Identification of biological tissues by rapid evaporative ionization mass spectrometry.

The newly developed rapid evaporative ionization mass spectrometry (REIMS) provides the possibility of in vivo, in situ mass spectrometric tissue analysis. The experimental setup for REIMS is characterized in detail for the first time, and the description and testing of an equipment capable of in vivo analysis is presented. The spectra obtained by various standard surgical equipments were compared and found highly specific to the histological type of the tissues. The tissue analysis is based on their different phospholipid distribution; the identification algorithm uses a combination of principal component analysis (PCA) and linear discriminant analysis (LDA). The characterized method was proven to be sensitive for any perturbation such as age or diet in rats, but it was still perfectly suitable for tissue identification. Tissue identification accuracy higher than 97% was achieved with the PCA/LDA algorithm using a spectral database collected from various tissue species. In vivo, ex vivo, and post mortem REIMS studies were performed, and the method was found to be applicable for histological tissue analysis during surgical interventions, endoscopy, or after surgery in pathology.

Proton dissociation properties of arylphosphonates: Determination of accurate Hammett equation parameters.

Determination of the proton dissociation constants of several arylphosphonic acid derivatives was carried out to investigate the accuracy of the Hammett equations available for this family of compounds. For the measurement of the pKa values modern, accurate methods, such as the differential potentiometric titration and NMR-pH titration were used. We found our results significantly different from the pKa values reported before (pKa1: MAE = 0.16 pKa2: MAE=0.59). Based on our recently measured pKa values, refined Hammett equations were determined that might be used for predicting highly accurate ionization constants of newly synthesized compounds (pKa1=1.70-0.894σ, pKa2=6.92-0.934σ).

Use of reversed-phase liquid chromatography for determining the lipophilicity of alpha-aryl-N-cyclopropylnitrones.

The relationship between a reversed-phase high-performance liquid chromatography (RP-HPLC) retention parameter and various calculated log P-values of our previously synthesized alpha-aryl-N-cyclopropyl-nitrone derivatives was investigated. The RP-HPLC experiments were carried out with acetonitrile-water and methanol-water mixtures as mobile phases and with two kinds of stationary phases of different polarity. The retention parameter, log k(w) was obtained by linear extrapolation of the log k retention to pure water as the mobile phase. The calculated log P-values were C log P, ACD/log P, R log P, A log P, LogKow, X log P and M log P. Statistically, highly significant correlations were found between log k(w) and the calculated log P-values with squared correlation coefficients ranging from 0.771 (with A log P) to 0.956 (with C log P). In addition, the comparative molecular similarity indices analysis (CoMSIA) method was also applied to correlate the log k(w) retention parameter of the compounds with their molecular fields. Statistically significant CoMSIA models were obtained between log k(w) and the hydrophobic and steric molecular fields of our compounds. The CoMSIA models describe how the structure of the nitrone derivatives influences (through hydrophobic and steric interactions with the stationary phase) the chromatographic retention of the compounds.

Ligand-based computer-aided pesticide design. A review of applications of the CoMFA and CoMSIA methodologies.

An overview is given of the CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis) methodologies that are established ligand-based molecular design tools widely used by medicinal and pesticide chemists. In the absence of a three-dimensional structure of the target biopolymer, CoMFA and CoMSIA often provide a practical solution to an otherwise intractable problem of proper characterization of ligand-receptor interactions. These techniques are especially important in agrochemistry, where the number of known molecular structures of pesticide targets is limited. The use of CoMFA and CoMSIA in the agrochemical field for modelling the interactions of insecticides, fungicides, herbicides and herbicide safeners with their target binding sites is illustrated by using some selected published work. The CoMFA and CoMSIA models developed have been used successfully to map the properties of unknown receptors, construct hypotheses for ligand-receptor interactions, optimize lead structures, design novel active compounds, and predict biological activities. The application of CoMFA by the present authors for deriving a binding site hypothesis for dichloroacetamide-type herbicide safeners is described in somewhat more detail.

[Fragment-based drug design using stereoisomers. A case study of analogues of the phenol group in the Bioster database]. / Fragmentum-alapú hatóanyagtervezés a bioizosztéria alkalmazásával. Esettanulmány: a fenolcsoport analogonjai a Bioster adatbázisban.

This case study examined various structural features of the 55 bioisosteric fragments of the phenol group registered in version 2002.1 of the Bioster database. The size, calculated lipophilicity and H-bond donor or acceptor character of the fragments were found to vary on a fairly wide scale. In most cases, molecular modelling calculations indicated similarities in the electrostatic potential maps of the fragments.