分子构效关系研究的模式识别方法

定量构效关系QSAR是研究并揭示物质结构和活性之间的联系，近年来有广泛的研究与应用。在一定程度上，联系揭示的是一种模式识别的问题，本介绍了在此类研究中所涉及到的模式识别方法，并作了一些前景展望。     

昆虫天然免疫的研究进展

对果蝇等昆虫天然免疫的研究有利于揭示人类自身的免疫机制,并为感染性疾病和自身免疫病等的治疗提供新思路.昆虫的天然免疫机制包括物理防线、体液免疫和细胞免疫等方面.在病原体入侵昆虫体内后,昆虫可通过模式识别机制识别病原体并通过Toll途径和Imd途径等机制启动昆虫的体液及细胞免疫反应.昆虫的体液免疫和细胞免疫并不是绝然独立的,而是相互联系、相互促进和协作.在昆虫的各种免疫反应中,抗菌肽的产生、黑化包被反应和细胞吞噬作用是最为重要的防御机制.     

神经网络研究与模式识别

本文讨论了模式识别研究中存在的一些主要问题。提出神经网络的研究不能停留在把它作为实现现有模式识别方法的一种工具上 ,而应着眼于解决一些主要问题上。并结合具体问题对当前状况作了简要的综述     

肺腺癌吸烟相关甲基化模式识别分类模型及特征基因的识别研究

吸烟是导致肺癌的一个重要诱导因素,从全基因组基因甲基化水平出发,利用生物信息学方法,通过建立对当前吸烟/不吸烟样本的模式识别分类模型,识别甲基化特征基因,为揭示不吸烟肺癌患者的患病机理奠定基础。为避免甲基化微阵列数据超高维小样本、高噪声、高相关性以及信息饱和现象淹没真正的特征基因,首次采用迭代多重筛选方法,分别从显著性差异、与基因表达水平的关系、生物功能、分类重要性等多个角度对全基因组甲基化数据进行多步筛选,从而识别吸烟相关特征基因。以TCGA数据库中127个肺腺癌样本为训练集,64个EDRN肺腺癌样本为独立测试集,最终确定了48个关键基因。相应模式识别模型对训练集精度达到87.5%(敏感性、特异性分别为87.2%和87.8%),独立测试集分类精度达到76.4%(敏感性、特异性分别为80.2%和73.6%)。交叉研究表明,其中17个基因对癌症发展的重要性已经在其他研究中有所证实,进一步的研究则证明其甲基化的重要性。同时,KEGG和IPA对特征基因在基因调控网络和代谢通路水平的分析表明,特征基因与癌症的发展以及生物功能、细胞发育等都有着密切的联系。     

TLR家族在中枢神经系统中的免疫调节作用

Toll样受体（Toll—like receptors，TLRs）家族识别病原体相关分子模式（PAMPs）从而启动固有免疫应答，属于模式识别受体（PRRs）。目前关于TLRs在中枢神经系统中发挥的免疫调节作用所进行的研究已经积累了一些资料。深入探讨TLR家族在中枢系统的慢性炎症中的作用，将有助于揭示阿尔茨海默病等常见病的发病机理及寻求其防治新措施。     

Toll样受体-9的研究进展

Toll样受体-9(Toll-like receptor 9,TLR9)是哺乳动物TLRs家族中一员,作为细胞表面的天然模式识别受体,主要参与免疫刺激序列(CpG序列)激活免疫细胞的信号传导,从而在天然抗感染免疫及联系天然免疫和获得性免疫中发挥重要作用。通过对TLR9-CpG作用通路的研究,将促进天然免疫机制研究的进一步深入,有利于解决诸如:CpG佐剂、DNA疫苗、CpG抗感染、抑制肿瘤、预防过敏反应等实际应用过程中存在的问题。     

心电图模式分类方法研究进展与分析

心电图模式分类是模式识别研究的经典应用之一,在可穿戴心电图设备、动态心电图诊断、重症监护以及疾病与心脏活动关系研究等方面具有重要的应用价值。讨论面向实际应用的心电图模式分类工作的可能方法,归纳近年来心电图模式分类技术在知识推理模型、结构模式识别、统计模式识别等方面的研究进展,并在此基础上做分析与展望。同时论述心电图模式分类研究所面临的主要挑战,即面向实际数据的分类器构建、心电图数据库的标注、分类模型评估标准和领域特征表示问题,并探讨可能的解决途径。     

