肿瘤坏死因子-α小分子抑制剂的设计、筛选及初步活性测定

目的结合计算机虚拟筛选和实物活性筛选,寻找新的TNF-α的小分子抑制剂,并完成对其生物学活性的测定。方法基于TNF-α受体蛋白的晶体结构和计算机辅助设计,用docking方法对含有约9万个小分子三维数据库进行筛选;选择对接结果较好的50个化合物进行初步的抑制TNF-α细胞毒活性实验;MTT法进一步分析筛选出的小分子化合物的细胞毒性,以及其在不同剂量时抑制TNF-α对L929细胞毒性的作用;采用AnnexinV-FITC检测上述小分子对TNF-α诱导的细胞凋亡的抑制作用。结果确定受体p55蛋白第二结构域的第二loop环中7肽(RKEMGQV)作为docking的配体模板;经计算机虚拟筛选后得到965种结构相似的化合物,综合分析后最终选择并购买了50个代表性化合物做进一步生活性测定;活性筛选结果显示有3个小分子化合物(C-12、C-34、C-35)能抑制TNF-α的细胞毒活性;对其中抑制活性较好的C-12进行了深入研究的结果表明:该化合物具有较低的细胞毒性和较强的抑制TNF-α(1μg.L-1)对L929细胞毒性的作用,表现为剂量依赖性,半数抑制浓度(IC50)为10μmol.L-1;该化合物能抑制TNF-α诱导的L929细胞凋亡,并呈剂量依赖性。结论通过计算机虚拟筛选并结合生物活性分析,筛选到一种能直接靶向TNF-α,并能中和TNF-α的细胞毒活性的全新的先导化合物。     

新型CDK9小分子抑制剂的设计和发现

目的通过同源模建、计算机虚拟筛选和生物活性筛选,寻找新型的CDK9小分子抑制剂。方法采用同源模建方法得到CDK9的三维晶体构象,用DOCK(分子对接)对小分子三维数据库进行虚拟筛选。采用MTT法对挑选出的化合物进行生物活性测定,然后挑选高活性的化合物进行CDK9与小分子之间相互作用的研究,验证化合物对CDK9激酶活性的抑制作用。结果用DOCK程序对三维化合物库虚拟筛选后挑选出得分高的前1000个化合物,按结构差异化分类,最终选择并购买了27个代表性化合物进行进一步生物学活性测定。27个化合物中12个化合物明显抑制肿瘤细胞的增殖,其中1个化合物C-21的半数抑制浓度(IC50)在20μmol.L-1以下。选择C-21类化合物进一步进行研究,结果显示此化合物能够有效抑制各类肿瘤细胞系的增殖。酶学水平研究表明此类化合物能够有效抑制CDK9激酶活性,并在较低浓度范围内呈明显的剂量依赖关系。结论通过同源模建、计算机虚拟筛选、生物活性实验和分子水平研究,得到了一类靶向CDK9的全新的先导化合物。     

基于虚拟筛选和分子动力学模拟的PD-1/PD-L1小分子抑制剂的发现

目的 发现具有新型结构的PD-1/PD-L1小分子抑制剂，并测试其对PD-1/PD-L1蛋白的阻断活性，为后续相关研究提供参考。方法 利用AutoDock Vina对TCM和TargetMol两种天然产物分子库进行虚拟筛选，获得打分较高的分子，采用HTRF方法测试所得化合物的体外抑制活性，并通过分子动力学模拟对其稳定性和结合模式进行分析。结果与结论最终确定了一种能够与PD-L1相互作用的新型化合物754792,并证明其可以有效阻断PD-1/PD-L1与配体的结合。该研究为开发免疫检查点抑制剂提供了重要的理论依据，为进一步开发高效的PD-1/PD-L1小分子抑制剂奠定了基础。     

