Bioactivity of Hydrolysates Obtained from Chicken Egg Ovalbumin Using Artichoke (Cynara scolymus L.) Proteases

The aim of this work was to obtain chicken egg ovalbumin hydrolysates using aspartic proteinases present in extracts from the artichoke flower (Cynara scolymus L.) and evaluate their antioxidant, antimicrobial, and angiotensin I-converting enzyme (ACE) inhibitory activity in vitro. Hydrolysis time and molecular weight (<3 kDa) had a significant influence on the hypertensive and antioxidant activity of the hydrolysates. The <3 kDa fraction of the 16 h hydrolysate had an ACE inhibitory activity with an IC₅₀ of 64.06 µg peptides/mL. The fraction <3 kDa of ovalbumin hydrolysate at 2 h of hydrolysis showed a DPPH radical scavenging activity of 30.27 µM of Trolox equivalents/mg peptides. The fraction <3 kDa of the hydrolysate of 16 h had an ABTS⁺ caption activity of 4.30 mM of Trolox equivalents/mg peptides. The fraction <3 kDa of the hydrolysate of 2 h had an iron (II) chelating activity of 32.18 µg peptides/mL. From the peptide sequences identified in the hydrolysates, we detected four peptides (from the BIOPEP database) that were already in their bioactive form (IAAEVYEHTEGSTTSY, HLFGPPGKKDPV, PIAAEVYEHTEGSTTSY, and YAEERYPIL), and are reported to display antioxidant and ACE inhibitory activity.

Selective in vitro and in silico butyrylcholinesterase inhibitory activity of diterpenes and rosmarinic acid isolated from Perovskia atriplicifolia Benth. and Salvia glutinosa L

Cholinesterase inhibition is one of the most treatment strategies against Alzheimer's disease (AD) where metal accumulation is also strongly associated with pathology of the disease. In the current study, we assessed inhibitory effect against acetyl- (AChE) and butyrylcholinesterase (BChE) and metal-chelating capacity of twelve diterpenes: arucadiol, miltirone, tanshinone IIa, 1-oxomiltirone, cryptotanshinone, 1,2-didehydromiltirone, 1,2-didehydrotanshinone IIa, 1β-hydroxycryptotanshinone, 15,16-dihydrotanshinone, tanshinone I, isotanshinone II, 1(S)-hydroxytanshinone IIa, and rosmarinic acid, isolated from Perovskia atriplicifolia and Salvia glutinosa. The compounds were tested at 10 μg/mL using ELISA microtiter assays against AChE and BChE. QSAR and molecular docking studies have been also performed on the active compounds. All of the compounds showed higher [e.g., IC50 = 1.12 ± 0.07 μg/mL for 1,2-didehydromiltirone, IC50 = 1.15 ± 0.07 μg/mL for cryptotanshinone, IC50 = 1.20 ± 0.03 μg/mL for arucadiol, etc.)] or closer [1,2-didehydrotanshinone IIa (IC50 = 5.98 ± 0.49 μg/mL) and 1(S)-hydroxytanshinone IIa (IC50 = 5.71 ± 0.27 μg/mL)] inhibition against BChE as compared to that of galanthamine (IC50 = 12.56 ± 0.37 μg/mL), whereas only 15,16-dihydrotanshinone moderately inhibited AChE (65.17 ± 1.39%). 1,2-Didehydrotanshinone IIa (48.94 ± 0.26%) and 1(S)-hydroxytanshinone IIa (47.18 ± 5.10%) possessed the highest metal-chelation capacity. The present study affords an evidence for the fact that selective BChE inhibitors should be further investigated as promising candidate molecules for AD therapy.

Topological structural alerts modulations of mammalian cell mutagenicity for halogenated derivatives

Genotoxicity is a key toxicity endpoint for current regulatory requirements regarding new and existing chemicals. However, genotoxicity testing is time-consuming and costly, and involves the use of laboratory animals. This has motivated the development of computational approaches, designed to predict genotoxicity without the need to conduct laboratory tests. Currently, many existing computational methods, like quantitative structure-activity relationship (QSAR) models, provide limited information about the possible mechanisms involved in mutagenicity or predictions based on structural alerts (SAs) do not take statistical models into account. This paper describes an attempt to address this problem by using the TOPological Substructural MOlecular Design (TOPS-MODE) approach to develop and validate improved QSAR models for predicting the mutagenicity of a range of halogenated derivatives. Our most predictive model has an accuracy of 94.12%, exhibits excellent cross-validation and external set statistics. A reasonable interpretation of the model in term of SAs was achieved by means of bond contributions to activity. The results obtained led to the following conclusions: primary halogenated derivatives are more mutagenic than secondary ones; and substitution of chlorine by bromine increases mutagenicity while polyhalogenation decreases activity. The paper demonstrates the potential of the TOPS-MODE approach in developing QSAR models for identifying structural alerts for mutagenicity, combining high predictivity with relevant mechanistic interpretation.