模式生物基因组研究进展

我们重点介绍了模式生物基因组计划的研究进展情况 ,以阐明其基因组的结构、功能以及生物进化关系间的普遍规律 ,从而揭示生命的本质及生物间的相互联系。同时明确模式生物在比较基因组学研究中的地位和作用 ,为研究高等生物特别是人类的生、老、病、死提供生物模式     

NODs蛋白及其与TLRs相互调控在机体抗病原真菌感染中的作用

宿主的模式识别受体(pattern recognition receptors,PRRs)主要包括Toll样受体(TLRs)和核苷酸结合寡聚化结构域( NODs)两大类受体[1],其中TLRs是胞膜模式识别受体,NODs是近年来新发现的胞质模式识别受体.目前,已有大量关于TLRs与NODs在细菌感染免疫应答中作用的研究,但NODs蛋白在真菌感染中作用的研究报道屈指可数,且NODs与TLRs在抗病原真菌感染中相互调控关系的机制尚不明确.本文主要对NODs蛋白信号通路,NODs与TLRs相互调控关系,NODs蛋白在抗病原真菌感染免疫应答中的作用进行综述.     

Toll样受体研究进展

Toll最早在果蝇中被发现。Toll受体蛋白 (d Toll)不仅参与果蝇胚胎发育时背腹的形成 ,而且参与成蝇对病原体侵袭的先天性免疫应答 ,是微生物诱导成年果蝇产生抗菌肽的信号转导通道的门户。 Toll样受体是先天性模式识别受体 ,在细胞活化信号的转导中起重要作用。它作为联系先天性与获得性免疫系统的桥梁 ,备受人们关注     

Structure-activity relationship of genotoxic polycyclic aromatic nitro compounds: further evidence for the importance of hydrophobicity and molecular orbital energies in genetic toxicity.

A quantitative structure-activity relationship (QSAR) has been formulated for 15 polycyclic aromatic nitro compounds acting on E. coli PQ37. Upon damage of DNA by these substances beta-galactosidase is induced and can be easily assayed colorimetrically, hence, this is a short-term test for mutagenicity. The QSAR (log SOSIP = 1.07 log P - 1.57 epsilon LUMO - 6.41) is strikingly similar to that found earlier with nitroaromatics acting in the Ames test (TA100) and differs significantly for that found using TA98 organisms. The QSAR brings out in a unique manner the underlying similarity in the two test systems.     

化合物构效关系的模糊极小极大神经网络识别研究

应用模糊极小极大神经网络研究了化合物复杂结构和性能（QSAR）之间的关系，用该法进行几组化合物致癌的识别，结果优于线性回归的方法，对此作出一些分析。     

Quantitative structure-activity relationship investigation of the role of hydrophobicity in regulating mutagenicity in the Ames test: 2. Mutagenicity of aromatic and heteroaromatic nitro compounds in Salmonella Typhimurium TA100.

A quantitative structure-activity relationship (QSAR) has been derived for the mutagenic activity of 117 aromatic and heteroaromatic nitro compounds acting on Salmonella typhimurium TA100. Relative mutagenic activity is bilin-early dependent on hydrophobicity, with an optimal log P of 5.44, and is linearly dependent on the energy of the lowest unoccupied molecular orbital of the nitro compound. The dependence of mutagenic activity on hydrophobicity and electronic effects is very similar for TA98 and TA100. Mutagenic activity in TA100 does not depend on the size of the aromatic ring system, as its does in TA9. The effect of the choice of assay organism, TA98 versus TA100, on nitroarene QSAR is seen to be similar to the effect previously found for aminoarenes. Lateral verification of QSARs is presented as a tool for establishing the significance of a new QSAR.     

