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1.
以80个作用方式相同, 分子结构特征不同的表皮生长因子受体酪氨酸激酶(EGFR TK)竞争性抑制剂为训练集, 利用计算机药物辅助软件Catalyst, 构建不同的药效团模型, 并结合酪氨酸激酶的作用位点等因素, 筛选出一个含有两个芳环中心, 一个疏水中心和一个阳离子基团的具有较好预测能力(RMS=0.438, Correl=0.908, Weight=1.52, Config=17.36)的药效团模型, 为设计和合成新型结构的EGFR TK抑制剂提供参考.  相似文献   

2.
γ-分泌酶抑制剂的药效团模型构建   总被引:1,自引:0,他引:1  
利用Catalyst软件系统, 选择具有较高体外抑制活性的苯并二氮(艹卓)类化合物作为训练集, 经计算机建模, 构象优化, 由Catalyst系统构建出药效团模型. 并结合γ-分泌酶的作用机制等因素, 筛选出一个含有一个芳环中心, 一个疏水中心和两个氢键受体的具有较好预测能力(RMS=0.366343, Correl=0.95535, Weight=1.17389, Config=18.8671)的药效团模型. 该模型的建立有助于设计及合成新型结构的γ-分泌酶抑制剂.  相似文献   

3.
选择20 个3,4-二氢-1(1H)-异喹啉酮类gpIIb/IIIa受体抑制剂作为训练集, 利用Catalyst软件包建立了gpIIb/IIIa受体抑制剂三维药效团模型. 探讨了药效团作用模式. 并通过建立的可靠性最佳的药效团模型(线性回归系数r=0.7715), 从中草药数据库中虚拟筛选了gpIIb/IIIa受体抑制剂, 通过实验活性测定得到了8个抑制ADP活化全血血小板聚集的IC50从40到100 μmol·L-1的化合物, 进一步证明了所建药效团模型的有效性.  相似文献   

4.
选择20个3,4-二氢-1(1H)-异喹啉酮类gpⅡb/Ⅲa受体抑制剂作为训练集,利用Catalyst软件包建立了gpⅡb/Ⅲa受体抑制剂三维药效团模型.探讨了药效团作用模式.并通过建立的可靠性最佳的药效团模型(线性回归系数r=0.7715),从中草药数据库中虚拟筛选了gpⅡb/Ⅲa受体抑制剂,通过实验活性测定得到了8个抑制ADP活化全血血小板聚集的IC50从40到100μmol·L-1的化合物,进一步证明了所建药效团模型的有效性.  相似文献   

5.
黄文海  胡纯琦  廖勇  盛荣  胡永洲 《化学学报》2008,66(16):1889-1897
选择活性跨越0.002至25 μmol•L-1的4类共25个β分泌酶抑制剂作为训练集, 使用Catalyst软件包构建出药效团模型, 并通过对药效团的有效性分析, 筛选得到的最佳模型(correlCorrel=0.969, Config=16.32, Δcost=62.422)由一个环芳香性、一个疏水中心、一个正电荷中心和一个氢键供体组成. 并用其它209个抑制剂组成测试集对模型进行验证, 结果表明该模型显示出较强的预测能力, 能够为进一步的数据库搜索, 寻找新型的β分泌酶抑制剂先导物提供依据.  相似文献   

6.
基于药效团模型的DHODH抑制剂构效关系研究   总被引:1,自引:0,他引:1  
利用药效团模型研究二氢乳清酸脱氢酶(Dihydroorotate dehydrogenase,DHODH)抑制剂的构效关系,为DHODH抑制剂的虚拟筛选提供新的方法.以31个具有DHODH抑制活性的化合物为训练集化合物,半数抑制浓度(IC50)范围为7~63000 nmol/L,利用Catalyst/HypoGen算法构建DHODH抑制剂药效团模型,通过对训练集化合物多个构象进行叠合,提取药效团特征及三维空间限制构建药效团模型.利用基于CatScramble的交叉验证方法及评价模型对已知活性化合物的活性预测能力,确定较优药效团模型.模型包含1个氢键受体、3个疏水中心,表征了受体配体相互作用时可能发生的氢键相互作用、疏水相互作用和π-π相互作用,4个药效特征在三维空间的排列概括了DHODH抑制剂产生活性的结构特点.所得较优模型对训练集化合物及测试集化合物的计算活性值与实验活性值的相关系数分别为0.8405和0.8788.利用药效团模型对来源于微生物的系列化合物进行虚拟筛选,筛选出59个预测活性较好的化合物,可作为进一步药物研发的候选化合物.  相似文献   

