HMG-CoA还原酶抑制剂三维药效团的构建

以作用于鼠肝脏细胞的21个3-羟基-3-甲基戊二酰辅酶A(HMG-CoA)还原酶抑制剂(RI)为训练集, 训练集化合物具备结构多样性, 来源于相同药理模型, 活性值IC50范围在0.3-8000 nmol·L-1. 利用Catalyst 计算HMG-CoA还原酶抑制剂最优药效团由一个氢键受体, 一个氢键给体, 一个疏水基团和一个芳香环特征组成. 药效团模型Fixed cost值, Total cost值和Configuration cost值分别为88.75、111.5 和16.98. 训练集化合物活性计算值与实测值相关系数为0.8883, 偏差值为1.269, 交叉验证结果表明, 药效团模型具有较高的置信度, 对测试集化合物活性值的预测结果显示有较好的预测能力, 可用于数据库搜索发现新的具有该活性的化合物, 也可用于中药或天然产物药物的研究开发.     

基于药效团模型从中草药数据库中搜索gpIIb/IIIa受体抑制剂

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.     

3DFs:用于药物设计的三维结构柔性搜索系统

在三维结构数据库中搜索含有某种药效团的分子的三维结构搜索法已经成为新药研制的重要手段，近年已有了广泛的发展。３ＤＦＳ是我室研制的用于药物分子设计的三维结构柔性搜索系统，该系统支持由化学功能基团定义的药效团，并详细定义了氢键给体、氢键受体、电荷中心、疏水区等重要化学功能基团的结构类型，并且具有三维构象柔性搜索功能。     

5-HT3受体拮抗剂药效团模型的构建

以31个来源于MDDR数据库中具有抑制鼠Bezold-Jarisch反射作用的5-HT3受体拮抗剂作为训练集化合物, 构建5-HT3受体拮抗剂药效团模型. 训练集化合物具备结构多样性, 来源于相同药理模型, 活性值ED50范围为0.05~320 μg/kg i.v.. 利用Catalyst计算5-HT3受体拮抗剂的最优药效团由一个氢键受体、一个疏水基团、一个正电离子化基团、一个芳香环特征和6个排除体积组成; Fixed cost值、Null cost 值、Δcost值和Configuration cost值分别为112.6, 172.0, 59.4和7.248. 训练集化合物活性的计算值与实测值相关系数为0.9031, 偏差值为0.8976, 基于Fischer的交叉验证结果表明药效团模型具有较高的置信度, 所得药效团对训练集化合物活性值的预测结果显示有较好的预测能力, 可用于数据库搜索指导发现新的具有该活性的先导化合物, 也可用于中药或天然产物药物研究开发.     

基于药效团模型从中草药数据库中搜索gpⅡb/Ⅲa受体抑制剂

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.     

距离比较法构建M1受体激动剂药效团模型

在M1受体三维结构未知的情况下,利用距离比较法（DISCO）对24个具有M1受体激动活性的化合物进行了研究,构建了M1受体激动剂可能的药效团模型,为设计新M1受体激动剂提供了参考,并以此为提问结构在ACD数据库和中草药数据系统（TCMDB）中进行搜索,得到一系列结构新颖并可能具有M1激动活性的化合物.     

距离比较法构建M1受体激动剂药效团模型

在M1受体三维结构未知的情况下,利用距离比较法(DISCO)对24个具有Mi受体激动活性的化合物进行了研究,构建了Mi受体激动剂可能的药效团模型,为设计新M1受体激动剂提供了参考,并以此为提问结构在ACD数据库和中草药数据系统(TCMDB)中进行搜索,得到一系列结构新颖并可能具有Mi激动活性的化合物.     

丙型肝炎病毒抑制剂的三维药效团和构效关系

通过ＣＡＴＡＬＹＳＴ软件包得到了两类ＨＣＶ ＮＳ３丝氨酸蛋白酶抑制剂的三维药效团模型。尽管这两类抑制剂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。这当这两类抑制剂和受体发生相互作用时,可能采用了相似的结合模式。根据药效团模型,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良好的预测能力（线性回归系数Ｒ＝０．８９）。     

γ-分泌酶抑制剂的药效团模型构建

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.     

6-氮杂吲唑类Pim-1激酶抑制剂的3D-QSAR、药效团模型研究和分子设计

Pim-1激酶通过作用于多种信号通路或靶点影响肿瘤的发生发展,近年来被认为是肿瘤治疗的良好靶标。本文采用SYBYL-X2.1.1软件中的Topomer CoMFA、GALAHAD模块建立计算机模型,研究39个基于6-氮杂吲唑环的Pim-1激酶抑制剂的三维定量构效关系及药效团特征元素。结果显示,Topomer CoMFA建模所得交叉验证系数(q²)和相关系数(r²)分别为0.756和0.951,结合外部验证表明此3D-QSAR模型具有较高预测能力及较好的统计学稳定性,同时,用等势图描述了R1、R2基团处立体场、静电场对活性的具体影响。药效团研究结果表明,含氢键受体的芳香杂环母核结构,以及侧链取代基中含有芳香杂环结构对化合物的活性贡献较大。最后根据上述模型信息新设计了15个Pim-1激酶抑制剂分子并完成活性预测及分子对接模式研究,其中4个分子的预测pIC₅₀高于建模分子中活性最好的化合物17,Surflex-Dock分析显示新设计分子均与Pim-1激酶形成较强氢键相互作用。基于6-氮杂吲唑环的Pim-1激酶抑制剂的3D-QS...     

