Virtual screening and rational design of antioxidant peptides based on tryptophyllin L structures isolated from the Litoria rubella frog

Discovery of natural antioxidants has been carried out for decades relying mainly on experimental approaches that are commonly associated with time and cost demanding biochemical assays. The maturation of quantitative structure activity relationship (QSAR) modelling has provided an alternative approach for searching and designing antioxidant compounds with alleviated costs. As a contribution to this approach, this work aimed to establish a fragment-based 3D-QSAR procedure to discover and design potential antioxidants based on tryptophyllin L structures isolated from the red tree frog Litoria rubella. A force field and a Gaussian 3D-QSAR model were built to screen for potential antioxidants from tripeptide fragments covering all sequences of tryptophyllin L database. Among those, PWY(NH₂ ) corresponding tryptophyllin L 4.1 was predicted to have the highest 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) radical cation (ABTS⁺ ·) scavenging capability. Two newly designed peptides PYW and PYW(NH₂ ) together with PWY(NH₂ ), tryptophyllin L 4.1, and the reference peptide PWY were synthesized and subjected to two antioxidant assays including ABTS scavenging and ferric reducing antioxidant power assays. Although the experimental TEAC values of the five peptides were roughly similar to those from predictions, the activity order was not in agreement with the predictions. The dissimilarities were accounted by the difference in the experimental procedures, the deviation of modelling regression, and the synergetic effect of structural and experimental features. The ABTS radical scavenging assays revealed that all the tested peptides were strong ABTS⁺ · scavengers with the antioxidant capabilities approximately twice as high as trolox and higher than glutathione. The ferric reducing activities of the peptides were, on the other hand, much weaker than that of trolox suggesting different antioxidant mechanisms inserted by trolox and the peptides. This work was a demonstration that 3D-QSAR methods can be employed in conjunction with experimental methods to effectively detect and design antioxidant peptides.

Leading individual features of antioxidant systematically classified by the ORAC assay and its single electron transfer and hydrogen atom transfer reactivities; analyzing ALS therapeutic drug Edaravone

Many natural compounds mop up radicals and limit radical reactions and may prove useful in reducing or preventing oxidative stress-related diseases in vivo. Several assays have been developed to measure antioxidant or anti-radical activity. Here, we measured the anti-radical activities of representative antioxidants using different assays. The oxygen radical absorption capacity (ORAC) assay has two mechanistic stages. We classified antioxidant behavior using two characteristic values thought to be related to the two stages - peroxyl radical formation time (lag time) and fluorescein annihilation rate (k _obs) - by applying Voronoi polyhedral division. We focused on four class-representative antioxidants, Trolox ®, vitamin C, l-cysteine, and 2,6-di‑tert‑butyl‑p-cresol, and compared their characteristic activities with those of edaravone. Our analysis indicates that edaravone is in the same group as cysteine and may function via a similar mechanism. Our results suggest that analyzing lag time and k _obs is a useful method to characterize antioxidants.

Effect of Cooking on Protein Digestion and Antioxidant Activity of Different Legume Pastes

Legumes are protein-rich foods that can be used to prepare pastes or pureed foods suitable for babies and the elderly. The aims of this study were the characterization of different legume pastes (from soybean, lentil, and pea) subjected to three processing methods (ordinary cooking, pressure cooking, and microwave) and the evaluation of protein digestion and antioxidant activity during simulated gastrointestinal digestion (GID). The different cooking methods of legumes led to differences in the physicochemical properties of the pastes, as well as on the textural and viscoelastic characteristics, except for soybean samples, despite all the pastes presenting elastic properties and weak gel behavior. Cooking followed by GID improved the protein digestibility and antioxidant activity of the legumes, which was attributed to released peptides and amino acids more than free phenolics. However, the fate and extent at each digestion stage was different according to the legume type and cooking method, as it would be influenced by the matrix structure and interaction between components. This work has expanded knowledge about the properties, digestibility, and antioxidant activity of different cooked legumes for a future design of pastes.

The Radical-Scavenging Activity of a Purified and Sequenced Peptide from Lactic Acid Fermentation of Thunnus albacares By-Products

Yellowfin tuna by-products (Thunnus albacares) were processed to produce radical-scavenging peptides from hydrolysis by lactic acid fermentation (LAF) with Lactobacillus plantarum, papaya fruit (Carica papaya), and molasses as a carbon source for 72 h. A 15-kDa peptide was purified; after de novo sequencing, it was determined that fragments are rich in hydrophobic and neutral amino acids. The results suggest this effect is mainly to the hydrophobicity of the amino acids in their sequence. Further work is on progress to assess the ability of peptides to provide stability in lipids or in other types of samples sensitive to the action of free radicals.

Quantitative Structure-Activity Relationship Study of Antioxidant Tripeptides Based on Model Population Analysis

Due to their beneficial effects on human health, antioxidant peptides have attracted much attention from researchers. However, the structure-activity relationships of antioxidant peptides have not been fully understood. In this paper, quantitative structure-activity relationships (QSAR) models were built on two datasets, i.e., the ferric thiocyanate (FTC) dataset and ferric-reducing antioxidant power (FRAP) dataset, containing 214 and 172 unique antioxidant tripeptides, respectively. Sixteen amino acid descriptors were used and model population analysis (MPA) was then applied to improve the QSAR models for better prediction performance. The results showed that, by applying MPA, the cross-validated coefficient of determination (Q²) was increased from 0.6170 to 0.7471 for the FTC dataset and from 0.4878 to 0.6088 for the FRAP dataset, respectively. These findings indicate that the integration of different amino acid descriptors provide additional information for model building and MPA can efficiently extract the information for better prediction performance.