化学环境编码与分子相似度计算

分子相似度方法主要用于药物分子设计中先导化合物的选取及化合物物理、化学性质的预测,这种方法所依据的原理是：相似的化合物结构将具有相似的化学及物理性质［‘,’1．将已知具有某种性质的化合物的结构（常称为探针化合物）与诸多化合物进行比较,由此得到与之相似的化合物,这种邻近化合物有可能在分子设计中做先导化合物．近年来已报道过多种化合物相似度的计算方法,可粗略的归为以下几类：（l）结构碎片法［‘’‘j;（2）拓扑指数法卜·“;（3）量子化学方法［’,’j．本文提出一种新的化学环境编码方法,该方法有别于结构碎片…     

用氨基酸加和法计算多肽的脂水分配系数

在药物设计中,化合物的流水性是值得考虑的一种重要的性质．目前常使用化合物在正辛醇和水两相间的分配系数的对数值（logP）来度量其流水性．仅从化合物的结构出发来预测其脂水分配系数具有重要的意义,已有多种计算方法见诸报导’‘,“．对于普通的有机化合物,它们能给出较好的结果．多肽是一类具有重要生物功能的化合物．在药物设计中,多肽也是常用的物系．目前预测一般有机化合物脂水分配系数的方法对于多肽尚不能给出满意的结果．鉴于多肽类化合物特殊的重要性,专门发展一种方法来预测多肽的脂水分配系数也是十分必要的．在这方…     

建立在群对称轨道(SMO)及特征组态(CD)基础上的CI方法与程序发展

ISMO－CDCI方法点群理论，特别是不可约张量方法，在量子化学理论方法发展以及简化概念与计算方面，发挥了重要作用．但在国外的量子化学计算程序（如G94）中，在后自洽场（opt－SCF）计算方面，很少用到对称约化．在文献中，只见有关hbeltah群（DZh与它的子群）对称约化用于组态相关计算的报导．由于多重耦合系数的计算复杂，蜕化不可约表示多体问题的对称约化难于得到解决．我们提出了一个统一与普遍的方法，它能解决所有分子体系多体相关的点群对称约化问题［‘－6］，这个方法的核心是群对称轨道（SMO）概念的提出．SMO的基本特…     

遗传算法在分子图形显示中的应用

遗传算法在分子图形显示中的应用邵学广，蔡文生，张懋森，赵贵文（中国科学技术大学应用化学系，化学物理系，合肥２３００２６）分子图形和分子模型的研究是计算化学领域中研究的热门课题之一［１，２］，它对于结构一活性相关、有机合成路线设计、药物设计［３，４］等...     

4—苯甲酰氧基苯甲酸液晶性的研究

关于个苯甲酸氧基苯甲酸（BBA）的合成虽已有报道［‘j，但其双分子缔合物具有液晶性则属本文作者首次发现．一般认为在有机分子结构中引人不对称性及柔性基团对其液晶性的形成十分重要“‘．在不具备这两个条件时，当分子的长径比达到一定值（约l／d＞4）时也可能出现液晶性，但实例不多，且一般t。。很高．如聚合度为5的聚苯t。。一388”C［’j，而且难溶．这给此类液晶化合物的研究带来很大不便．BBA以双分子缔合物（BBA）。形式存在，结构对称，亦无柔性基团，但却具有液晶性，其t。。为230C．BBA与个乙酸氧基苯甲酸形成的低共熔…     

基于药物数据报道数据库的虚拟组合片段库构建

对药物数据报道数据库中142553个药物分子进行统计分析, 提取得到了这些药物分子的共同结构特征. 根据药物分子的结构特征将其拆分为环结构、侧链和连接子, 共整理得到32017个片段结构, 其中环结构13642个、侧链10076个、连接子8299个. 为更好地指导全新药物设计, 利用拆分片段构建了三个虚拟组合片段数据库: 用环结构和侧链组合方式构建了药效基团库, 含有34244个片段; 用环结构的刚性特点构建了基本骨架库, 含有片段13574个; 直接利用连接子构建了连接片段库, 含有连接片段8051个. 库中所有片段都经过能量优化, 均具有合理的构型和构象, 可以用于虚拟组合库的构建和全新药物设计.     