An inequality for 3D database searching and its use in evaluating the treatment of conformational flexibility

Summary A mathematical formula is introduced for predicting the number of hits that should be observed in a flexible 3D database search, based on the results of a set of related queries. The projected number of hits is always greater than or equal to the actual number of hits, the discrepancy being due to imperfect treatment of conformational flexibility of the molecules. Hence, the difference between the projected and actual number of hits, , serves to measure how well conformational flexibility is being treated, in a manner that is objective, easy for a user to quickly verify, and independent of the particular algorithm for flexible 3D database search. It is shown that is a function both of how well conformational flexibility is treated and of the precision of the query. When the distance constraint is defined only to a precision of ±2.0 Å, in a single-conformer database of drug-like molecules values of only 0.03 are found, while in a single-conformer database of di- and tripeptides, is 0.15. At increased precision, a flexible 3D database search becomes critical. For a single-conformer database, using a query of precision ±0.2 Å, applied to a database of drug-like molecules, is 0.97; applied to a database of di- and tripeptides, is 2.21. By contrast, treating conformational flexibility by storing up to 100 conformers per molecule, at this precision, applied to a database of drug-like molecules, is 0.002; applied to a database of di- and tripeptides, is 0.07. This inequality, and hence , is defined only for database queries containing a single distance constraint; how the inequality may generalize to higher-dimensional queries is still unclear.     

酪氨酸激酶抑制剂的三维定量构效关系研究

利用柔性原子受体模型(FLARM)方法对一系列的异黄酮和喹诺酮衍生物表皮生长因子受体酪氨酸激酶抑制剂进行了三维定量构效关系研究，得到了合理的构效关系模型.FLARM方法的计算结果还给出了虚拟的受体模型，该模型说明了抑制剂与受体之间可能的相互作用.由该虚拟受体模型得到的受体-配体相互作用与Novartis药效团模型比较类似.     

A hybrid approach for addressing ring flexibility in 3D database searching

A hybrid approach for flexible 3D database searching is presented that addresses the problemof ring flexibility. It combines the explicit storage of up to 25 multiple conformations ofrings, with up to eight atoms, generated by the 3D structure generator CORINA with thepower of a torsional fitting technique implemented in the 3D database system UNITY. Acomparison with the original UNITY approach, using a database with about 130,000 entriesand five different pharmacophore queries, was performed. The hybrid approach scored, on anaverage, 10–20% more hits than the reference run. Moreover, specific problems withunrealistic hit geometries produced by the original approach can be excluded. In addition, theinfluence of the maximum number of ring conformations per molecule was investigated. Anoptimal number of 10 conformations per molecule is recommended.     

药物设计中的三维结构搜索方法

利用分子的三维特征, 在三维结构数据库中进行三维结构搜索的方法是一种发现先导化合物的快捷而有效的方法, 已经得到了广泛的重视。本文综述了三维结构搜索方法的原理、发展及其近年来在药物分子设计中的应用。     

Three-dimensional quantitative structure-activity relationship (3D QSAR) and pharmacophore elucidation of tetrahydropyran derivatives as serotonin and norepinephrine transporter inhibitors

Three-dimensional quantitative structure-activity relationship (3D QSAR) using comparative molecular field analysis (CoMFA) was performed on a series of substituted tetrahydropyran (THP) derivatives possessing serotonin (SERT) and norepinephrine (NET) transporter inhibitory activities. The study aimed to rationalize the potency of these inhibitors for SERT and NET as well as the observed selectivity differences for NET over SERT. The dataset consisted of 29 molecules, of which 23 molecules were used as the training set for deriving CoMFA models for SERT and NET uptake inhibitory activities. Superimpositions were performed using atom-based fitting and 3-point pharmacophore-based alignment. Two charge calculation methods, Gasteiger-Hückel and semiempirical PM3, were tried. Both alignment methods were analyzed in terms of their predictive abilities and produced comparable results with high internal and external predictivities. The models obtained using the 3-point pharmacophore-based alignment outperformed the models with atom-based fitting in terms of relevant statistics and interpretability of the generated contour maps. Steric fields dominated electrostatic fields in terms of contribution. The selectivity analysis (NET over SERT), though yielded models with good internal predictivity, showed very poor external test set predictions. The analysis was repeated with 24 molecules after systematically excluding so-called outliers (5 out of 29) from the model derivation process. The resulting CoMFA model using the atom-based fitting exhibited good statistics and was able to explain most of the selectivity (NET over SERT)-discriminating factors. The presence of −OH substituent on the THP ring was found to be one of the most important factors governing the NET selectivity over SERT. Thus, a 4-point NET-selective pharmacophore, after introducing this newly found H-bond donor/acceptor feature in addition to the initial 3-point pharmacophore, was proposed.     

新型多巴胺D3受体抑制剂的发现

根据最新解析的多巴胺D3受体的晶体结构进行活性位点分析, 建立了基于受体的药效团模型, 并对Asinex Gold Collection 数据库进行筛选, 选择7个化合物进行生物活性测试, 得到了高活性新型多巴胺受体抑制剂(04932482), 它对多巴胺D3受体抑制率达85.45%, 其Ki值为(806.75±34.58) nmol/L. 进一步对活性化合物进行结构分析, 研究了其与受体相互作用的模式, 并以此为指导提出以04932482为先导化合物进行结构改造的方向.