Biomedical subjects

Sorel Muresan

Publications and source records attributed to Sorel Muresan.

5 recordsLinked to original sources

PubMed2006

Identification of the volatile component(s) causing the characteristic foxy odor in various cultivars of Fritillaria imperialis L. (Liliaceae).

To identify the component(s) causing the foxy odor, characteristic for some Fritillaria imperialis cultivars, the headspace of flower bulbs was analyzed using gas chromatography-olfactometry (GC-O) and GC-mass spectrometry (GC-MS). Six Fritillaria species and cultivars were selected as follows: F. imperialis cv. Premier (very strong foxy odor), F. imperialis cv. Lutea (strong foxy odor), F. imperialis ssp. Inodora (no odor), Fritillaria eduardii (weak mousy odor), Fritillaria raddeana (no odor), and an F1 of F. imperialis Lutea x Inodora (weak foxy odor). Volatiles from these flower bulbs were accumulated on Tenax and injected into the GC by thermodesorption. The majority of the volatiles consisted of low molecular weight aliphatic compounds. GC-O revealed that the foxy odor was caused by a single component, identified as 3-methyl-2-butene-1-thiol on the basis of smell in GC-O analyses (two GC columns), mass spectra, and retention times. Chemical identification was substantiated by GC-O and GC-MS of an authentic standard of 3-methyl-2-butene-1-thiol, prepared by organic synthesis.

Butanes↗

PubMed2005

Database mining for pKa prediction.

The acid dissociation constant (pKa) is the key parameter to define the extent of ionization of a drug molecule and is used for ADME properties evaluation via the pH-dependent distribution coefficient, logD. We present a method for pKa prediction using a predefined reference database and structural fingerprints based on a multilevel neighborhoods description of the ionizable atom(s). This database mining approach is suitable for screening large compound collections for HTS compound prioritization and external compound acquisition. In addition to pKa prediction it provides medicinal chemists rapid access to already available pKa measurements and hints for manipulating the chemical structure to increase or decrease pKa.

Chemical Phenomena↗

PubMed2002

FTIR spectra of whey and casein hydrolysates in relation to their functional properties.

Mid-infrared spectra of whey and casein hydrolysates were recorded using Fourier transform infrared (FTIR) spectroscopy. Multivariate data analysis techniques were used to investigate the capacity of FTIR spectra to classify hydrolysates and to study the ability of the spectra to predict bitterness, solubility, emulsifying, and foaming properties of hydrolysates. Principal component analysis revealed that hydrolysates prepared from different protein sources or with different classes of proteolytic enzymes are distinguished effectively on basis of their FTIR spectra. Moreover, multivariate regression analysis showed satisfactory to good prediction of functional parameters; the coefficient of determination (R(2)) varied from 0.60 to 0.92. The accurate prediction of bitterness and emulsion forming ability of hydrolysates by using only one uncomplicated and rapid analytical method has not been reported before. FTIR spectra in combination with multivariate data analysis proved to be valuable in protein hydrolysate fingerprinting and can be used as an alternative for laborious functionality measurements.

Caseins↗

PubMedDate not supplied

"In-house likeness": comparison of large compound collections using artificial neural networks.

Binary classification models able to discriminate between data sets of compounds are useful tools in a range of applications from compound acquisition to library design. In this paper we investigate the ability of artificial neural networks to discriminate between compound collections from various sources aiming at developing an "in-house likeness" scoring scheme (i.e. in-house vs external compounds) for compound acquisition. Our analysis shows atom-type based Ghose-Crippen fingerprints in combination with artificial neural networks to be an efficient way to construct such filters. A simple measure of the chemical overlap between different compound collections can be derived using the output scores from the neural net models.

Combinatorial Chemistry Techniques↗

PubMedDate not supplied

Multifingerprint based similarity searches for targeted class compound selection.

Molecular fingerprints are widely used for similarity-based virtual screening in drug discovery projects. In this paper we discuss the performance and the complementarity of nine two-dimensional fingerprints (Daylight, Unity, AlFi, Hologram, CATS, TRUST, Molprint 2D, ChemGPS, and ALOGP) in retrieving active molecules by similarity searching against a set of query compounds. For this purpose, we used biological data from HTS screening campaigns of four protein families (GPCRs, kinases, ion channels, and proteases). We have established threshold values for the similarity index (Tanimoto index) to be used as starting points for similarity searches. Based on the complementarities between the selections made by using different fingerprints we propose a multifingerprint approach as an efficient tool to balance the strengths and weaknesses of various fingerprints.

Journal Article↗