酰胺型冠醚液晶的合成及性质研究

冠醚液晶出现至今仅十几年，由于其具有冠醚和液晶的各种性质而受到人们的关注［‘－‘1．我们在已有工作的基础上，设计合成了5种酸胺型冠醚液晶分子（4—8），其中3种分子（4－6）具有液晶性．合成路线如下：1结果与讨论合成样品4－8经IR、MS、‘HNMR和元素分析确证其结构．用DSC和Texture图测定了4－6的液晶性质，其结果见图1．化合物7、8无液晶性，分子长径比分别为5．8：I，满足一般律状向列液晶分子长径比的要求．当在其分子链中增加1个苯环（5、6）时，分子的刚性链比例增大，整个分子的刚性增加，则具有液晶性．双臂型冠醚液…     

应用分子图形学、分子力学、量子化学及静电势研究农药分子结构与性能关系(X)──磺酰脲分子内旋转通道的分子力学研究

磺酞豚分子是一类极其重要的低毒超高效除草剂，有着十分重要的用途．研究分子的空间结构对于了解分子的构效关系十分重要．最近，我们测定的一系列分子的晶体结构［‘－’1表明，分子1、2、3晶体结构的空间群分别为PZ；儿、Pz、Pz，说明晶体中分别有对称元素（对称面或者对称中心），分子以对映体的形式存在于晶体中．由于磺酸豚分子本身不存在手性原子，由此推断磺酷服分子在晶体中存在的对映异构体是由内旋转阻碍产生的，因而应是构象异构体．本项研究工作的目的是应用分子力学方法，计算阻碍内旋转的能垒，从而找出分子内旋转时的最低…     

化合物分子表面积计算方法的研究

化合物的分子表面积是重要的物理化学性质参数．根据不同的应用领域及数学方法,提出了多种分子表面积算法[1-10],由此产生了“分子表面积法”,各方法的有效性在各具体应用领域都已被验证．本文将统计方法中的随机变量引入计算化合物分子表面积体系,由分子模型化技术得到化合物分子的原子坐标,不考虑化合物分子中原子的相互作用及分子间近似,直接计算分子表面积．使用该方法可以计算“净”分子表面积、“溶剂可及表面积”、甚至分子结构片段,分子结构中有交叉重叠片段及存在“空洞”的各种分子表面积,该算法及程序较简捷,适应范围广,计算结果较为满意．     

反相胶束对辣根过氧化物酶催化反应的影响

胶束体系是酶学研究比较理想的体系,因为它所具有的诸如热力学稳定、光学透明及能增溶亲水分子、亲油分子或两性分子等性质,使许多酶在胶束体系中的反应速率远远高于在水相中,即人们发现的所谓“超活性”［‘j．辣根过氧化物酶（HRP）是一种比较稳定的酶,且价廉易得,具备一般过氧化物酶的典型反应．在研究中人们发现,HRP在反相胶束体系中同样具有“超活性”,由于HRP能够催化大量底物进行反应,因此“超活性”对HRP的催化反应具有重要意义．已有研究者［’、’j对CTAB反相胶束体系中HRP的性质进行了探讨,但反相胶束对HRP的…     

Receptor-independent 4D-QSAR analysis of a set of norstatine derived inhibitors of HIV-1 protease

A training set of 27 norstatine derived inhibitors of HIV-1 protease, based on the 3(S)-amino-2(S)-hydroxyl-4-phenylbutanoic acid core (AHPBA), for which the -log IC(50) values were measured, was used to construct 4D-QSAR models. Five unique RI-4D-QSAR models, from two different alignments, were identified (q(2) = 0.86-0.95). These five models were used to map the atom type morphology of the lining of the inhibitor binding site at the HIV protease receptor site as well as predict the inhibition potencies of seven test set compounds for model validation. The five models, overall, predict the -log IC(50) activity values for the test set compounds in a manner consistent with their q(2) values. The models also correctly identify the hydrophobic nature of the HIV protease receptor site, and inferences are made as to further structural modifications to improve the potency of the AHPBA inhibitors of HIV protease. The finding of five unique, and nearly statistically equivalent, RI-4D-QSAR models for the training set demonstrates that there can be more than one way to fit structure-activity data even within a given QSAR methodology. This set of unique, equally good individual models is referred to as the manifold model.     

