓度=([葡萄糖+Na]+的质谱信号强度/[葡萄糖-1-13C +Na]+的质谱信号强度)×已知葡萄糖-1-13C浓度;
筛选得到化合物8(具有上述式1结构)、化合物11(具有上述式2结构)、化合物13(具有上述式3结构)、化合物21(具有上述式4结构)和化合物 27(具有上述式5结构)。
图1为高通量筛选己糖激酶2(HK2)候选抑制剂的GLMSD平台示意图; 102个浓度×3个平行测试实验×6个平行样品,每个试样测试10s;超快速的小分子药物筛选检测速度:5.1小时内分析1836个样品;该平台对接小分子药物药效分析,无需转移至其它检测平台。
图2为38种候选抑制剂在4种不同浓度下对HK2的抑制率;从图2可以看出:对比常用的己糖激酶2比色的筛选方法,发现本申请提供的方法和比色法所得的化合物的抑制率接近,说明,本申请提供的GLMSD检测结果准确。图中由红至紫为抑制效率从强到弱,灰色为检测试剂盒无法检测。此外,选择 3-溴丙酮酸(3-BP,一种常用的HK2抑制剂)作为阳性对照,筛选得到化合物8(对应上述式1,抑制率为44%)、化合物11(对应上述式2,抑制率为29%)、化合物13(对应上述式3,抑制率为42%)、化合物21(对应上述式4,抑制率为25%)和化合物27(对应上述式5,抑制率为31%)5个新的小分子 (抑制剂小分子浓度为20μM),对HK活性表现出良好的抑制能力。
己糖激酶比色法并不像GLMSD平台那样广泛,是因为比色法是监测 340nm紫外吸收变化来测定酶活性的,但许多小分子在这个范围内有很强的紫外吸收,如化合物3、化合物4、化合物6、化合物9、化合物11、化合物23、化合物25、化合物26、化合物28和化合物39,这些化合物自身吸收峰改变了待测吸收峰的形状和位置,干扰了检测结果。由于这一局限性,常规比色法检测过程中有10种化合物未能成功检测出抑制性,而其中化合物11在GLMSD 平台检测中表现出良好抑制的作用。因此,GLMSD平台可以对所有小分子进行抑制效率评估,不受紫外吸收峰影响。
图3中(a)为化合物8的结构式,(b)为化合物8从比色试剂盒和GLMSD 获得的HK2酶的抑制曲线,以及(c)为通过GLMSD平台检测到的四种浓度的化合物8中HK2活性的原始数据;
图4中(a)为化合物11的结构式,(b)为化合物8从比色试剂盒和GLMSD 获得的HK2酶的抑制曲线,以及(c)为通过GLMSD平台检测到的四种浓度的化合物11中HK2活性的原始数据;
图5中(a)为化合物13的结构式,(b)为化合物8从比色试剂盒和GLMSD 获得的HK2酶的抑制曲线,以及(c)为通过GLMSD平台检测到的四种浓度的化合物13中HK2活性的原始数据;
图6中(a)为化合物21的结构式,(b)为化合物8从比色试剂盒和GLMSD 获得的HK2酶的抑制曲线,以及(c)为通过GLMSD平台检测到的四种浓度的化合物21中HK2活性的原始数据;
图7中(a)为化合物27的结构式,(b)为化合物8从比色试剂盒和GLMSD 获得的HK2酶的抑制曲线,以及(c)为通过GLMSD平台检测到的四种浓度的化合物27中HK2活性的原始数据;
从图3~图7可以看出,化合物8、化合物11、化合物13、化合物21和化合物27这5个化合物的不同浓度下对应的抑制效果,对HK2均有较好的抑制效果。
