Proteins and Peptides Studied In Silico and In Vivo for the Treatment of Diabetes Mellitus: A Systematic Review DOI Open Access
Isaiane Medeiros, Ana Francisca Teixeira Gomes,

Emilly Guedes Oliveira e Silva

и другие.

Nutrients, Год журнала: 2024, Номер 16(15), С. 2395 - 2395

Опубликована: Июль 24, 2024

Bioinformatics has expedited the screening of new efficient therapeutic agents for diseases such as diabetes mellitus (DM). The objective this systematic review (SR) was to understand naturally occurring proteins and peptides studied in silico subsequently reevaluated vivo treating DM, guided by question: which or have been treatment mellitus? RS protocol registered International Prospective Register Systematic Reviews database. Articles meeting eligibility criteria were selected from PubMed, ScienceDirect, Scopus, Web Science, Virtual Health Library (VHL), EMBASE databases. Five studies that investigated analyzed selected. Risk bias assessment conducted using adapted Strengthening Reporting Empirical Simulation Studies (STRESS) tool. A diverse range assessed and/or had a natural origin corresponding reevaluation demonstrated reductions glycemia insulin, morphological enhancements pancreatic β cells, alterations gene expression markers associated with DM. outlined offer crucial insights into strategies along promising leads novel future trials.

Язык: Английский

Peptides Evaluated In Silico, In Vitro, and In Vivo as Therapeutic Tools for Obesity: A Systematic Review DOI Open Access
Ana Aguiar, Wendjilla Fortunato de Medeiros, Juliana Kelly da Silva-Maia

и другие.

International Journal of Molecular Sciences, Год журнала: 2024, Номер 25(17), С. 9646 - 9646

Опубликована: Сен. 6, 2024

Bioinformatics has emerged as a valuable tool for screening drugs and understanding their effects. This systematic review aimed to evaluate whether in silico studies using anti-obesity peptides targeting therapeutic pathways obesity, when subsequently evaluated vitro vivo, demonstrated effects consistent with those predicted the computational analysis. The was framed by question: “What or proteins have been used treat obesity studies?” structured according acronym PECo. protocol developed registered PROSPERO (CRD42022355540) accordance PRISMA-P, all stages of adhered these guidelines. Studies were sourced from following databases: PubMed, ScienceDirect, Scopus, Web Science, Virtual Heath Library, EMBASE. search strategies resulted 1015 articles, which, based on exclusion inclusion criteria, 7 included this review. identified originated various sources including bovine alpha-lactalbumin cocoa seed (Theobroma cacao L.), chia (Salvia hispanica rice bran (Oryza sativa), sesame (Sesamum indicum sea buckthorn flour (Hippophae rhamnoides), adzuki beans (Vigna angularis). All articles underwent vivo reassessment molecular docking methodology studies. Among review, 46.15% classified having an “uncertain risk bias” six thirteen criteria evaluated. primary target investigated pancreatic lipase (n = 5), enzyme demonstrating inhibition, finding supported both vivo. Additionally, other PPARγ PPARα agonists 2). Notably, exhibited different mechanisms action lipid metabolism adipogenesis. findings underscore effectiveness simulation tool, providing crucial insights guiding investigations discovery novel peptides.

Язык: Английский

Процитировано

5

Identifying novel drug targets with computational precision DOI

Rutwij Dave,

P Giordano,

Sakshi Roy

и другие.

Advances in pharmacology, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Anti‐obesity peptides from food: Production, evaluation, sources, and commercialization DOI Creative Commons

Mona Hajfathalian,

Sakhi Ghelichi, Charlotte Jacobsen

и другие.

