Mapping the structural coverage of Arabidopsis thaliana plant developmental proteins: Insights from Experimental and AlphaFold Approaches

Abstract

BackgroundPlant development is a multifaceted process governed by intricate protein regulatory networks. High-throughput sequencing methods have vastly expanded plant transcriptomic and proteomic datasets, yet there is a large discrepancy between structural information for plant developmental proteins and the UniProt sequence entries. Advances in X-ray crystallography, NMR spectroscopy, and Cryo-EM have enabled the determination of protein complex structures and their dynamics. AI-driven tools like AlphaFold have revolutionized analysis of protein structural intricacies. However, available three-dimensional structural models predominantly prioritize the human proteome and other mammals over plants. Assessing structural coverage of plant developmental proteins is thus essential to identify research gaps, guide structure-function studies, and advance agriculture. ResultsHere, we focus on mapping the structural coverage of developmental proteins in Arabidopsis thaliana. We observed a substantial disparity in the Protein Data Bank (PDB) representation of Arabidopsis thaliana proteins compared to those of Homo sapiens. Our analysis identified 16,389 reviewed UniProt entries, of which only 1,038 have experimentally determined structures. Functional mapping using PlantGSEA revealed 3,485 proteins associated with plant developmental processes; of which only 337 (9.67%) have experimentally determined structures. In contrast, analysis of the AlphaFold database showed that 69.85% of the 39,278 Arabidopsis thaliana UniProt protein entries have predicted structures. Notably, all 3,485 plant developmental proteins (100%) from Arabidopsis thaliana are covered by AlphaFold models. The substantially higher structural coverage provided by AlphaFold for Arabidopsis thaliana, relative to Homo sapiens, highlights the strength of computational approaches in addressing the challenges of structural studies of difficult-to-crystallize proteins. Furthermore, 79.15% of reviewed A. thaliana protein models exhibit high confidence (pLDDT > 70), indicating reliable structural predictions. Although the experimental structural coverage of Arabidopsis thaliana developmental proteins remains limited, AlphaFold has markedly expanded the accessible structural landscape. ConclusionThis study investigated the structural coverage of Arabidopsis thaliana plant developmental proteins, underscoring the critical need for structural studies using both experimental and AlphaFold approaches. It provides research directions for bridging the knowledge gap in understanding molecular mechanisms of plant development.