益气滋阴饮治疗2型糖尿病活性成分的虚拟筛选研究

目的:对中药方剂益气滋阴饮治疗2型糖尿病的活性成分、作用靶标和途径进行虚拟筛选研究,从分子水平上阐述该方治疗2型糖尿病的药效机制,为其推广应用和合理组方提供理论依据。方法:从《中药原植物化学成分手册》中检索出益气滋阴饮方剂10味药材中已分离得到的化学成分,从DrugBank数据库中检索出治疗2型糖尿病的药物/类药分子,在PubChem Compound数据库中下载各成分的三维分子结构,在Cerius~2 4.10软件中对其进行结构优化,建立益气滋阴饮小分子化合物数据集;以"type 2diabetes mellitus"为关键词,在治疗靶蛋白数据库中搜索及筛选出2型糖尿病的靶标蛋白,然后从治疗靶蛋白数据库中查询并下载这些蛋白质的三维立体结构;将选出的化合物分子(配体)与靶标蛋白(受体)进行对接,找出活性较高(根据Degree值与Betweenness值大小排序)的小分子和相关度较高的靶标蛋白;以筛选出的小分子化合物与靶标蛋白(如N-反式-咖啡酰酪胺分子与糖原合成酶激酶-3β)的精细对接为例,讨论配体与受体间的相互作用机制。结果:检索得到化学成分及药物/类药分子分别为732、127个,筛选出2型糖尿病的靶标蛋白30个;根据Degree值与Betweenness值大小排序,筛选出了8个活性较高的小分子化合物(如N-反式-咖啡酰酪胺、金丝桃苷等)和10个相关度较高的靶标蛋白(如碳酸酐酶1、糖原合成酶激酶-3β等);N-反式-咖啡酰酪胺与糖原合成酶激酶-3β之间可形成氢键及π烷基化相互作用,从而影响受体蛋白的结构稳定性及活性而产生降低血糖作用。结论:采用虚拟筛选研究发现,益气滋阴饮治疗2型糖尿病时既存在一个小分子化合物与多个靶标相互作用,同时又有不同小分子化合物作用于同一靶标的现象,从分子水平上揭示了其通过多组分、多靶标协同作用的机制,为开发治疗糖尿病的新药时先导化合物的筛选和结构修饰提供了参考信息。     

基于计算机虚拟筛选技术寻找NDM-1抑制剂

β-内酰胺类抗生素的广泛使用,使得越来越多的细菌产生由β-内酰胺酶介导的耐药性,针对丝氨酸β-内酰胺酶,目前已有克拉维酸、舒巴坦等抑制剂与临床常用抗生素配伍使用,但尚无金属β-内酰胺酶的有效抑制剂,因此,寻找金属β-内酰胺酶尤其是目前最受瞩目的新德里金属β-内酰胺酶-1[NDM-1(B1类)]的抑制剂是遏制"超级细菌"引起的感染最迫切的要求。虚拟筛选作为发现新的先导化合物、寻找新药物的有力手段,大大缩小了人工进行配体活性筛选研究范围。我们通过计算机虚拟筛选技术,利用Discovery Studio 2.5和GOLD 3.0平台,基于NDM-1晶体结构(PDB:3Q6X),从一个含有2059个天然产物分子的化合物库里筛选得到6个可能具有金属β-内酰胺酶NDM-1(B1类)抑制活性的化合物结构。     

芳香环并咪唑环类凋亡抑制蛋白抑制剂的设计、合成与抗肿瘤活性评价

目的设计并合成新的小分子凋亡抑制蛋白抑制剂。方法运用计算机辅助药物设计模拟靶蛋白与目标分子的结合作用,设计并合成新结构的化合物,以紫杉醇作为阳性对照,进行与多个凋亡抑制蛋白的结合实验和多个细胞系的抗肿瘤细胞增殖抑制活性评价,并比较目标物对癌细胞的抑制率。结果合成两个系列共21个目标化合物,部分化合物表现出对多个凋亡抑制蛋白有强烈的抑制活性(纳摩尔级)和对多种肿瘤细胞的抑制能力,其中,ⅡA-1活性最为突出,对XIAP L-BIR2-BIR3抑制作用的IC50值为77.2 nmol·L-1;对乳腺癌细胞系MDA-MB-231的抑制率为70.9%,相同条件下紫杉醇的抑制率仅为38.5%。结论合成的部分化合物有较好的活性,将为今后此类凋亡抑制蛋白抑制剂的研究奠定基础。     

