Abstract
Recent advances in protein structure prediction have opened new avenues for understanding the potential impact of genetic mutations and how they might affect protein structure. In this study, we analyzed the distribution and structural characteristics of mutations in four plant species: Arabidopsis, rice, sugar beet, and cassava. We integrated population genotype datasets with protein structure predictions to map mutation positions to their corresponding gene protein products and structural features. Our analysis reveals that high-effect mutations are more likely to occur in unstructured, disordered regions of proteins rather than in well-folded, conserved regions. This finding suggests that natural selection exerts greater pressure to conserve sequence integrity in folded regions, which are crucial for protein function. Conversely, disordered regions may tolerate higher variability exhibiting a higher frequency of impactful mutations. By providing a comprehensive overview of mutation distribution in relation to protein structure, this study enhances our understanding of the evolutionary pressures shaping plant proteomes. The insights gained from this research could inform future studies on protein function, evolutionary biology, and plant improvement strategies.