The Acid/Base Profile of a Large Food Chemical Database

The Acid/Base Characterization of Molecules with Epigenetic Activity

The acidic and basic functional groups in a molecule strongly influence its physicochemical properties, affinity for a macromolecule, pharmacokinetics, and toxicity. For instance, basicity has been correlated with molecular promiscuity, hERG blockade, and phospholipidosis. Nonetheless, no systematic characterization of the acid/base profile of epigenomic databases has been reported. This study describes an analysis of the acidic ionization constant distribution of a library of 7820 compounds with reported activity against epigenetic targets. Furthermore, the epigenomics database's acid/base profile was compared to the reference libraries of food chemicals, natural products, and approved drugs. It was found that the acid/base profile of histone lysine demethylase ligands is more similar to previously approved drugs, and histone acetyltransferase ligands have acidic and basic functional groups largely found in food chemicals and natural products; this support the potential of these libraries for finding new epigenetic inhibitors.

Cheminformatics to Characterize Pharmacologically Active Natural Products

Natural products have a significant role in drug discovery. Natural products have distinctive chemical structures that have contributed to identifying and developing drugs for different therapeutic areas. Moreover, natural products are significant sources of inspiration or starting points to develop new therapeutic agents. Natural products such as peptides and macrocycles, and other compounds with unique features represent attractive sources to address complex diseases. Computational approaches that use chemoinformatics and molecular modeling methods contribute to speed up natural product-based drug discovery. Several research groups have recently used computational methodologies to organize data, interpret results, generate and test hypotheses, filter large chemical databases before the experimental screening, and design experiments. This review discusses a broad range of chemoinformatics applications to support natural product-based drug discovery. We emphasize profiling natural product data sets in terms of diversity; complexity; acid/base; absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties; and fragment analysis. Novel techniques for the visual representation of the chemical space are also discussed.

Analysis of Nuisance Substructures and Aggregators in a Comprehensive Database of Food Chemical Compounds

The mechanistic understanding of the biological effects of foods involves the testing of food compounds in biochemical and biological assays. Positive results in these assays can be artifactual due to some properties of the compound: namely chemical reactivity, membrane disruption, redox cycling, etc., or through the formation of colloidal aggregates. Within the drug discovery field, a wide set of so-called "nuisance" filters have been developed to identify substructures prone to assay artifacts and/or promiscuity, e.g., the pan-assay interference compounds (PAINS) and others. In the subarea of natural products, a similar concept is the so-called invalid metabolic panaceas (IMPs). Finally, tools to identify putative aggregators have also been developed. Here, we analyzed the presence of nuisance substructures, IMPs, and aggregators in a large database of food compounds (the FooDB), which should be useful to the researchers working in the field, in order to be aware of possible artifact/promiscuity issues in their assays.

Characteristics of Biopeptides Released In Silico from Collagens Using Quantitative Parameters

The potential of collagens to release biopeptides was evaluated using the BIOPEP-UWM-implemented quantitative criteria including the frequency of the release of fragments with a given activity by selected enzyme(s) (AE), relative frequency of release of fragments with a given activity by selected enzyme(s) (W), and the theoretical degree of hydrolysis (DHt). Cow, pig, sheep, chicken, duck, horse, salmon, rainbow trout, goat, rabbit, and turkey collagens were theoretically hydrolyzed using: stem bromelain, ficin, papain, pepsin, trypsin, chymotrypsin, pepsin+trypsin, and pepsin+trypsin+chymotrypsin. Peptides released from the collagens having comparable AE and W were estimated for their likelihood to be bioactive using PeptideRanker Score. The collagens tested were the best sources of angiotensin I-converting enzyme (ACE) and dipeptidyl peptidase IV (DPP-IV) inhibitors. AE and W values revealed that pepsin and/or trypsin were effective producers of such peptides from the majority of the collagens examined. Then, the SwissTargetPrediction program was used to estimate the possible interactions of such peptides with enzymes and proteins, whereas ADMETlab was applied to evaluate their safety and drug-likeness properties. Target prediction revealed that the collagen-derived peptides might interact with several human proteins, especially proteinases, but with relatively low probability. In turn, their bioactivity may be limited by their short half-life in the body.

Analysis of the Acid/Base Profile of Natural Products from Different Sources

For many years drug discovery and other areas in chemistry have successfully relied on natural products. Recent advances in computational methods have made possible to study the chemical space of natural products from different sources. Ionizable acidic and basic functional groups heavily influence physicochemical properties and thus a molecule's absorption, distribution, metabolism, excretion, and toxicity characteristics as well as their affinity for biological targets. This work reports the generation and critical comparison of the acid/base profiles of ten chemical databases including seven natural products sets from different origins, a set of semisynthetic compounds, a collection of approved drugs, and a compendium of food chemicals. Similarities were found in the proportion of the main charge state categories among the natural products databases with few differences in their pK_a distributions. Clear differences were observed between natural products and the approved drugs and semi-synthetic natural products databases, whereas natural products share some trends with the food chemical database. We noted that the natural products collections comprise around 45 % of neutral compounds. The proportion of single acids was approximately twice that found for FDA drugs, and they demonstrated a similar distribution of pK_a values. In contrast to drugs, only 5 % of compounds among the natural products sets had a single basic group. Likewise, simple ampholytes were less prevalent in the natural products databases relative to drugs.