基于分子对接、定量构效关系和分子动力学研究筛选小分子SIRT1抑制剂

为了寻找和发现靶向SIRT1的治疗AML的新型先导化合物,本研究利用分子对接与MM-GBSA结合自由能计算进行虚拟筛选,从231511个天然小分子类药分子库中筛选出8个潜在的SIRT1抑制剂,通过对已有的SIRT1抑制剂分子作为训练集和测试集进行QSAR建模,对筛选出的潜在SIRT1抑制剂分子进行活性预测,随后进行分子动力学模拟验证这些潜在抑制剂与SIRT1蛋白的结合模式与稳定性,最后通过OCI-AML2、OCI-AML3和MV4-11三种AML细胞增殖实验和SIRT1酶活性验证了这些分子的生物活性,发现其中5个分子对3种AML细胞具有不同程度的抑制作用,其中活性最强的化合物ZINC000001774455对AML细胞OCI-AML2的IC50达到2.29±0.09μmol·L^-1μmol·L^-1浓度下对SIRT1抑制率为65.33%,可作为SIRT1抑制剂先导化合物进行结构修饰,为开发新的AML治疗药物奠定了前期基础。     

自噬相关蛋白ATG4B抑制剂的虚拟筛选及体外活性测定

目的通过计算机虚拟筛选和体外活性测定,筛选自噬相关蛋白ATG4B的特异性小分子抑制剂。方法基于ATG4B蛋白的晶体结构(PDB ID:2CY7)找出合适的对接口袋;用分子对接方法对SPECS数据库20万化合物进行虚拟筛选并确定候选化合物;用荧光共振能量转移方法(FRET)检测候选化合物对ATG4B的体外抑制活性并对其特异性进行验证。结果确定受体蛋白2CY7的site 5为最适的对接口袋;分子对接后经综合分析选择并购买30个代表性化合物做进一步活性测定。活性测定结果显示,AG-690/10400046能有效抑制ATG4B蛋白的活性,而对半胱氨酸蛋白酶家族的另一成员caspase-3无酶切抑制作用。结论建立了一种ATG4B蛋白抑制剂的虚拟筛选方法。筛选得到的化合物AG-690/10400046具有明显的体外抑制活性,为后续ATG4B抑制剂的生理功能研究奠定基础。     

基于FAK的药物筛选及海洋小分子CY308抗乳腺癌研究

目的 从已知化合物中挖掘出新型的对FAK具有较强作用的化合物,并进行了药理活性的体外初筛,以期得到效果更好、选择性更高的FAK抑制剂。方法 首先采用Autodock vina从SPECS数据库进行FAK小分子抑制剂的计算机虚拟筛选,再通过rdkit操作环境进行类药5原则筛选后,采用Ward方法对化合物进行分层聚类,然后选出6类得分最高的化合物进行FAK抑制活性检测和进一步的实验验证。 结果 计算机辅助药物虚拟筛选得到的6个代表化合物在MDA-MB-231-FAKWT细胞上均具有一定的FAK激酶抑制活性,其中以CY308的活性最优,IC50为6umol/L。并进一步利用SPR技术证实了活性化合物CY308与FAK有较强的结合,并采用分子对接对其结合位点进行了预测。     

热休克蛋白90(Hsp90)抑制剂荧光标记探针 化合物的设计合成

目的 寻找新型Hsp90抑制剂荧光标记探针化合物,用于建立高通量荧光偏振筛选模型。方法 选择高活性的小分子Hsp90抑制剂(化合物 1),以氟硼二吡咯为荧光标记物质,对小分子化合物进行标记,并进行荧光偏振测试窗口测定,确定正确的标记位置。结果与结论 设计合成了两个未见文献报道的全新探针化合物,化合物结构经IR、¹H-NMR、MS和HR-MS谱确证。初步测试结果表明,当Hsp90的浓度为50 nmol.L^-1时,探针-Ⅱ的测试窗口达到了96 mp,能初步满足筛选方法建立的要求,为进一步的优化筛选打下了一定的基础。     

