CN116650484A - 一种乳腺癌相关蛋白的抑制剂及其应用 - Google Patents
一种乳腺癌相关蛋白的抑制剂及其应用 Download PDFInfo
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Abstract
本发明公开了一种乳腺癌相关蛋白的抑制剂及其应用，所述乳腺癌相关蛋白为PARP1、CDK2和PI3Kα，所述抑制剂为雷洛昔芬和氟维司群；其中，雷洛昔芬为PARP1和PI3Kα的抑制剂，氟维司群为CDK2的抑制剂。本发明充分应用分子对接技术分析结合相互作用，并关联氟维司群和雷洛昔芬对三种乳腺癌标靶受体5HA9、6GUE和7K6O的结合亲和力，发现雷洛昔芬是PARP1和PI3Kα最有效的抑制剂，氟维司群是CDK2最有效的抑制剂。最后采用分子动力学方法测定了5HA9‑雷洛昔芬、6GUE‑氟维司群和7K6O‑雷洛昔芬的稳定性。这一结果有助于发现治疗乳腺癌的新药。
Description
技术领域
本发明属于医药技术领域，具体涉及一种乳腺癌相关蛋白的抑制剂及其应用。
背景技术
乳腺癌是目前全球常见的危及生命的健康问题之一。在不同亚型乳腺癌中，三阴性乳腺癌(TNBC)、人类表皮生长因子受体-2(HER2)阳性和激素受体阳性(HR+)乳腺癌是特别值得关注的，因为它们是基于激素和生长因子受体产生的。尽管存活率有所提高，但乳腺癌仍然是第五大常见的癌症死亡原因。由于易感基因突变，近5％～10％的乳腺癌患者直接表现有遗传性综合征。高达10％的乳腺癌患者有遗传性DNA突变，这可能导致与DNA修复和细胞周期检查点刺激相关的基因功能丧失。其余约90％的病例是通过获得性遗传变异和表观遗传变异引发的。尽管癌症诊断和治疗取得了进展，但乳腺癌是女性最致命的疾病之一，并且仍然是世界各地女性死亡的主要原因。目前，聚(ADP-核糖)聚合酶1(PARP1)、周期蛋白依赖型激酶2(CDK2)和磷脂酰肌醇3-激酶(PI3K)被认为是乳腺癌治疗的潜在靶点。
PARP1在分析DNA损伤的影响中发挥着至关重要的作用，并且是与抗癌药物研发中临床抑制剂相关的潜在靶标。有研究描述PARP1是DNA损伤反应(DDR)的重要组成部分，有助于理解和修复DNA损伤，可表现为单链DNA断裂(SSB)或双链DNA断裂(DSB)以控制细胞基因组的稳定性。一些研究人员分析并使用PARP1抑制剂作为具有发展前景的乳腺癌治疗方法。
CDKs调节因子因其在细胞分裂中的重要功能而受到广泛关注。CDK2可引发细胞周期中S期和M期细胞的进化，是调控细胞周期的重要调节因子，能特别调控G1/S和S/G2时相转换和肿瘤发生。CDK2过表达为调节异常细胞周期提供了原理依据，据报道，这与几种癌细胞的过度增殖直接相关。靶向CDK2可能是减少癌细胞进展的潜在治疗方法，它能推进细胞周期进程，并在真核细胞周期进程、DNA损伤和DNA修复反应等各种生理学过程中发挥作用。Patel等人发现抑制CDK2和CDK4促进了乳腺癌细胞的重要反应。
PI3K作为脂质激酶家族的一种，有助于乳腺癌的临床治疗，而且对细胞存活、增殖及迁移等各种生物学功能至关重要。PI3K有三类，其中I类包括PI3Kα、β、γ和δ，有研究显示在40％乳腺癌患者中观察到PI3Kα的过表达。I类PI3K是PI3K的有效亚型之一，可催化磷脂酰肌醇二磷酸(PIP2)向磷脂酰肌醇三磷酸(PIP3)的转变，从而启动质膜上含Pleckstrin同源结构域的各种蛋白质的合成。在一些肿瘤中PI3K通路失调等其它功能引起了人们的关注。通过PIK3CA基因变异，可以找到刺激PI3K信号通路的相关路径。近年来，PI3Kα抑制剂被应用于晚期乳腺癌患者临床治疗，为治疗药物研发获得了良好的疗效反馈。因此，抑制PI3Kα是治疗乳腺癌的一种方法。
