To identify the component(s) causing the foxy odor, characteristic for some Fritillaria imperialis cultivars, the headspace of flower bulbs was analyzed using gas chromatographyolfactometry (GC-O) and GCmass 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

Block-milk or white crumb is an intermediate product used in the manufacture of white chocolate and milk chocolate and it is produced from a mixture of concentrated milk and sugar. Volatile compounds of block-milk samples at different stages in the manufacturing process were investigated by dynamic headspace GC-MS. The changes in aroma profiles during processing were evaluated using similarity indices and a multidimensional scaling technique. These

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

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

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

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

Natural compounds are evolutionary selected and prevalidated by Nature, displaying a unique chemical diversity and a corresponding diversity of biological activities. These features make them highly interesting for studies of chemical biology, and in the pharmaceutical industry for development of new leads. Of utmost importance, for the discovery of new biologically active compounds, is the identification and charting of the corresponding biologically

The last two years have seen a dramatic expansion in public cheminformatics, as exemplified by the approximate five-fold growth of PubChem from over 50 contributing data sources. Consequently, medicinal chemists who were hitherto limited to commercial databases now also have access to public sources that they can download and/or query directly over the Web. The range of public sources, particularly where they link out to structured bioinformatic

Addressing drug-like/lead-like properties of biologically active small molecules early in a lead generation program is the current paradigm within the drug discovery community. Lipinski's rule of five has become the most commonly used tool to assess the relationship between structures and drug-like properties. Sixty percent of the 126 140 unique compounds in The Dictionary of Natural Products had no violations of Lipinski's rule of five. We have