Pharmacophore‐based virtual screening,molecular docking,molecular dynamics simulation,and biological evaluation for the discovery of novel BRD4 inhibitors

Bromodomain is a recognition module in the signal transduction of acetylated histone. BRD4, one of the bromodomain members, is emerging as an attractive therapeutic target for several types of cancer. Therefore, in this study, an attempt has been made to screen compounds from an integrated database containing 5.5 million compounds for BRD4 inhibitors using pharmacophore‐based virtual screening, molecular docking, and molecular dynamics simulations. As a result, two molecules of twelve hits were found to be active in bioactivity tests. Among the molecules, compound 5 exhibited potent anticancer activity, and the IC₅₀ values against human cancer cell lines MV4‐11, A375, and HeLa were 4.2, 7.1, and 11.6 μm , respectively. After that, colony formation assay, cell cycle, apoptosis analysis, wound‐healing migration assay, and Western blotting were carried out to learn the bioactivity of compound 5 .     

应用虚拟筛选方法寻找链阳霉素A乙酰转移酶抑制剂

维吉尼亚霉素乙酰转移酶D(VatD)通过灭活链阳霉素A而在链阳霉素耐药性的产生中起重要作用。本研究采用虚拟筛选技术寻找VatD的抑制剂,此VatD抑制剂可以和链阳霉素联合使用,从而提供新的治疗耐药菌感染的方法。作者首次应用基于结构的虚拟筛选方法(分子对接)从含300 000化合物的商业化数据库中筛选对抗VatD底物结合位点的化合物,从200个评分最高的化合物中选取26个测定对VatD酶活性的抑制作用。将构建的质粒pRSET B/vatD转染宿主细胞E.coli(TrxB)用于过表达,纯化的VatD对维吉尼亚霉素M1表现乙酰转移酶活性。26个化合物中有3个对VatD表现抑制作用,IC₅₀分别为168.6,91.0和55.2 μmol·L^-1。其他化合物在反应体系中不溶解和/或对酶活性的抑制作用很小(IC₅₀>200 μmol·L^-1)。本文首次设计VatD的小分子化合物抑制剂,发现了3个有活性的化合物,希望其可作为先导化合物进一步发展为新的对抗链阳霉素耐药性的药物。     

Identification of Dipeptidyl Peptidase IV Inhibitors: Virtual Screening,Synthesis and Biological Evaluation

Inhibition of dipeptidyl peptidase IV is an important approach for the treatment of type‐2 diabetes. In this study, we reported a multistage virtual screening workflow that integrated 3D pharmacophore models, structural consensus docking, and molecular mechanics/generalized Born surface area binding energy calculation to identify novel dipeptidyl peptidase IV inhibitors. After screening our in‐house database, two hit compounds, HWL‐405 and HWL‐892, having persistent high performance in all stages of virtual screening were identified. These two hit compounds together with several analogs were synthesized and evaluated for in vitro inhibition of dipeptidyl peptidase IV. The experimental data indicated that most designed compounds exhibited significant dipeptidyl peptidase IV inhibitory activity. Among them, compounds 35f displayed the greatest potency against dipeptidyl peptidase IV in vitro with the IC₅₀ value of 78 nm . In an oral glucose tolerance test in normal male Kunming mice, compound 35f reduced blood glucose excursion in a dose‐dependent manner.     

Design,synthesis and bioevaluation of isoflavone derivative as a novel CLR/RAMP1 antagonist

CGRP receptor (CLR) is a B class GPCR that functions only when combined with RAMPs. CLR/RAMP1 has been regarded as a promising target for migraine treatment, as its antagonists have been proved to be effective recently. In the present study we designed and synthesized small molecular antagonists against CLR/RAMP1, resulting in a novel type of structure with acceptable high potency. The molecules were designed via virtual screening. Afterwards, a series of modification were conducted on the hit compounds, resulting in compound 8 as the best scored compound in docking, which was further validated in vitro by cell-based functional assay.     

