Computational strategies for the discovery of biological functions of health foods, nutraceuticals and cosmeceuticals: a review

Scientific and consumer interest in healthy foods (also known as functional foods), nutraceuticals and cosmeceuticals has increased in the recent years, leading to an increased presence of these products in the market. However, the regulations across different countries that define the type of claims that may be made, and the degree of evidence required to support these claims, are rather inconsistent. Moreover, there is also controversy on the effectiveness and biological mode of action of many of these products, which should undergo an exhaustive approval process to guarantee the consumer rights. Computational approaches constitute invaluable tools to facilitate the discovery of bioactive molecules and provide biological plausibility on the mode of action of these products. Indeed, methodologies like QSAR, docking or molecular dynamics have been used in drug discovery protocols for decades and can now aid in the discovery of bioactive food components. Thanks to these approaches, it is possible to search for new functions in food constituents, which may be part of our daily diet, and help to prevent disorders like diabetes, hypercholesterolemia or obesity. In the present manuscript, computational studies applied to this field are reviewed to illustrate the potential of these approaches to guide the first screening steps and the mechanistic studies of nutraceutical, cosmeceutical and functional foods.We gratefully acknowledged the financial support of the Agencia Valenciana de la Investigación (AVI, https://innoavi.es/en/) by its program Innodocto (Reference number INNTAL32/19/002). SJB acknowledges the funding assistance from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 893810.Peer reviewe

Discovery of 2-aryl and 2-pyridinylbenzothiazoles endowed with antimicrobial and aryl hydrocarbon receptor agonistic activities

Benzothiazole is a privileged scaffold in medicinal chemistry present in diverse bioactive compounds with multiple pharmacological applications such as analgesic, anticonvulsant, antidiabetic, anti-inflammatory, anticancer and radioactive amyloidal imagining agents. We reported in this work the study of sixteen functionalized 2-aryl and 2-pyridinylbenzothiazoles as antimicrobial agents and as aryl hydrocarbon receptor (AhR) modulators. The antimicrobial activity against Gram-positive (S. aureus and M. luteus) and Gram-negative (P. aeruginosa, S. enterica and E. coli) pathogens yielded MIC ranging from 3.13 to 50 μg/mL and against the yeast C. albicans, the benzothiazoles displayed MIC from 12.5 to 100 μg/mL. All compounds showed promising antibiofilm activity against S. aureus and P. aeruginosa. The arylbenzothiazole 12 displayed the greatest biofilm eradication in S. aureus (74%) subsequently verified by fluorescence microscopy. The ability of benzothiazoles to modulate AhR expression was evaluated in a cell-based reporter gene assay. Six benzothiazoles (7, 8-10, 12, 13) induced a significant AhR-mediated transcription and interestingly compound 12 was also the strongest AhR-agonist identified. Structure-activity relationships are suggested herein for the AhR-agonism and antibiofilm activities. Furthermore, in silico predictions revealed a good ADMET profile and druglikeness for the arylbenzothiazole 12 as well as binding similarities to AhR compared with the endogenous agonist FICZ.protected - PROTECTion against Endocrine Disruptors; Detection, mixtures, health effects, risk assessment and communicatio

Comparative Binding Study of Gliptins to Bacterial DPP4-like Enzymes for the Treatment of Type 2 Diabetes Mellitus (T2DM)

The role of the gut microbiota and its interplay with host metabolic health, particularly in the context of type 2 diabetes mellitus (T2DM) management, is garnering increasing attention. Dipeptidyl peptidase 4 (DPP4) inhibitors, commonly known as gliptins, constitute a class of drugs extensively used in T2DM treatment. However, their potential interactions with gut microbiota remain poorly understood. In this study, we employed computational methodologies to investigate the binding affinities of various gliptins to DPP4-like homologs produced by intestinal bacteria. The 3D structures of DPP4 homologs from gut microbiota species, including Segatella copri, Phocaeicola vulgatus, Bacteroides uniformis, Parabacteroides merdae, and Alistipes sp., were predicted using computational modeling techniques. Subsequently, molecular dynamics simulations were conducted for 200 ns to ensure the stability of the predicted structures. Stable structures were then utilized to predict the binding interactions with known gliptins through molecular docking algorithms. Our results revealed binding similarities of gliptins toward bacterial DPP4 homologs compared to human DPP4. Specifically, certain gliptins exhibited similar binding scores to bacterial DPP4 homologs as they did with human DPP4, suggesting a potential interaction of these drugs with gut microbiota. These findings could help in understanding the interplay between gliptins and gut microbiota DPP4 homologs, considering the intricate relationship between the host metabolism and microbial communities in the gut

Supplemental information Comparative Binding Study of Gliptins to Bacterial DPP4-like Enzymes for the Treatment of Type 2 Diabetes Mellitus (T2DM)

Table S1.Comparative analysis of residues within binding pocket sections across 5 DPP4 homologs and the human variant. Colors visually represent aminoacids properties: pink indicates non-polar aliphatic residues, green represents polar uncharged residues, orange denotes aromatic R-groups, red signifies positively charged residues, and blue indicates negatively charged residues. Figure S1. 2D interaction maps of alogliptin predicted best pose with the six different DPP4 homologues studied. Figure S2. 2D interaction maps of linagliptin predicted best pose with the six different DPP4 homologues studied. Figure S3. 2D interaction maps of saxagliptin predicted best pose with the six different DPP4 homologues studied. Figure S4. 2D interaction maps of teneligliptin predicted best pose with the six different DPP4 homologues studied. Figure S5. 2D interaction maps of vildagliptin predicted best pose with the six different DPP4 homologues studied.Peer reviewe

Structure-Based Design and Synthesis of Stapled 10Panx1 Analogues for Use in Cardiovascular Inflammatory Diseases

Following a rational design, a series of macrocyclic ("stapled") peptidomimetics of10Panx1, the most established peptide inhibitor of Pannexin1 (Panx1) channels, were developed and synthesized. Two macrocyclic analoguesSBL-PX1-42andSBL-PX1-44outperformed the linear native peptide. Duringin vitroadenosine triphosphate (ATP) release and Yo-Pro-1 uptake assays in a Panx1-expressing tumor cell line, both compounds were revealed to be promising bidirectional inhibitors of Panx1 channel function, able to induce a two-fold inhibition, as compared to the native10Panx1 sequence. The introduction of triazole-based cross-links within the peptide backbones increased helical content and enhancedin vitroproteolytic stability in human plasma (>30-fold longer half-lives, compared to10Panx1). In adhesion assays, a "double-stapled" peptide,SBL-PX1-206inhibited ATP release from endothelial cells, thereby efficiently reducing THP-1 monocyte adhesion to a TNF-α-activated endothelial monolayer and making it a promising candidate for futurein vivoinvestigations in animal models of cardiovascular inflammatory disease