Comprehensive Reviews in Food Science and Food Safety, Год журнала: 2025, Номер 24(2)

Опубликована: Март 1, 2025

The global obesity epidemic has heightened interest in natural solutions, with anti-obesity peptides emerging as promising candidates. Derived from food sources such plants, algae, marine organisms, and products like milk eggs, these combat through various mechanisms but face challenges production scalability. aim of this review is to explore their sources, mechanisms, measurement, synthesis methods, including innovative approaches de novo synthesis, proteomics, bioinformatics. Its unique contribution lies critically analyzing the current state research while highlighting novel techniques practical relevance addressing commercialization challenges, offering valuable insights for advancing peptide development. Diverse methods assessing properties are discussed, encompassing both vitro vivo experimental approaches, well alternatives. also explores integration cutting-edge technologies potential revolutionize scalability cost-effectiveness. Key findings assert that despite great fight against advances identification analysis, scalability, regulatory hurdles, bioavailability issues, high costs, consumer appeal persist. Future should use bioinformatics tools advanced screening identify design enhanced efficacy bioavailability, efficient cost-effective extraction purification sustainable practices utilizing byproducts industry, containing isolated versus whole materials clinical settings.

Язык: Английский

Процитировано

0

Evaluation of antiobesogenic properties of fermented foods: In silico insights DOI Creative Commons
Abdullahi Adekilekun Jimoh, Janet Adeyinka Adebo

Journal of Food Science, Год журнала: 2025, Номер 90(3)

Опубликована: Март 1, 2025

Obesity prevalence has steadily increased over the past decades. Standard approaches, such as energy expenditure, lifestyle changes, a balanced diet, and use of specific drugs, are conventional strategies for preventing or treating disease its associated complications. Fermented foods their subsequent bioactive constituents now believed to be novel strategy that can complement already existing approaches managing this disease. Recent developments in systems biology bioinformatics have made it possible model simulate compounds interactions. The adoption silico models contributed discovery fermented product targets helped testing hypotheses regarding mechanistic impact underlying functions food components. From studies explored, key findings suggest affect adipogenesis, lipid metabolism, appetite regulation, gut microbiota composition, insulin resistance, inflammation related obesity, which could lead new ways treat these conditions. These outcomes were linked probiotics, prebiotics, metabolites, complex substances produced during fermentation. Overall, show promise innovative tools obesity management by influencing metabolic pathways overall health.

Язык: Английский

Процитировано

0

Artificial intelligence in anti-obesity drug discovery: unlocking next-generation therapeutics DOI Creative Commons

Amit Gangwal,

Antonio Lavecchia

Drug Discovery Today, Год журнала: 2025, Номер unknown, С. 104333 - 104333

Опубликована: Март 1, 2025

Obesity, a multifactorial disease linked to severe health risks, requires innovative treatments beyond lifestyle changes and current medications. Existing anti-obesity drugs face limitations regarding efficacy, side effects, weight regain high costs. Artificial intelligence (AI) is emerging as pivotal tool in drug discovery, expediting the identification of novel candidates optimizing treatment strategies. This review examines AI's potential developing next-generation therapeutics, with focus on glucagon-like peptide-1 receptor agonists (GLP-1 RAs) their role discovering peptides. Additionally, it explores integration challenges offers future perspectives leveraging AI reshape landscape discovery.

Язык: Английский

Процитировано

0

Proteins and Peptides Studied In Silico and In Vivo for the Treatment of Diabetes Mellitus: A Systematic Review DOI Open Access
Isaiane Medeiros, Ana Francisca Teixeira Gomes,

Emilly Guedes Oliveira e Silva

и другие.

Nutrients, Год журнала: 2024, Номер 16(15), С. 2395 - 2395

Опубликована: Июль 24, 2024

Bioinformatics has expedited the screening of new efficient therapeutic agents for diseases such as diabetes mellitus (DM). The objective this systematic review (SR) was to understand naturally occurring proteins and peptides studied in silico subsequently reevaluated vivo treating DM, guided by question: which or have been treatment mellitus? RS protocol registered International Prospective Register Systematic Reviews database. Articles meeting eligibility criteria were selected from PubMed, ScienceDirect, Scopus, Web Science, Virtual Health Library (VHL), EMBASE databases. Five studies that investigated analyzed selected. Risk bias assessment conducted using adapted Strengthening Reporting Empirical Simulation Studies (STRESS) tool. A diverse range assessed and/or had a natural origin corresponding reevaluation demonstrated reductions glycemia insulin, morphological enhancements pancreatic β cells, alterations gene expression markers associated with DM. outlined offer crucial insights into strategies along promising leads novel future trials.

Язык: Английский

Процитировано

0