酪氨酸激酶抑制剂的柔性原子受体模型方法研究

用柔性原子受体模型方法对一系列嘧啶类衍生物酪氨酸激酶抑制剂进行了3D－ QSAR研究，建立了相关性很好的模型，这些模型对测试集中化合物活性的预测结果 表明其具有较强的预测能力。柔性原子受体模型方法还给出了虚拟的受体模型，表 明了受体和配体之间可能的相互作用，包括两个氢键相互作用、一个疏水作用和一 个硫－芳香相互作用，这与Novartis的药效团模型非常一致。     

Virtual screening and rational drug design method using structure generation system based on 3D-QSAR and docking

An efficient virtual and rational drug design method is presented. It combines virtual bioactive compound generation with 3D-QSAR model and docking. Using this method, it is possible to generate a lot of highly diverse molecules and find virtual active lead compounds. The method was validated by the study of a set of anti-tumor drugs. With the constraints of pharmacophore obtained by DISCO implemented in SYBYL 6.8, 97 virtual bioactive compounds were generated, and their anti-tumor activities were predicted by CoMFA. Eight structures with high activity were selected and screened by the 3D-QSAR model. The most active generated structure was further investigated by modifying its structure in order to increase the activity. A comparative docking study with telomeric receptor was carried out, and the results showed that the generated structures could form more stable complexes with receptor than the reference compound selected from experimental data. This investigation showed that the proposed method was a feasible way for rational drug design with high screening efficiency.     

Virtual screening and rational drug design method using structure generation system based on 3D-QSAR and docking

An efficient virtual and rational drug design method is presented. It combines virtual bioactive compound generation with 3D-QSAR model and docking. Using this method, it is possible to generate a lot of highly diverse molecules and find virtual active lead compounds. The method was validated by the study of a set of anti-tumor drugs. With the constraints of pharmacophore obtained by DISCO implemented in SYBYL 6.8, 97 virtual bioactive compounds were generated, and their anti-tumor activities were predicted by CoMFA. Eight structures with high activity were selected and screened by the 3D-QSAR model. The most active generated structure was further investigated by modifying its structure in order to increase the activity. A comparative docking study with telomeric receptor was carried out, and the results showed that the generated structures could form more stable complexes with receptor than the reference compound selected from experimental data. This investigation showed that the proposed method was a feasible way for rational drug design with high screening efficiency.     

4D-QSAR analysis of a series of antifungal p450 inhibitors and 3D-pharmacophore comparisons as a function of alignment

A training set of 55 antifungal p450 analogue inhibitors was used to construct receptor-independent four-dimensional quantitative structure-activity relationship (RI 4D-QSAR) models. Ten different alignments were used to build the models, and one alignment yields a significantly better model than the other alignments. Two different methodologies were used to measure the similarity of the best 4D-QSAR models of each alignment. One method compares the residual of fit between pairs of models using the cross-correlation coefficient of their residuals of fit as a similarity measure. The other method compares the spatial distributions of the IPE types (3D-pharmacophores) of pairs of 4D-QSAR models from different alignments. Optimum models from several different alignments have nearly the same correlation coefficients, r(2), and cross-validation correlation coefficients, xv-r(2), yet the 3D-pharmacophores of these models are very different from one another. The highest 3D-pharmacophore similarity correlation coefficient between any pair of 4D-QSAR models from the 10 alignments considered is only 0.216. However, the best 4D-QSAR models of each alignment do contain some proximate common pharmacorphore sites. A test set of 10 compounds was used to validate the predictivity of the best 4D-QSAR models of each alignment. The "best" model from the 10 alignments has the highest predictivity. The inferred active sites mapped out by the 4D-QSAR models suggest that hydrogen bond interactions are not prevalent when this class of P450 analogue inhibitors binds to the receptor active site. This feature of the 4D-QSAR models is in agreement with the crystal structure results that indicate no ligand-receptor hydrogen bonds are formed.     