目前可用的有效乳腺癌治疗药物出现了不良反应，这可能是人们发现乳腺癌特异性药物对患者无效的原因。因此亟待探寻新的乳腺癌相关蛋白抑制剂。
发明内容
针对现有技术的不足，本发明提供一种乳腺癌相关蛋白的抑制剂及其应用，
本发明是通过以下技术方案实现的：
一种乳腺癌相关蛋白的抑制剂，所述乳腺癌相关蛋白为PARP1、CDK2和PI3Kα，所述抑制剂为雷洛昔芬和氟维司群；其中，雷洛昔芬为PARP1和PI3Kα的抑制剂，氟维司群为CDK2的抑制剂。
雷洛昔芬作为PARP1抑制剂在制备预防或治疗乳腺癌药物中的应用。
雷洛昔芬作为PI3Kα抑制剂在制备预防或治疗乳腺癌药物中的应用。
氟维司群作为CDK2抑制剂在制备预防或治疗乳腺癌药物中的应用。
一种预防或治疗乳腺癌药物，包括雷洛昔芬和/或氟维司群，以及药学上可接受的载体。
优选地，所述药物为片剂、胶囊剂、口服液、颗粒剂、丸剂或注射剂。
本发明的有益效果如下：
本发明充分应用分子对接技术分析结合相互作用，并关联巴多昔芬、依西美坦、氟维司群、雷洛昔芬、胰凝乳蛋白酶A和伏立诺他对三种乳腺癌标靶受体5HA9、6GUE和7K6O的结合亲和力，并得出结论：雷洛昔芬是PARP1和PI3Kα最有效的抑制剂，氟维司群是CDK2最有效的抑制剂。最后，采用分子动力学方法测定了5HA9-雷洛昔芬、6GUE-氟维司群和7K6O-雷洛昔芬的稳定性。这一结果有助于为乳腺癌治疗中先导化合物优化识别潜在有效的化合物，并有助于发现治疗乳腺癌的新药。
附图说明
图1为实施例1中氟维司群在5HA9蛋白靶标活性位点的最佳位置(A)及具有最高生物活性的5HA9蛋白靶标和氟维司群之间分子相互作用的二维图(B)；
图2为实施例1中雷洛昔芬在5HA9蛋白靶标活性位点的最佳位置(A)及具有最高生物活性的5HA9蛋白靶标和雷洛昔芬之间分子相互作用的二维图(B)；
图3为实施例1中氟维司群在6GUE蛋白靶标活性位点的最佳位置(A)及具有最高生物活性的6GUE蛋白靶标和氟维司群之间分子相互作用的二维图(B)；
图4为实施例1中雷洛昔芬在6GUE蛋白靶标活性位点的最佳位置(A)及具有最高生物活性的6GUE蛋白靶标和雷洛昔芬之间分子相互作用的二维图(B)；
图5为实施例1中氟维司群在7K6O蛋白靶标活性位点的最佳位置(A)及具有最高生物活性的7K6O蛋白靶标和氟维司群之间分子相互作用的二维图(B)；
图6为实施例1中雷洛昔芬在7K6O蛋白靶标活性位点的最佳位置(A)及具有最高生物活性的7K6O蛋白靶标和雷洛昔芬之间分子相互作用的二维图(B)；
图7为实施例2中5HA9-雷洛昔芬复合物(A)、6GUE-氟维司群复合物(B)和7K6O-雷洛昔芬复合物(C)的均方根偏差(RMSD)；
图8为实施例2中5HA9-雷洛昔芬复合物(A)、6GUE-氟维司群复合物(B)和7K6O-雷洛昔芬复合物(C)的均方根波动(RMSF)分析；
图9为实施例2中进行1000ps的分子动力学模拟期间5HA9-雷洛昔芬复合物(A)、6GUE-氟维司群复合物(B)和7K6O-雷洛昔芬复合物(C)中的氢键数；
图10为实施例2中5HA9-雷洛昔芬复合物(A)、6GUE-氟维司群复合物(B)和7K6O-雷洛昔芬复合物(C)的回转半径值；
图11为实施例2中5HA9-雷洛昔芬复合物(A)、6GUE-氟维司群复合物(B)和7K6O-雷洛昔芬复合物(C)的势能分析。
具体实施方式
下面结合附图与具体实施例对本发明做进一步详细说明。
以下实施例中所用蛋白质和配体：
