Systematic mining of generally recognized as safe (GRAS) flavor chemicals for bioactive compounds.

Bioactive food compounds can be both therapeutically and nutritionally relevant. Screening strategies are widely employed to identify bioactive compounds from edible plants. Flavor additives contained in the so-called FEMA GRAS (generally recognized as safe) list of approved flavoring ingredients is an additional source of potentially bioactive compounds. This work used the principles of molecular similarity to identify compounds with potential mood-modulating properties. The ability of certain GRAS molecules to inhibit histone deacetylase-1 (HDAC1), proposed as an important player in mood modulation, was assayed. Two GRAS chemicals were identified as HDAC1 inhibitors in the micromolar range, results similar to what was observed for the structurally related mood prescription drug valproic acid. Additional studies on bioavailability, toxicity at higher concentrations, and off-target effects are warranted. The methodology described in this work could be employed to identify potentially bioactive flavor chemicals present in the FEMA GRAS list.

Chemoinformatic analysis of GRAS (Generally Recognized as Safe) flavor chemicals and natural products.

Food materials designated as "Generally Recognized as Safe" (GRAS) are attracting the attention of researchers in their attempts to systematically identify compounds with putative health-related benefits. In particular, there is currently a great deal of interest in exploring possible secondary benefits of flavor ingredients, such as those relating to health and wellness. One step in this direction is the comprehensive characterization of the chemical structures contained in databases of flavoring substances. Herein, we report a comprehensive analysis of the recently updated FEMA GRAS list of flavoring substances (discrete chemical entities only). Databases of natural products, approved drugs and a large set of commercial molecules were used as references. Remarkably, natural products continue to be an important source of bioactive compounds for drug discovery and nutraceutical purposes. The comparison of five collections of compounds of interest was performed using molecular properties, rings, atom counts and structural fingerprints. It was found that the molecular size of the GRAS flavoring substances is, in general, smaller cf. members of the other databases analyzed. The lipophilicity profile of the GRAS database, a key property to predict human bioavailability, is similar to approved drugs. Several GRAS chemicals overlap to a broad region of the property space occupied by drugs. The GRAS list analyzed in this work has high structural diversity, comparable to approved drugs, natural products and libraries of screening compounds. This study represents one step towards the use of the distinctive features of the flavoring chemicals contained in the GRAS list and natural products to systematically search for compounds with potential health-related benefits.

Computational methods for the discovery of mood disorder therapies.

INTRODUCTION: Despite the significant progress, research is still needed to reveal details of the complex and dynamic chemical processes operating in the central nervous system (CNS) and their relationship to psychological effects such as mood disorders. The incidence of behavioral depression is widely spread worldwide, with an estimated 14.8 million adults diagnosed yearly in the United States alone. The efficacy of current antidepressants on 50 - 60% of patients, their slow onset of action and the prevalence of adverse side effects highlight the need for developing a new generation of improved antidepressants. Computational methods have the potential to aid in the discovery of mood modulators. AREAS COVERED: This review contains three main sections: historical evolution of marketed antidepressants, physicochemical and structural properties of antidepressant compounds reported in the ChEMBL database and recent efforts in the design and discovery of antidepressants using computational methods. The authors provide details of the computational methods employed, from chemoinformatic analyses to molecular modeling. EXPERT OPINION: While there have been numerous and important findings in depression research, the high cost and time spent on research into new therapies for brain disorders is a risky undertaking. Computational methodologies can be employed to speed up the discovery of new antidepressants and to detect new sources of chemical compounds with potential antidepressant activity. Compound collections containing compounds already approved in the pharmaceutical and food industries that cover the property space and complement the structural space of CNS drugs represent a promising starting point for the discovery of new antidepressant agents.

The effect of solvent interactions on alpha-, beta-, and gamma-cyclodextrin/flavor molecular inclusion complexes.

Three commonly used flavor industry solvents (propylene glycol, triacetin, and triethyl citrate) were tested for their capacity to interfere with the ability of alpha-, beta-, and gamma-cyclodextrin to form molecular inclusion complexes with flavors. Six flavor compounds (ethyl butyrate, ethyl heptanoate, l-menthol, methyl anthranilate, neral, and geranial) were measured by headspace gas chromatography above 2:1 water/ethanol containing appropriate additions of cyclodextrin and flavor solvent. The smallest and most polar solvent molecule represented by propylene glycol had the least effect on cyclodextrin/flavorant complex formation. In contrast, triacetin, intermediate in size among the three flavor diluents studied, had the greatest effect, even though, based on at least some computed molecular parameters, it appears to be more polar than triethyl citrate. The explanation for this apparent anomaly may lie in differences in the extent to which triacetin and triethyl citrate are able to interact with cyclodextrins by means of partial interaction with the hydrophobic cavities of the latter.