In silico engineering of tailored ink-binding ability at molecular printboards.

Molecular recognition between guest ink molecules and beta-cyclodextrin (beta-CD) cavities at self-assembled monolayers provides a molecular printboard for nanopatterning applications. We recently used molecular dynamics (MD) simulations to describe the specificity of ink-printboard binding and here extend the simulations to include charged cyclodextrin hosts, necessary to broaden the chemistry of molecular printboards and bind charged inks such as the ferrocenium cation. Shifting to high pH, or alternatively grafting a charged sidearm onto beta-CD, created three distinct types of anionic beta-CD cavity and we used electronic structure calculations and MD simulations to measure host-guest charge transfer and binding strengths. We find that steric recognition of uncharged organic molecules is retained at the charged printboards, and that improved guest-host electrostatic contacts can strengthen binding of larger inks while penalising small inks, enhancing the level of discrimination. A prudent choice of complementary host-guest shape and charge states thus provides a means of tuning both ink binding strength and specificity at molecular printboards.     

Partial least-squares regression and fuzzy clustering — A joint approach

Chemical and physical analyses of malt, the main ingredient of beer, have been used to predict the concentration of certain volatile compounds in the finished beer.The prediction was done by means of the partial least squares regression (PLS2) in SIMCA. The total data set as well as individual malt clusters were submitted to PLS analysis. Best prediction was obtained by separating the total object matrix in classes according to similarity found by fuzzy pattern recognition (FCV). FCV was also used to separate the beer variables in classes and to select the subset of variables to be predicted.A joint approach of fuzzy pattern recognition to identify groups of samples and SIMCA-PLS2 to predict several dependent variables is suggested as a powerful tool in process-analytical chemistry.     

基于非生物折叠体的分子识别

利用分子自组装的方法控制大分子量的线性有机分子的构象是物理有机化学一个富于挑战性的研究课题. 近年来, 化学家已经成功利用不同的分子内非共价键作用力如氢键和疏溶剂作用等诱导线性分子的折叠乃至螺旋构象的产生. 综述了近年来这种新的非生物二级结构形式在分子识别研究中的应用.     

Tweezer分子的合成和对有机阴离子的配位效应

本文报道新的Ｔｗｅｅｚｅｒ（１）的合成，用＾１ＨＮＭＲ研究了新的Ｔｗｅｅｚｅｒ分子和对硝基苯甲酸盐的配位效应，结果表明它兴通过氢键，静电引力和芳环夹心堆叠作用而自动缔合。     

Repeatability and pattern recognition of bacterial fatty acid profiles generated by direct mass spectrometric analysis of in situ thermal hydrolysis/methylation of whole cells

Direct CI mass spectrometry profiling of fatty acid methyl esters (FAMEs) from in situ thermal hydrolysis/methylation (THM) of whole bacterial cells with tetramethylammonium hydroxide (TMAH) has been demonstrated as a potential method for real time and fieldable detection/identification of microorganisms. Bacillus anthracis (Ames), Yersinia pestis (Nair. Kenya), Vibrio cholerae (E1 Tor), Brucella melitensis (Abortus wild) and Francisella tularensis (LVS vaccine) were profiled by this method during a 10-month period. Repeatability of the in situ FAME data was calculated using one-way analysis of variance (ANOVA) and a t-test. Artificial neural network (ANN) and multivariate statistics of the FAME profiles were also compared for bacterial identification/classification. Equivalent results were obtained with a multivariate rule building expert system (MuRES) and the ANN. However, the ANN analysis required much less computer time and was deemed the best choice for this application. In situ THM FAME profiles of the bacterial samples provided comparable results with those obtained from the Microbial Identification System (MIDI) (Newark, DE) wet chemistry-gas chromatographic based system.     

Molecular Recognition of Nucleic Acid Bases in Water by Hydrogen Bonding of Poly(vinyldiaminotriazine)

Poly(2-vinyl-4,6-diamino-1,3,5-triazine) efficiently binds nucleic acid bases and nucleosides in water by using complementary hydrogen bonding. The binding activity decreases in the order: U, T > A C, G. The corresponding monomer shows virtually no activity, indicating a predominant role of polymer effect for the molecular recognition in water.     

模式识别—人工神经网络在化学中的若干新应用

本文通过我们应用模式识别－人工神经网络方法预报新化合物、熔盐相图以及复杂化学反应体系的研究，展示应用模式识别－人工神经网络方法与物理化学理论相结合，研究化学现象的可能性和应用价值。     

Molecular recognition properties of salicylic acid-imprinted polymers

Summary Two molecularly imprinted polymers (MIP) have been prepared using the acidic drug salicylic acid, which can form intramolecular hydrogen bond, as the template and acrylamide or 4-vinylpyridine as the functional monomer. HPLC was used to evaluate the binding performance of the MIP for the template and for several analogues. The results showed that the MIP (P₂) prepared using acrylamide as the functional monomer had no molecular imprinting effect whereas that (P₁) prepared using 4-vinylpyridine as the functional monomer had a significant molecular imprinting effect. The reason the molecular imprinting effect was different for the two MIP was elucidated and the molecular recognition properties of P₁ were studied in detail. It was confirmed that electrostatic interaction played an important role in the molecular recognition of P₁. Scatchard analysis showed that two types of binding site with distinctly different affinity were formed in P₁. Their dissociation constants were estimated to be 7.6×10⁻⁵ mol L⁻¹ and 3.2×10⁻³ mol L⁻¹, respectively. Because P₁ has high affinity and selectivity for salicylic acid not only in organic systems but also in water-containing systems, it gives P₁ the potential for use in the enrichment, separation, and detection of salicylic acid in biological fluids.