图8-1为TMZ(替莫唑胺)药代动力学数据;其中(d)为小鼠腹腔注射 TMZ(替莫唑胺)后血浆中TMZ的平均浓度-时间曲线;(f)为每只小鼠的 TMZ药代动力学曲线进行中值分析;(g)为用GLMSD测定多次给药-药代动力学曲线;从图8可以看出:GLMSD平台能够针对性获取27号小分子化合物的药代动力学数据。GLMSD在药代动力学研究中的竞争优势:(1)可追踪每个个体的完整药物血药浓度曲线;(2)减少试验中使用的小鼠总数。由于 GLMSD方法的血样消耗量低(每个时间点10μL血液),因此可以使用一只小鼠完成药物的整个药代动力学曲线(24小时内11个时间点的血液取样,最小间隔为0.25小时)。八只小鼠(n=8)的TMZ平均药代动力学曲线(图8-1 中d)提供了Cmax(33.66μg/mL)、Tmax(0.5h)、T1/2(1.72h)和AUC0-24 h(247.05 μg/mL·h)的详细值,与以往的文献研究数据相似,证明GLMSD方法能够完成药物动力学研究。图8-1中f显示了连续5天每天服用TMZ(8只小鼠) 的平均血浆浓度。
在验证了GLMSD法在药动学检测中的优越性后,我们进一步应用该方法对化合物27的药动学曲线进行了表征,见图8-2,图8-2为化合物27的药代动力学数据。8只小鼠均进行单次给药(化合物27剂量为40mg/kg),血浆药代动力学PK值结果如图8-2中f所示,包括Cmax(14.65μg/mL)、Tmax(2h)、 T1/2(4.12h)和AUC0-24h(64.36μg/mL·h)。基于GLMSD能在一只小鼠中检测到整个PK曲线的优势,我们观察到8只小鼠中的3只(#2,#3,#4)在 8h出现这种小分子抑制剂的特征性再吸收峰,而在其他5只小鼠中几乎没有。这一显著现象与个体间的药物摄取差异有关,提示化合物27可能通过二次吸收途径重新进入血液循环。在连续多次给药(图8-2中g)的模式下,每天(最后一次给药后1、3、6和8小时)从每只小鼠收集化合物27(40mg/kg)的药代动力学数据,持续5天。无论是单剂量(图8-2中e)还是连续多剂量(图 8-2中h)形式的药物给予方式,传统的LC-MS技术仅限于通过牺牲一只小鼠来获得药物药代动力学的单个数据点,而GLMSD可以通过提供基于单个小鼠的完整药代动力学曲线来突破此限制。
图9为药物和代谢物(化合物27:m/z 499,乳酸:m/z 113)在脑组织切片中的MSI图像;其中,以H&E染色连续切片的光学显微照片作为参考。脑胶质瘤和侧脑室用虚线环表示;色条编码MSI中三个小分子的信号强度;分辨率:10μm。图9表明:化合物27具有穿透血脑屏障的能力。100-1000个小分子的叠加图像(左第1个图)清晰地显示了脑的纵切面结构(U87细胞移植瘤位于右额叶),这与H&E染色的相邻纵向连续组织切片(左第2个图)一致。左第3个图显示化合物27主要存在胼胝体和海马的轮廓边缘。左第4个图显示乳酸(m/z 113.35)在胶质瘤植入部位周围的含量明显高于其他脑组织。胶质瘤部位有化合物27的富集,这表明这种小分子具有良好的渗透性,可以突破血脑屏障。
图10中(b)为裸鼠经各种治疗消除原发肿瘤后的U87MG皮下肿瘤生长曲线,误差棒代表平均值±s.d,(n=6);(c)为接受各种治疗后患有皮下U87MG 肿瘤的小鼠的存活率(每组n=6);(d)为具有代表性的生物发光图像,以追踪经过各种治疗后原位U87-luciferase小鼠的癌症生长。由图10可以看出:化合物27能够抑制实体瘤的生长。在所有不同的实验组(图10中b和c)中,用TMZ和化合物27联合治疗的小鼠的总存活率(OS)是最好的。TMZ+化合物27的中位生存时间(58天),显著长于其他治疗组:PBS(15天),3-BP (17天),化合物27(30天),TMZ(35天)和TMZ+3-BP(35天)。这些实验结果表明,作为HK2抑制剂,化合物27与TMZ等化疗药物联合用于癌症治疗具有良好的药物适应性。(图10中d)与PBS相比,单独使用TMZ或化合物27的单一药物治疗延缓了胶质瘤的生长。然而,只在治疗的前20天,胶质瘤引起的小鼠死亡被减少。在这段时间后,两个单一药物组的原位U87异质瘤的存活率都因恶性胶质瘤而迅速下降。与此形成鲜明对比的是,TMZ联合化合物27治疗组可以抑制生物发光的U87胶质瘤并显著提高生存率