Three-dimensional quantitative structure-activity relationship analysis of the new potent sulfonylureas using comparative molecular similarity indices analysis

The present study describes the implementation of a new three-dimensional quantitative structure-activity relationship (3D-QSAR) technique: comparative molecular similarity indices analysis (CoMSIA) to a set of novel herbicidal sulfonylureas targeted acetolactate synthase. Field expressions in terms of similarity indices in CoMSIA were applied instead of the usually used Lennard-Jones and Coulomb-type potentials in CoMFA. Two different kinds of alignment techniques including field-fit alignment and atom-by-atom fits were used to produce the molecular aggregate. The results indicated that those two alignment rules generated comparative 3D-QSAR models with similar statistical significance. However, from the predictive ability of the test set, the models from the alignment after maximal steric and electrostatic optimization were slightly better than those from the simple atom-by-atom fits. Moreover, systematic variations of some parameters in CoMSIA were performed to search the best 3D-QSAR model. A significant cross-validated q2 was obtained, indicating the predictive potential of the model for the untested compounds; meanwhile the predicted biological activities of the five compounds in the test set were in good agreement with the experimental values. The CoMSIA coefficient contour plots identified several key features explaining the wide range of activities, which were very valuable for us in tracing the properties that really matter and getting insight into the potential mechanisms of the intermolecular interactions between inhibitor and receptor, especially with respect to the design of new compounds.     

3D-QSAR and receptor modeling of tyrosine kinase inhibitors with flexible atom receptor model (FLARM)

A set of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors was investigated with the aim of developing 3D-QSAR models using the Flexible Atom Receptor Model (FLARM) method. Some 3D-QSAR models were built with high correlation coefficients, and the FLARM method predicted the biological activities of compounds in test set well. The FLARM method also gave the pseudoreceptor model, which indicates the possible interactions between the receptor and the ligand. The possible interactions include two hydrogen bonds, one hydrophobic interaction, and one sulfur-aromatic interaction, which are in accord with those in the pharmacophore model given by the scientists at Novartis. This shows that the FLARM method can bridge 3D-QSAR and receptor modeling in computer-aided drug design. Pharmacophore can be obtained according to these results, and 3D searching can then be done with databases to find the lead compound of EGFR tyrosine kinase inhibitors.     

Fragment-based strategy for structural optimization in combination with 3D-QSAR

Fragment-based drug design has emerged as an important methodology for lead discovery and drug design. Different with other studies focused on fragment library design and active fragment identification, a fragment-based strategy was developed in combination with three-dimensional quantitative structure–activity relationship (3D-QSAR) for structural optimization in this study. Based on a validated scaffold or fragment hit, a series of structural optimization was conducted to convert it to lead compounds, including 3D-QSAR modelling, active site analysis, fragment-based structural optimization and evaluation of new molecules. 3D-QSAR models and active site analysis provided sufficient information for confirming the SAR and pharmacophoric features for fragments. This strategy was evaluated through the structural optimization on a c-Met inhibitor scaffold 5H-benzo[4,5]cyclohepta[1,2-b]pyridin-5-one, which resulted in an c-Met inhibitor with high inhibitory activity. Our study suggested the effectiveness of this fragment-based strategy and the druggability of our newly explored active region. The reliability of this strategy indicated it could also be applied to facilitate lead optimization of other targets.     

Estimation of the aqueous solubility of organic molecules by the group contribution approach

Several group contribution methods to estimate the aqueous solubility of organic molecules are proposed and evaluated for their ability to predict the water solubility of new molecules. The learning set consisted of 1168 organic compounds with experimental data taken from the literature after critical evaluation. The best method, based on a new fragment atom scheme, leads to a squared correlation coefficient of 0.95 and an average absolute calculation error of 0.50 log unit, which is superior to other group contribution methods currently available. One of the advantages of this model is that it has upper and lower limits so that the predicted solubilities cannot be unrealistily high or low.