与乳腺癌相关的蛋白质结构均获取于蛋白质结构数据库(RCSB Protein DataBank，https://www.rcsb.org)，包括：PARP1(PDB编号：5HA9，分辨率：)、CDK2/细胞周期期蛋白A+AZD5438复合物(PDB编号：6GUE，分辨率：/> )及PI3Kα抑制剂10-5429晶体结构(PDB编号：7K6O，分辨率：/>)。
所用配体化合物为巴多昔芬、依西美坦、氟维司群、雷洛昔芬、胰凝乳蛋白酶A和伏立诺他，结构信息来自PubChem数据库和Molinspiration。用普适型力场融合并调整电荷，以使配体适应对接技术。从PubChem数据库中获得了结构数据文件(SDF)类型化合物的三维构象，并通过Open Babel软件转换为PDB格式。借助于AutoDock工具1.5.7将受体和化合物的晶体结构转化为PDBQT型，是通过AutoDock Vina(https://vina.scripps.edu/)进行分子对接的基本步骤。
实施例1分子对接研究
1、实验步骤
分子对接是一种有效的计算工具，用于评估在原子水平上配体与标靶蛋白之间的关联，这在发现乳腺癌治疗抗癌作用方面很有效。本实施例利用CASTp服务器(http://sts.bioengr.uic.edu/castp)对所研究蛋白质(5HA9、6GUE、7K6O)的活性位点残基进行鉴定，如表1所示。
表1本实施例所研究蛋白质活性位点残基的预测
通过研究利用反向分子对接模型来寻找乳腺癌治疗的潜在蛋白质靶点，以设计新药。在本实施例的研究中，应用对接技术来阐明配体与相应标靶蛋白活性位点之间的关联。多次重复测试，采用具有最佳结合亲和力(千卡/摩尔)的蛋白质-配体化合物。
在转变为PDBQT型之前，在受体中添加极性氢和科尔曼(Kollman)电荷，并去除水分子，选择配体可扭转的键。5HA9蛋白的网格大小固定在X：-4.097、Y：10.995和Z：-21.410，间距为中心位于X：/>Y：/>和Z：/>6GUE蛋白的网格大小固定在X：-29.878、Y：-7.266和Z：18.174，间距为/>中心位于X：/>Y：/>和Z：/>7K6O蛋白的网格大小固定在X：3.114、Y：3.733和Z：20.033，间距为/>中心位于X：/>Y：/>和Z：/>在设置参数exhaustiveness为8及energy range为4的情况下进行对接。其他选项仍设为默认值。实施对接技术后，评估了9个结合位姿以及以“千卡/摩尔”为单位的结合亲和力。源自最低结合亲和力的对接位姿，这也显示最低均方根偏差(RMSD)，旨在应用于实现最精确的预测。应用AutoDock Vina评估受体和化合物之间对接位姿及其结合亲和力，并对其进行分层，并应用PyMOL分子图形系统(2.5.2版)观察配体-蛋白质结合位姿。采用BIOVIA DiscoveryStudio 2021版分析对接结果。用于检测蛋白质-配体相互作用的二维模型以及分子间关联(如氢键和疏水相互作用的效力)。
2、分子对接建模
由于氢键和疏水相互作用，配体结构具有潜在的有效性。研究表明对5HA9结合亲和力最低的最好配体分别为雷洛昔芬、氟维司群、依西美坦、巴多昔芬、胰凝乳蛋白酶A和伏立诺他，其相应分值分别为：-12.3千卡/摩尔、-11.9千卡/摩尔、-11.1千卡/摩尔、-11千卡/摩尔、-10千卡/摩尔和-9千卡/摩尔。氟维司群和雷洛昔芬在5HA9受体活性位点残基中的结合亲和力(千卡/摩尔)的图形描述分别如图1、2所示。化合物雷洛昔芬的结合亲和力最小，与Glu102形成结构碳氢键，与His201形成常规氢键(图2中A和B)。本实施例观察到巴多昔芬具有与药物依西美坦几乎相关的结合亲和力分值。化合物和受体之间的结合亲和力、氢键和疏水相互作用如表2所示。
表2化合物和受体之间分子对接结果