图11为化合物27对脑神经胶质瘤细胞U87的抗增殖活性;从图11看出:化合物27能够抑制U87生长,浓度为11.31μM时,能够杀死一半的肿瘤细胞。
图12中(e)为通过Glide XP对接模拟预测的comp-27-HK复合物的结合结构示意图;(f)为具有氢键和强疏水相互作用的复合27-HK配合物的结合模式的二维示意图。HK2的活性位点残基Phe156、His159、Ser155、Cys158、 Asn235、Asp209、Glu294、Ile229、Asn208和Glu260均与化合物27结合。其中,HK2上的Asp209、Ile229和Glu260对化合物27的结合最为关键。Glu260 与酰胺的氮原子形成氢键,残基Asp209形成两个氢键。Ile229与化合物27的苯环之间的疏水性接触(芳烃-H相互作用)也有助于结合。图12证明小分子化合物27和HK酶的结合部位较多。
图13为化合物27和3-Br在每个残基上的相互作用分数(Eintcompd 27-Eint3-Br)的差异,其中突出了重要的残基(氨基酸残基,组成蛋白质脱了一个水的形式)。通过中的Glide模块计算配体和蛋白质残基之间的总相互作用能,范德华力和氢键分数;通过理论计算,小分子化合物27比常用HK酶抑制剂3-Br与HK酶的结合力强。化合物27和3-BP之间结合机制的对比呈现在图中,显示化合物27与HK2的结合位点更多,这可能是化合物27对HK2活性抑制效果更好的原因。
图14为化合物8、化合物11、化合物13和化合物21对脑神经胶质瘤细胞U87的抗增殖活性测试图。从图14可知,GLMSD平台筛选得到的上述4 个小分子化合物对U87均有抑制效果。
实施例2靶向代谢组学分析
1.代谢物提取
收集1×107细胞(一个样本细胞数),用新配的淬灭剂淬灭后离心(1000×g, 1分钟)去除细胞上清液。用100μL超纯水重新悬浮细胞,混匀。加入800μL 冷甲醇:乙腈(1:1,v/v)后,将混匀细胞样品在冰浴中超声处理30分钟。混合物在-20℃下储存1h以沉淀蛋白质。在4℃下离心(14000×g,20分钟)后,收集上清液,冷冻干燥,并在-80℃下保存,然后用GC-MS进行分析;
2、样品检测
将冻干的样品重新悬浮于溶液(乙腈:水,1:1,v/v,100μL)中,然后在4℃下离心(14000×g,10分钟)。收集上清液(100μL),并用乙腈溶液(100μL) 稀释,使用安捷伦1290Infinity LC系统(安捷伦科技,中国北京)和5500 QTRAP质谱仪(加拿大多伦多,ABSciex)在4℃下装载GS-MS样品。在 ACQUITY-UPLC-BEH柱(1.7μm,2.1mm×150mm;沃特斯技术(上海)有限公司)上,以300μL/min的流速进行色谱分离,其中溶剂A(流动相)为 15mM醋酸铵水溶液,溶剂B为乙腈。梯度洗脱的色谱条件由90%B下降到 40%B,18分钟后由40%B急剧上升到90%B,0.1分钟后保持90%B的体积比为4.9分钟,整个过程持续时间为23分钟,为监测体系的稳定性,从32个实际样品中提取等体积的复合物,用以对质量控制(QC)样品进行处理并放入真实样品中。质谱实验在负电离和多反应监测模式下进行,具体参数为:源温度450℃,雾化器气体(GS1):45,辅助气体(GS2):45,帘气(CUR):30,离子空间电压浮动(ISVF):-4500V。
3、数据处理