7.
为了研究黄酮类醛糖还原酶抑制剂的抑制机理, 选择了31个黄酮类化合物作为训练集, 使用Catalyst软件包构建了此类抑制剂的药效团模型. 并专门针对黄酮类化合物定制了氢键给体和受体模型, 效果优于使用Catalyst内预定义的模型. 最终的药效团模型由两个氢键给体和一个氢键受体组成, 对训练集具有较好预测能力(Correl=0.9013). 此外, 使用InsightII/Affinity对6个黄酮类化合物进行了分子对接研究. 综合药效团模型和分子对接研究的结果, 发现黄酮类化合物的抑制活性主要源于黄酮骨架上的C4’或C3’位的羟基与醛糖还原酶活性口袋中的TYR48、VAL47、GLN49和C7位的羟基与HIS110, TRP111所形成的两组氢键.  相似文献   

8.
秦芳  郭彦伸  文辉  杨光中 《化学学报》2009,67(19):2258-2268
近年来的研究表明, 去甲肾上腺素(NE)能系统和5-羟色胺(5-HT)能系统可能共同参与了抑郁症的发病机制. 采用Catalyst软件的Hypogen方法, 利用22个不同结构类型的5-HT重摄取抑制剂和19个不同结构类型和活性的NE重摄取抑制剂分别建立了5-HT药效团模型和NE药效团模型, 它们的相关系数分别为0.935, 0.844, 这表明所得到的模型能较好地表征重摄取抑制剂化合物的特征; 此外, 我们还选择了四种不同活性的预测集分别对所建立的药效团模型进行检验, 结果表明所建立的药效团模型具有较好的预测能力. 对这两个药效团模型进行了比较分析, 其结果可以为设计高活性的双重5-HT和NE重摄取抑制剂提供依据.  相似文献   

9.
基于24个目前已知的氧肟酸类组蛋白去乙酰化酶抑制剂,我们运用Catalyst软件建立了一个三维药效团模型。其中,最好的药效团模型1,包含了四个化学特征(一个氢键供体,一个芳环和两个疏水基),相关系数达到0.946,并由另外20个化合物进行了测试验证。我们第一次特征性描述了组蛋白去乙酰化酶的帽子(CAP)部分。我们的研究结果对于设计全新组蛋白去乙酰化酶抑制剂具有很好的指导作用。  相似文献   

10.
通过CATALYST软件包得到了两类HER2抑制的三维药效团模型。尽管亚苄基丙二腈化合物和3-取代吲哚啉-2-酮系列化合物具有完全不同的骨架结构,但得到的药效团却具有共同的特性,这表明当这两类抑制剂和受体发生相互作用时,采用了相似的结合模式。共同的药效团模型包括一个氢键受体,一个氢键给体,一个脂肪类疏水团以及一个芳香类疏水团。根据药效团模型,我们还进行了三维构效关系的研究,结果表明得到的药效团模型具有很好的预测能力(线性回归系数R≈0.96)。药效团模型对于研究酪氨酸激酶小分子抑制剂的结构与活性关系,以及评估和预测此类未知化合物活性具人重要的意义。  相似文献   

11.
The p53 protein, also called guardian of the genome, plays a critical role in the cell cycle regulation and apoptosis. This protein is frequently inactivated in several types of human cancer by abnormally high levels of its negative regulator, mouse double minute 2 (MDM2). As a result, restoration of p53 function by inhibiting p53-MDM2 protein–protein interaction has been pursued as a compelling strategy for cancer therapy. To date, a limited number of small-molecules have been reported as effective p53−MDM2 inhibitors. X-ray structures of MDM2 in complex with some ligands are available in Protein Data Bank and herein, these data have been exploited to efficiently identify new p53-MDM2 interaction antagonists through a hierarchical virtual screening strategy. For this purpose, the first step was aimed at compiling a focused library of 686,630 structurally suitable compounds, from PubChem database, similar to two known effective inhibitors, Nutlin-3a and DP222669. These compounds were subjected to the subsequent structure-based approaches (quantum polarized ligand docking and molecular dynamics simulation) to select potential compounds with highest binding affinity for MDM2 protein. Additionally, ligand binding energy, ADMET properties and PAINS analysis were also considered as filtering criteria for selecting the most promising drug-like molecules. On the basis of these analyses, three top-ranked hit molecules, CID_118439641, CID_60452010 and CID_3106907, were found to have acceptable pharmacokinetics properties along with superior in silico inhibitory ability towards the p53-MDM2 interaction compared to known inhibitors. Molecular docking and molecular dynamics results well confirmed the interactions of the final selected compounds with critical residues within p53 binding site on the MDM2 hydrophobic clefts with satisfactory thermodynamics stability. Consequently, the new final scaffolds identified by the presented computational approach could offer a set of guidelines for designing promising anti-cancer agents targeting p53-MDM2 interaction.  相似文献   