如图3所示，氟维司群与蛋白质包中氨基酸残基(Ser0，Thr72，Arg241)三个氢键具有-10.2千卡/摩尔的结合亲和力，三个氢键的键长分别为 和/>而依西美坦与6GUE蛋白三个氢键的结合亲和力为-7.3千卡/摩尔。本实施例发现Lys300和Ala303残基与氟维司群和6GUE蛋白之间的疏水相互作用相关(图3)，另一方面，没有残基被鉴定出与依西美坦和6GUE蛋白之间的疏水相互作用相关。Ser0和Thr72残基在这些分子和6GUE蛋白之间的氢键相互作用中很常见。氟维司群与6GUE蛋白的结合亲和力最小，并表现出强氢键，被证明是6GUE蛋白抑制剂的重要候选药物。此外，目前的对接研究显示雷洛昔芬(图4)和巴多昔芬有更紧密的结合亲和力。这些分子对6GUE蛋白的结合亲和力分别为-9.5和-9.3千卡/摩尔。雷洛昔芬与6GUE蛋白结合包中残基Val69/> 和Asp68/>的氢键相互作用如图4所示。巴多昔芬与6GUE蛋白相互作用，在Asn73/>和Ser0/>残基之间形成两个氢键。胰凝乳蛋白酶A具有2个氢键Ser0/>和Asn73/>氨基酸残基，结合亲和力为-8.7千卡/摩尔，相较而言，伏立诺他具有3个氢键His296/>His71和Ser0/>氨基酸残基，结合亲和力为-7.7千卡/摩尔。
在7K6O蛋白中，结合亲和力最高的的顶级化合物是雷洛昔芬(图6)和巴多昔芬。在本次研究分析中，雷洛昔芬与一个常规氢键(Asn170)和一个碳氢键(Arg662)具有-10.6千卡/摩尔的高结合亲和力，显示了高程度的对接验证(图6)。结果显示巴多昔芬与两种常规氢键(Arg662和Asn170)的结合亲和力为-9.9千卡/摩尔，有四种疏水相互作用(Phe666、Arg662、Pro757和Ala758)。在7K6O蛋白中，胰凝乳蛋白酶A与残基Phe666Lys271Leu755/>Leu839/>Phe666/>His670/>和His759 之间展现了更多的疏水相互作用。计算研究表明，其他化合物对氟维司群(图5)、胰凝乳蛋白酶A、依西美坦和伏立诺他分别具有-9.7、-8.9、-8.8和-8.4千卡/摩尔的结合亲和力。此外，蛋白质包中蛋白质-配体相互作用表明伏立诺他在Arg662、Arg818和Gly837氨基酸残基之间形成三个氢键。发现显著的氨基酸残基Phe666分别与巴多昔芬、依西美坦、胰凝乳蛋白酶A和伏立诺他发生疏水相互作用，这对与7K6O结合至关重要。
本实施例结果表明，有几种化合物在抑制乳腺癌基因中发挥着关键作用。已发现雷洛昔芬和氟维司群是主要的先导分子，可能是5HA9、6GUE和7K6O的有效抑制剂。
实施例2分子动力学模拟
1、实验步骤
使用GROMACS 2022.3charmm27力场参数分析了5HA9、6GUE和7K6O蛋白分别与雷洛昔芬和氟维司群相互作用的分子动力学，以表征原子间的相互作用。从SwissParam服务器(https://swissparam.ch)提取拓扑文件和CHARMM参数文件。蛋白质-配体复合物的结构获取于对接的结果。使用UCSF Chimera的Dunbrack Rotamers收集不完整的侧链，并使用Antechamber计算电荷。利用TIP3P水模型进行模拟。使用V-rescale(改进型Berendsen恒温器)设置NVT温度为300K(通过Maxwell-Boltzmann分布选取)，并使用Berendsen算法在1个大气压下平衡用于NPT平衡的蛋白质-配体复合物。进行各1000ps的两个平衡步骤。持续进行了1000ps的分子动力学模拟，这些轨迹用来分析均方根偏差(RMSD)、均方根波动(RMSF)、回转半径、氢键数和相互作用能等。
2、分子动力学模拟结果
(1)RMSD
