Rodríguez Longarela Natalia, Paredes Ramos Maria, López Vilariño Jose Manuel
METMED Group, Chemistry Department, University of A Coruña, A Coruña, Spain.
Hijos de Rivera SAU, A Coruña, Spain.
Crit Rev Food Sci Nutr. 2025;65(18):3476-3495. doi: 10.1080/10408398.2024.2367571. Epub 2024 Jun 22.
Bioactive peptides from vegetal sources have been shown to have functional properties as anti-inflammatory, antioxidant, antihypertensive or antidiabetic capacity. For this reason, they have been proposed as an interesting and promising alternative to improve human health. In recent years, the numerous advances in the bioinformatics field for in silico prediction have speeded up the discovery of bioactive peptides, also reducing the associated costs when using an integrated approach between the classical and bioinformatics discovery. This review aims to provide an overview of the evolution, limitations and latest advances in the field of bioinformatics and computational tools, and specifically make a critical and comprehensive insight into computational techniques used to study the mechanism of interaction that allows the explanation of plant bioactive peptide functionality. In particular, molecular docking is considered key to explain the different functionalities that have been previously identified. The assumptions to simplify such a high complex environment implies a degree of uncertainty that can only be guaranteed and validated by or studies, however, the combination of databases, software and bioinformatics applications with the classical approach has become a promising procedure for the study of bioactive peptides.
植物源生物活性肽已被证明具有抗炎、抗氧化、抗高血压或抗糖尿病等功能特性。因此，它们被认为是改善人类健康的一种有趣且有前景的替代物。近年来，生物信息学领域在计算机模拟预测方面的众多进展加快了生物活性肽的发现，同时在采用经典方法与生物信息学发现相结合的综合方法时，也降低了相关成本。本综述旨在概述生物信息学和计算工具领域的发展、局限性和最新进展，特别是对用于研究相互作用机制的计算技术进行批判性和全面的洞察，从而解释植物生物活性肽的功能。特别是，分子对接被认为是解释先前已确定的不同功能的关键。简化如此高度复杂环境的假设意味着一定程度的不确定性，而这只能通过实验或临床研究来保证和验证，然而，数据库、软件和生物信息学应用与经典方法的结合已成为研究生物活性肽的一种有前景的方法。
