Advances and opportunities for computational interrogation of plant proteins

Plants exhibit remarkable biochemical and physiological diversity, and are capable of adapting to a wide range of environmental conditions and stresses. This complexity makes them essential systems for understanding how life responds to a changing climate. Plant proteins are the molecular engines that carry out the reactions, signalling and regulation underlying these adaptive processes. However, studying plant proteins remains constrained by limited experimental throughput and the challenges of genetic manipulation, which vary widely across species. While synthetic biology and heterologous expression systems have expanded opportunities to investigate plant proteins, in planta studies are still limited by the availability and efficiency of genetic transformation methods. Computational approaches offer a powerful complement to experimental research by generating high-throughput, testable hypotheses that can accelerate discovery of plant protein function. In recent years, the power, versatility and ease of use of computational tools for protein research have expanded dramatically. These methods now enable detailed predictions of protein structure, dynamics and interactions, as well as insights into their evolutionary history and mechanistic function. In this review, we highlight the expanding computational toolkit for plant protein analysis, emphasising both established and emerging approaches. We summarise recent successes where computational methods have provided key biological insights into plant protein function and highlight the potential of such methods for scientific discovery in plant research. By integrating computation with experimentation, plant biology can overcome current limitations to studying plant proteins and move more rapidly toward a mechanistic understanding of plant processes, enabling advances in agriculture, ecology and climate resilience.