Identification of 2-nonynoic acid, a cosmetic component, as a potential trigger of primary biliary cirrhosis

Antimitochondrial antibodies (AMA) are unique among autoimmune serologic reactants because of their extremely high association with the index disease primary biliary cirrhosis (PBC). This autoantibody response is specifically directed only to the lipoyl domain of the mitochondrial 2-oxo-acid dehydrogenase complexes, which prompted us to search for environmental mimotopes in the form of xenobiotics and led to our identification of 2-octynoic acid as a high-affinity reactant for AMA. To focus on the chemical characteristics requisite for binding of AMA to the xenobiotic-modified self-peptide, quantitative structure-activity relationship (QSAR) studies were performed using a panel of alkynoic compounds, including examination of the length of the carbon chain and the location of the triple bond in the identified mimotope. Analyses of octynamides that varied in the position of the triple bond demonstrated that only the 2-octynamide reacted strongly with PBC sera. Furthermore, among 2-alkynamides with varying carbon chain length, 2-octyn-, 2-nonyn- (particularly) and 2-decynamide exhibited the highest reactivity. Thus, an optimal chemical structure of the xenobiotically modified epitope recognized by AMA-positive PBC sera is provided by 2-nonynoic acid. The methyl ester of this compound is ranked 2,324th out of 12,945 compounds to which there is occupational exposure, with an 80% female prevalence due to its use in cosmetic products. Our findings illustrate an unusual polyreactivity of anti-PDC-E2 and support the idea of epitope mimicry in the genesis of this autoantibody and perhaps of PBC itself.     

3D QSAR of aminophenyl benzamide derivatives as histone deacetylase inhibitors

The article describes the development of a robust pharmacophore model and the investigation of structure activity relationship analysis of 48 aminophenyl benzamide derivatives reported for Histone Deacetylase (HDAC) inhibition using PHASE module of Schrodinger software. A five point pharmacophore model consisting of two aromatic rings (R), two hydrogen bond donors (D) and one hydrogen bond acceptor (A) with discrete geometries as pharmacophoric features was developed and the generated pharmacophore model was used to derive a predictive atom-based 3D QSAR model for the studied dataset. The obtained 3D QSAR model has an excellent correlation coefficient value (r(2)=0.99) along with good statistical significance as shown by high Fisher ratio (F=631.80). The model also exhibits good predictive power confirmed by the high value of cross validated correlation coefficient (q(2) = 0.85). The QSAR model suggests that hydrophobic character is crucial for the HDAC inhibitory activity exhibited by these compounds and inclusion of hydrophobic substituents will enhance the HDAC inhibition. In addition to the hydrophobic character, hydrogen bond donating groups positively contributes to the HDAC inhibition whereas electron withdrawing groups has a negative influence in HDAC inhibitory potency. The findings of the QSAR study provide a set of guidelines for designing compounds with better HDAC inhibitory potency.     

基于SCORE函数估算HLA-A*0201限制性CTL表位亲和性

目的 建立HLA-A*0201限制性CTL表位亲和性的定量预测方法。方法基于SCORE打分函数,运用定量构效关系的理论和方法研究了HLA-A*0201限制性CTL表位九肽结构与亲和性间的定量关系,并建立了SCORE得分与亲和性的定量关系模型,并用外部样本(5个HLA-A*0201限制性CTL表位九肽)作为预测集用于检验模型的预测能力。结果基于SCORE打分函数建立的定量模型具有较好的相关性(r=0．9165,RMS=0．38)和对外部样本的预测能力(rpred=0.9847,RMS=0.135)。结论基于SCORE打分函数,运用定量构效关系研究的理论和方法建立了HLA-A*0201限制性CTL表位亲和性的定量预测方法,为实验鉴定高亲和性HLA-A*0201限制性CTL表位提供了理论依据。     

QSAR studies for the pharmacological inhibition of glycogen synthase kinase-3

The enzyme GSK-3 plays a central role in cells during the phosphorylation of various key regulatory proteins, and consequently pharmacological inhibitors of this enzyme potentially allow the treatment of diseases that include neurodegenerative and bipolar affective disorders, diabetes, and diseases caused by unicellular parasites. Today there is a huge number of reported empirical structure-activity relationships (SAR) that may guide a rational design of more potent and selective inhibitors. However, only a few studies based on Quantitative Structure-Activity Relationships (QSAR) are available for predicting the inhibitor potency against this specific kinase, and they involve mainly molecular modeling and 3D-QSAR. The present review deals with the recent search for a quantitative analysis of GSK-3 inhibition.