The future of plant lectinology: Advanced technologies and computational tools

Lectins play crucial roles in many biological processes and serve as tools in fields ranging from agriculture to biomedicine. While classical methods for lectin discovery and characterization were foundational for the field, they often lack sensitivity and throughput, limiting the detection of less abundant or weakly binding lectins, such as the stress-inducible or monovalent lectins. This review focuses on recent advancements in plant lectin research, particularly novel technologies that complement traditional approaches. Techniques such as glycan microarrays allow rapid assessment of lectin specificity across a diverse range of glycans by evaluating interactions with immobilized glycans on solid surfaces. Phage display libraries enable the identification of carbohydrate-mimetic peptides and the development of ligands for lectins by presenting diverse peptide libraries on bacteriophages. Genomic and transcriptomic analyses facilitate the exploration of the lectome in various plant species by scanning entire datasets to identify genes that contain lectin motifs-specific conserved amino acid sequences involved in carbohydrate recognition-and lectin domains, the larger structural regions that facilitate and stabilize these interactions. Additionally, computational methods-including molecular docking, molecular dynamics simulations, and machine learning pipelines-support predictions of lectin structures and binding properties, underpinning experimental efforts. These advanced techniques bring increased efficiency, accuracy, and a broader scope to lectin studies, with potential impacts across multiple fields. However, challenges such as data complexity and the need for experimental validation for computational methods remain. The future of lectin research will depend on the integration of these methods and the strengthening of interdisciplinarity to unlock the full potential of lectins.