12.
In the past decade, the p53-MDM2 protein-protein interaction by small molecules has been confirmed as a successful strategy for cancer therapy. In our previous work, pyrrolo[3,4-c]pyrazol-6(1H)-ones were found to be potent p53-MDM2 inhibitors. Further optimization and structure-activity relationship studies were described in the present work. The result revealed that benzyl group on position N1 of imidazole and bromine on C4-phenyl of pyrrolidone showed higher inhibitory activities. In vitro antiproliferative assay demonstrated the potent p53-MDM2 inhibitor 5c with 4-fold selectivity for U2 OS and Saos-2 cells. These data indicated that 4,5-dihydropyrrolo[3,4-c]pyrazol-6(1H)-one moiety is a valuable scaffold for further development of p53-MDM2 inhibitors.  相似文献   

13.
The p53-MDM2 interaction regulates p53-mediated cellular responses to DNA damage, and MDM2 is overexpressed in 7% of all cancers. Structure-based computational design was applied to this system to design libraries centered on a scaffold that projects side chain functionalities with distance and angular relationships equivalent to those seen in the MDM2 interacting motif of p53. A library of 173 such compounds was synthesized using solution phase parallel chemistry. The in vitro competitive ability of the compounds to block p53 peptide binding to MDM2 was determined using a fluorescence polarization competition assay. The most active compound bound with K(d) = 12 microM, and its binding was characterized by (15)N-(1)H HSQC NMR.  相似文献   

14.
Five nonpeptide, small-molecule inhibitors of the human MDM2-p53 interaction are presented, and each inhibitor represents a new scaffold. The most potent compound exhibited a Ki of 110 +/- 30 nM. These compounds were identified using our multiple protein structure (MPS) method which incorporates protein flexibility into a receptor-based pharmacophore model that identifies appropriate hotspots of binding. Docking the inhibitors with an induced-fit docking protocol suggested that the inhibitors mimicked the three critical binding residues of p53 (Phe19, Trp23, and Leu26). Docking also predicted a new orientation of the scaffolds that more fully fills the binding cleft, enabling the inhibitors to take advantage of additional hydrogen-bonding possibilities not explored by other small molecule inhibitors. One inhibitor in particular was proposed to probe the hydrophobic core of the protein by taking advantage of the flexibility of the binding cleft floor. These results show that the MPS technique is a promising advance for structure-based drug discovery and that the method can truly explore broad chemical space efficiently in the quest to discover potent, small-molecule inhibitors of protein-protein interactions. Our MPS technique is one of very few ensemble-based techniques to be proven through experimental verification of the discovery of new inhibitors.  相似文献   

15.
Quantum chemistry calculations at the levels of MP2/cc-pVDZ and MP2/cc-PVTZ have been carried out to study residue-specific interactions at the hydrophobic p53-MDM2 binding interface. The result of the calculation, based on structures from nanosecond molecular dynamics simulation, revealed that (19)Phe, (22)Leu, and (23)Trp of p53 have the strongest binding interaction with MDM2 followed by (26)Leu and (27)Pro. The specific residues of MDM2 that have dominant binding interactions with p53 are specifically identified to be (51)Lys, (54)Leu, (62)Met, (67)Tyr, (72)Gln, (94)Lys, (96)His, and (100)Tyr. The p53-MDM2 binding interaction is dominated by van der Waals interaction and to a lesser degree by electrostatic interaction. The MP2 results are in generally good agreement with those from the force field calculation while the DFT/B3LYP calculation failed to give attractive interaction energies for certain residue-residue interactions due to the lack of dispersion energy.  相似文献   