使用分析软件(AB Sciex,多伦多,加拿大)对标准GC-MS数据进行处理,包括将原始质谱数据转换为包含m/z的数据,测量相应的离子强度和保留时间,以及随后的统计分析。所有样品的峰检测和校准均参照其化学标准 (Sigma-Aldrich)进行比较。数据矩阵上传到MetaboAnalyst 5.0进行主成分分析(PCA)和层次聚类分析(HCA)。
4、流式细胞术实验
在DMEM培养基中,将5×105个U87细胞接种于24孔板中。培养24小时后,将化合物27(终浓度20μM)直接加入细胞生长培养基中,37℃孵育 24小时,用胰蛋白酶短暂消化,冷PBS洗涤2次,离心(2000转/分,5分钟),弃上清培养基,用冷PBS清洗细胞两次。用400μL缓冲液(1×)重新悬浮细胞(1×105个细胞/mL)。将5μL Annexin V-FITC添加到细胞悬浮液中,在4℃下培养15分钟。再将细胞轻轻地混合另一个染料PI(10μL)。收集细胞,进行流式细胞分析。数据分析使用CFLow Plus(Accuri Cytometers)进行。
图15为Compound 27治疗后胶质瘤U87细胞重编程代谢途径的正常化。其中,a、Compound 27和空白对照处理的U87细胞聚集代谢产物的相对差异热图,n=5;b、定量分析U87细胞在糖酵解和TCA循环中的代谢组学变化。统计显著性采用t检验。*:P<0.05;**:P<0.01;***:P<0.005。c、Compound 27抑制后差异糖酵解代谢产物表达的可视化。申请人观察到用HK2候选抑制剂(化合物27)处理的U87胶质瘤细胞中重编程代谢途径的变化,与PBS处理的对照组相比具有明显不同的代谢物簇表现(图15中a)。评估糖酵解途径中的第一个并且为限速酶的己糖激酶(癌细胞中的HK2),代谢组学分析显示了己糖激酶直接产物葡萄糖-6-磷酸的浓度是低于对照组的。甘油-3-磷酸、磷酸烯醇式丙酮酸和丙酮酸的降低表明,化合物27抑制了U87细胞的糖酵解,从而降低了肿瘤生长的基本能量储备。由于化合物27对HK2的抑制,U87的异常戊糖磷酸途径(PPP)也受到抑制。核糖骨架核苷酸合成的前体(α-D-核糖-5-磷酸)和关键辅因子(烟酰胺腺嘌呤二核苷酸磷酸,NADPH)均减少,从而通过肿瘤增殖所需的PPP DNA合成限制核糖供应。此外,先前的报道表明甘油酸-3-磷酸也是丝氨酸合成途径(SSP)中的一个重要代谢中间体。经化合物27处理后,U87细胞甘油酯-3-磷酸显著下降近两个数量级(P<0.005),表现出U87细胞存在从头合成丝氨酸和甘氨酸的不足。TCA循环中柠檬酸盐生成的阻断(p<0.0001)进一步抑制了U87细胞中FA的合成,导致脂质不足,不能满足肿瘤细胞活性的需要。另外,申请人发现经Compound27处理后,焦磷酸硫胺(TPP)浓度升高近2.5倍,而焦磷酸硫胺是通过调节丙酮酸脱氢酶(PDH)的活性将丙酮酸转化为乙酰辅酶a的关键辅酶,通过降低TCA的葡萄糖代谢流量,促进了U87细胞的凋亡。甘油醛-3-磷酸和α-D-核糖-5-磷酸是糖酵解途径中的中间代谢物,可发生可逆变化。实验表明,化合物27使戊糖磷酸途径正常化,减少了α-D-核糖-5-磷酸的产生,同时积累了甘油醛-3-磷酸(大约比PBS处理的对照组高3.5倍)。总之,这些数据揭示了由化合物 27诱导的U87细胞代谢途径正常化的重要变化。
为了进一步证实细胞凋亡的发生,申请人采用annexin V/碘化丙啶双染法检测暴露的磷脂酰丝氨酸,观察细胞膜损伤现象。参见图16,图16为流式细胞仪分析compd27诱发的U87细胞凋亡(Annexin V-FITC/PI染色),流式细胞仪观察到两个主要细胞群:与对照组相比,化合物27治疗组早期 (Annexin+/PI-)和晚期(Annexin+/PI+)凋亡细胞分别占31.2%和30.6%,而空白对照组中,U87损伤细胞的比例仅为2.06%和2.04%。这些结果表明化合物27的糖酵解抑制途径参与了胶质瘤细胞的凋亡。