Pyrogallol, ROS generator inhibits As4.1 juxtaglomerular cells via cell cycle arrest of G2 phase and apoptosis

Pyrogallol as a catechin compound has been employed as an O(2)(*-) generator and often used to investigate the role of ROS in the biological system. Here, we investigated the in vitro effect of pyrogallol on cell growth, cell cycle and apoptosis in As4.1 juxtaglomerular cells. Dose-dependent inhibition of cell growth was observed with IC(50) of about 60 microM for 48 h using MTT assay. Pyrogallol (100 microM) did not alter intracellular H(2)O(2) level and catalase activity, but increased the intracellular O(2)(-) level and decreased SOD activity in As4.1 cells. DNA flow cytometric analysis indicated that 50 and 100 microM pyrogallol significantly increased G2 phase cells as compared with those of pyrogallol-untreated cells. Also, pyrogallol induced apoptosis as evidenced by flow cytometric detection of sub-G1 DNA content, annexin V binding assay and DAPI staining. This apoptosis process was accompanied with the loss of mitochondrial transmembrane potential (DeltaPsi(m)), Bcl-2 decrease, caspase-3 activation and PARP cleavage. Pan caspase inhibitor (Z-VAD) could significantly rescue As4.1 cells from pyrogallol-induced cell death. But, the inhibitors of caspase-3, caspase-8, and caspase-9 did not prevent apoptotic events in pyrogallol-treated As4.1 cells. Taken together, we have demonstrated that an ROS inducer, pyrogallol inhibits the growth of As4.1 JG cells via cell cycle arrest and apoptosis, and suggest that the compound exhibits an anti-proliferative efficacy on these cells.     

Molecular field technology applied to virtual screening and finding the bioactive conformation

Virtual screening is being applied to reduce the high-throughput screening bottleneck in many pharmaceutical companies and to reduce compound wastage. Cresset’s ligand-based virtual screening technology using molecular fields can facilitate rapid identification of novel chemotypes from biologically testing only 200 – 1000 compounds. Four molecular fields calculated using the interaction of different probe atoms with the ligand are sufficient to describe how a ligand binds to its protein. Compounds with similar fields to known active ligands are predicted to have a high probability of showing similar activity. As binding is related to field similarity, this property has been exploited further to predict the bioactive conformation of small sets of structurally diverse active ligands starting from the two-dimensional structures alone without knowledge of the target site structure.     

A Discovery Funnel for Nucleic Acid Binding Drug Candidates

Computational approaches are becoming increasingly popular for the discovery of drug candidates against a target of interest. Proteins have historically been the primary targets of many virtual screening efforts. While in silico screens targeting proteins has proven successful, other classes of targets, in particular DNA, remain largely unexplored using virtual screening methods. With the realization of the functional importance of many non-cannonical DNA structures such as G-quadruplexes, increased efforts are underway to discover new small molecules that can bind selectively to DNA structures. Here, we describe efforts to build an integrated in silico and in vitro platform for discovering compounds that may bind to a chosen DNA target. Millions of compounds are initially screened in silico for selective binding to a particular structure and ranked to identify several hundred best hits. An important element of our strategy is the inclusion of an array of possible competing structures in the in silico screen. The best hundred or so hits are validated experimentally for binding to the actual target structure by a high-throughput 96-well thermal denaturation assay to yield the top ten candidates. Finally, these most promising candidates are thoroughly characterized for binding to their DNA target by rigorous biophysical methods, including isothermal titration calorimetry, differential scanning calorimetry, spectroscopy and competition dialysis.This platform was validated using quadruplex DNA as a target and a newly discovered quadruplex binding compound with possible anti-cancer activity was discovered. Some considerations when embarking on virtual screening and in silico experiments are also discussed.