与雷洛昔芬和氟维司群结合的5HA9、6GUE和7K6O的RMSD特性如图7所示。与氟维司群相比，雷洛昔芬与5HA9和7K6O相互作用表现了较低的RMSD及更高的稳定性。测得5HA9-雷洛昔芬、6GUE-氟维司群和7K6O-雷洛昔芬的平均RMSD分别为0.151、0.280和0.173。
(2)RMSF
在分子动力学模拟中，RMSF用于检测骨架原子的平均原子动力学。验证每个骨架原子的平均位置波动以计算RMSF。配体的RMSF值越低，复合物越稳定，而配体的RMSF值越高，复合物越灵活。三者中，5HA9-雷洛昔芬复合物的平均波动较低，与6GUE-氟维司群和7K6O-雷洛昔芬相比更稳定(图8)。RMSF结果表明，5HA9-雷洛昔芬复合物表现了更高的稳定性。
(3)氢键分析
在1000ps的分子动力学模拟过程中观察到5HA9-雷洛昔芬、6GUE-氟维司群和7K6O-雷洛昔芬之间的氢键如图9所示。结果表明，5HA9-雷洛昔芬和7K6O-雷洛昔芬在分子动力学模拟过程中维持了1-3个氢键。由此可以得出结论，雷洛昔芬与5HA9和7K6O结合的稳定性更高。
(4)回转半径
如图10所示，回转半径表现为刚体对齐，其对具有高构象变异的结构子集高度敏感。它代表蛋白质的紧凑性。回转半径值越小，蛋白质的紧凑性越高。结果表明，5HA9-雷洛昔芬和7K6O-雷洛昔芬比6GUE-氟维司群更紧凑。
(5)相互作用能分析
如表3所示，6GUE-氟维司群的平均键能(14422.4)和动能(341242)高于7K6O-雷洛昔芬的平均键能(11255.5)和动能(307210)及5HA9-雷洛昔芬的平均键能(8786.95)和动能(262331)。与6GUE-氟维司群和7K6O-雷洛昔芬相比，5HA9-雷洛昔芬显示了较低的势能面(图11)。
表3三种复合物的能量相互作用概况
本发明充分应用分子对接技术分析结合相互作用，并关联巴多昔芬、依西美坦、氟维司群、雷洛昔芬、胰凝乳蛋白酶A和伏立诺他对三种乳腺癌标靶受体5HA9、6GUE和7K6O的结合亲和力。本发明得出的结论是：雷洛昔芬和氟维司群可能是5HA9、6GUE和7K6O的有效抑制剂，其中，雷洛昔芬是PARP1和PI3Kα最有效的抑制剂，氟维司群是CDK2最有效的抑制剂。最后，采用分子动力学方法测定了5HA9-雷洛昔芬、6GUE-氟维司群和7K6O-雷洛昔芬的稳定性。这一结果有助于为乳腺癌治疗中先导化合物优化识别潜在有效的化合物，并有助于发现治疗乳腺癌的新药。
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何不经过创造性劳动想到的变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应该以权利要求书所限定的保护范围为准。
Claims (6)
1.一种乳腺癌相关蛋白的抑制剂，其特征在于，所述乳腺癌相关蛋白为PARP1、CDK2和PI3Kα，所述抑制剂为雷洛昔芬和氟维司群；其中，雷洛昔芬为PARP1和PI3Kα的抑制剂，氟维司群为CDK2的抑制剂。
2.雷洛昔芬作为PARP1抑制剂在制备预防或治疗乳腺癌药物中的应用。
3.雷洛昔芬作为PI3Kα抑制剂在制备预防或治疗乳腺癌药物中的应用。
4.氟维司群作为CDK2抑制剂在制备预防或治疗乳腺癌药物中的应用。
5.一种预防或治疗乳腺癌药物，其特征在于，包括雷洛昔芬和/或氟维司群，以及药学上可接受的载体。
6.根据权利要求5所述的一种预防或治疗乳腺癌药物，其特征在于，所述药物为片剂、胶囊剂、口服液、颗粒剂、丸剂或注射剂。
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