由以上实施例可知,本发明提供了一种己糖激酶2抑制剂的筛选方法,包括以下步骤:将候选抑制剂和缓冲液混合,孵育,终止反应,得到反应后溶液;所述缓冲液中包括己糖激酶2和葡萄糖;将反应后溶液和等体积的葡萄糖-1-13C混匀,得到待分析物;将待分析物滴加至石墨结构型纳米材料基质表面,干燥后进行MALDI-MS检测,筛选,得到己糖激酶2抑制剂。该方法以石墨结构型纳米材料为基质,结合MALDI-MS检测,超快速的筛选检测(5.1小时内分析1836个样品);获得一系列高抑脑瘤生长活性的小分子药物;对接小分子药物药效分析,无需转移至其它检测平台。
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)
1.一种己糖激酶2抑制剂的筛选方法,包括以下步骤:
将候选抑制剂和缓冲液混合,孵育,终止反应,得到反应后溶液;所述缓冲液中包括己糖激酶2和葡萄糖;
将反应后溶液和等体积的葡萄糖-1-13C混匀,得到待分析物;
将待分析物滴加至石墨结构型纳米材料基质表面,干燥后进行MALDI-MS检测,筛选,得到己糖激酶2抑制剂;
所述候选抑制剂由以下方法获得:
在质子化状态参数为pH=7.0±2.0,范德华半径的标度因子设为1.0,最大部分原子电荷设为0.25模拟环境下,将所述初步目标化合物与HK2先采用Glide-SP模式对结合亲和力进行评分和排序,再对得到排名靠前的50000个化合物采用GlideXP对接模式评分,随后采用ACD/ADME软件包预测所选化合物的ADMET性质,对Glide XP对接的1000个排名靠前的化合物进行过滤,去除那些不符合以下规则的化合物:(1)pH=7.0,logP/logD<5.5;(2)违反Lipinski的五规则<2;(3)违反Opera的药物相似性规则<3;(4)功能官能团没有毒性、反应性或REOS规则定义的其他不良部分;
最后采用Discovery Studio 2.5中的Find Diversity Molecule模块,根据FCFP_4指纹计算出的Tanimoto距离对其余分子进行聚类,得到候选抑制剂。
2.根据权利要求1所述的筛选方法,其特征在于,所述筛选的条件为:
候选抑制剂水溶液浓度为20μmol/L,己糖激酶2活性的抑制率≥25%;
抑制率=(1-B/A)×100%;
所述A为未加抑制剂的反应前溶液中葡萄糖浓度-未加抑制剂的反应后溶液中葡萄糖浓度;
所述B为加抑制剂的反应前溶液中葡萄糖浓度-加抑制剂的反应后溶液中葡萄糖浓度;
反应溶液中葡萄糖浓度=([葡萄糖+Na]+的质谱信号强度/[葡萄糖-1-13C+Na]+的质谱信号强度)×已知葡萄糖-1-13C浓度。
3.根据权利要求1所述的筛选方法,其特征在于,所述候选抑制剂和缓冲液的体积比为1:1;
所述缓冲液中己糖激酶2的质量和葡萄糖的物质的量比为(0.245~0.255)g:0.5mmol;
所述候选抑制剂的浓度为1μmol/L~1000μmol/L;
所述孵育的温度为35~40℃,孵育的时间为55~65min。
4.根据权利要求1所述的筛选方法,其特征在于,所述MALDI-MS检测采用反射正负离子模式;
MALDI-MS检测的实验参数:
355nm的Nd:YAG激光,激光能量为30%,对应于每脉冲57μJ,激光脉冲持续时间:3ns,激光光斑大小为50~100μm;
每个样本经4次重复测试;每一种质谱累积3000个激光光斑。
5.根据权利要求1所述的筛选方法,其特征在于,所述石墨结构型纳米材料基质含有羟基、羰基和环氧基三种官能团。
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