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Why and How to Dig into Plant Metabolite–Protein Interactions

生物 代谢组 代谢物 计算生物学 功能(生物学) 植物生长 代谢组学 相互作用体 生物化学 生物技术 生物信息学 细胞生物学 植物 基因
作者
Jhon Venegas‐Molina,Francisco Javier Molina‐Hidalgo,Elke Clicque,Alain Goossens
出处
期刊:Trends in Plant Science [Elsevier]
卷期号:26 (5): 472-483 被引量:30
标识
DOI:10.1016/j.tplants.2020.12.008
摘要

Plants are treasure troves of bioactive metabolites that not only regulate nearly all fundamental processes such as growth, reproduction, and environmental responses, but also nourish pharmaceutical and industrial applications for humankind. To date, however, we have only scratched the surface in the chemical characterization of plants. Recent studies reported unexpected roles of metabolites, highlighted by the observations that several compounds with a supposed specific plant defense function also act as plant growth regulators. A systematic in-depth mapping of interactions between metabolites and their target proteins would lift our understanding of cellular homeostasis and plant physiology to unprecedented levels. Comprehensive identification and characterization of the metabolite–protein interactome remains a major challenge. Only a handful of technologies are available, complementary, but each with specific shortcomings still. Further technological improvements are required to empower our analytical capacities to unravel the plant’s metabolome and its roles. Interaction between metabolites and proteins drives cellular regulatory processes within and between organisms. Recent reports highlight that numerous plant metabolites embrace multiple biological activities, beyond a sole role as substrates, products, or cofactors of enzymes, or as defense or growth-regulatory compounds. Though several technologies have been developed to identify and characterize metabolite–protein interactions, the systematic implementation of such methods in the plant field remains limited. Here, we discuss the plant metabolic space, with a specific focus on specialized metabolites and their roles, and review the technologies to study their interaction with proteins. We approach it both from a plant’s perspective, to increase our understanding of plant metabolite-dependent regulatory networks, and from a human perspective, to empower agrochemical and drug discoveries. Interaction between metabolites and proteins drives cellular regulatory processes within and between organisms. Recent reports highlight that numerous plant metabolites embrace multiple biological activities, beyond a sole role as substrates, products, or cofactors of enzymes, or as defense or growth-regulatory compounds. Though several technologies have been developed to identify and characterize metabolite–protein interactions, the systematic implementation of such methods in the plant field remains limited. Here, we discuss the plant metabolic space, with a specific focus on specialized metabolites and their roles, and review the technologies to study their interaction with proteins. We approach it both from a plant’s perspective, to increase our understanding of plant metabolite-dependent regulatory networks, and from a human perspective, to empower agrochemical and drug discoveries. metabolites that contain one or more nitrogen atoms and are principally synthesized from l-amino acids (Trp, Tyr, Phe, Lys, Arg). a class of phytohormones that are small ubiquitous molecules and provide pivotal functions within the growth and development of plants, named from the Greek auxein ‘to grow’. biological function of a small organic molecule present in a cell, tissue, or organism, which is found in its active form and is thereby able to fulfil its role within the metabolism, signaling, etc. the maintenance of an internal steady state at the level of the cell. metabolites that contain nitrogen and sulfur and are derived from glucose and an amino acid. the entire network of interactions between biomolecules in a cell, tissue, or organism. jasmonic acid derivative (3-oxo-2-2′-cis-pentenyl-cyclopentane-1-acetic acid), known as small, lipid-derived phytohormone, that is capable of eliciting the biosynthesis of bioactive metabolites in the plants. computer algorithms that build a model based on sample data, known as ‘training data’, in order to make predictions or decisions without being explicitly programmed to do so. the study of metabolomes (i.e., the entire collection of all the low-molecular weight compounds of a cell, tissue, or organism). A metabolome is specific for each cell, tissue, and organism and is influenced by the environment. aromatic metabolites that possess(ed) one or more ‘acidic’ hydroxyl groups attached to the aromatic phenyl ring. the entire collection of proteins that is, or can be, expressed in a cell, tissue, or organism. metabolites that are derived by repetitive fusion of branched five-carbon units (isopentenyl-phosphate) based on the isopentane skeleton.
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