16.
A successful structure-based design of a class of non-peptide small-molecule MDM2 inhibitors targeting the p53-MDM2 protein-protein interaction is reported. The most potent compound 1d binds to MDM2 protein with a Ki value of 86 nM and is 18 times more potent than a natural p53 peptide (residues 16-27). Compound 1d is potent in inhibition of cell growth in LNCaP prostate cancer cells with wild-type p53 and shows only a weak activity in PC-3 prostate cancer cells with a deleted p53. Importantly, 1d has a minimal toxicity to normal prostate epithelial cells. Our studies provide a convincing example that structure-based strategy can be employed to design highly potent, non-peptide, cell-permeable, small-molecule inhibitors to target protein-protein interaction, which remains a very challenging area in chemical biology and drug design.  相似文献   

17.
Extensively validated 3D pharmacophore models for ALK (anaplastic lymphoma kinase) and EGFR (T790M) (epithelial growth factor receptor with acquired secondary mutation) were developed. The pharmacophore model for ALK (r2 = 0.96, q2 = 0.692) suggested that two hydrogen bond acceptors and three hydrophobic groups arranged in 3-D space are essential for the binding affinity of ALK inhibitors. Similarly, the pharmacophore model for EGFR (T790M) (r2 = 0.92, q2 = 0.72) suggested that the presence of a hydrogen bond acceptor, two hydrogen bond donors and a hydrophobic group plays vital role in binding of an inhibitor of EGFR (T790M). These pharmacophore models allowed searches for novel ALK and EGFR (T790M) dual inhibitors from multiconformer 3D databases (Asinex, Chembridge and Maybridge). Finally, the eight best hits were selected for molecular dynamics simulation, to study the stability of their complexes with both proteins and final binding orientations of these molecules. After molecular dynamics simulations, one hit has been predicted to possess good binding affinity for both ALK and EGFR (T790M), which can be further investigated for its experimental in-vitro/in-vivo activities.  相似文献   

18.
Hydroxamic acid derivatives with metal ion binding properties were collected from the literature to generate a pharmacophore and 3D-QSAR model for HIV strand transfer inhibition. The derived pharmacophore model (AAAHRR) recognizes both metal ion binding site and hydrophobic group. The QSAR model generated using this hypothesis expressed statistical significance (r 2 = 0.971 for the training set and q 2 = 0.913 for the test set). The ability of this pharmacophore model to retrieve other metal ion binding inhibitors was examined by screening the ChemBank database (ligandinfo) incorporated with 10 known strand transfer inhibitors. The studied favourable and unfavourable contours of chemical features (H-bond donor, acceptor and hydrophobic sites) revealed the role of hydrophobic substitution at the fluorobenzene ring and cyclization of the metal ion binding hydroxamic acid in effective integrase inhibition. Analysis of the frontier orbitals, HOMO and LUMO revealed that the nucleophilic / electrophilic interactions depend on the significant overlapping observed at the azaindole and hydroxamic acid groups. In essence, the generated pharmacophore model is competent enough to disclose the essential site-specific interactions involved in the inhibition of HIV integrase, and hence can be used in virtual screening to identify novel scaffolds as leads with increased anti-viral potency.  相似文献   

19.
The oncoprotein MDM2 regulates the activity and stability of the tumor suppressor p53 through protein-protein interaction involving their N-terminal domains. The N-terminal lid of MDM2 has been implicated in p53 regulation; however, due to its flexible nature, limited data are available concerning its role in ligand binding. The quantitative dynamics study using NMR reported here shows, for the first time, that the lid in apo-MDM2 slowly interconverts between a "closed" state that is associated with the p53-binding cleft and an "open" state that is highly flexible. Our results reveal that apo-MDM2 predominantly populates the closed state, whereas the p53-bound MDM2 exclusively populates the open state. Unlike p53 binding, the small molecule MDM2 antagonist nutlin-3 binds to the cleft essentially without perturbing the closed lid state. The lid dynamics thereby represents a signature for the experimental and virtual screening of therapeutic antagonists that target the p53-MDM2 interaction.  相似文献   

20.
The most potent inhibitor of the p53-MDM2 interaction reported to date is an 8-mer p53 peptide analogue (Novartis peptide), which contains 6-chlorotryptophane (Cl-Trp) and phosphonomethylphenylalanine (Pmp) as key residues for the enhanced activity. We report here a crystal structure of the co-complex between MDM2 and the Novartis peptide solved at 1.8 A resolution. The structural basis for the role of the two aromatic residues are delineated by comparing the present structure with crystal structures of the MDM2 co-complex bound to other inhibitors including the wt-p53 peptide itself.  相似文献   

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