(597a) Computational Approaches for Understanding Nitrogen Use Efficiency in Plants

More than half the global population is nourished by crops grown with nitrogen (N) fertilizers. However, only 30-50% of the N fertilizer applied is captured by the roots of crops and the excess applied nitrogen leads to biodiversity loss, environmental pollution, and climate change. Improving nitrogen use efficiency (NUE) - that is, increasing crop production per unit of added nitrogen - is the key for meeting growing food demand while mitigating environmental pollution. 1% increase in NUE could save $1.1 billion annually. Therefore, there is need to understand the mechanisms of nitrogen uptake in plants to enable engineering of crops with high N-uptake efficiency. In this study, we have developed and employed efficient computational tools to uncover N uptake mechanism for multiple N transporters. We have developed a machine learning based algorithm (called FingerprintContacts) for quickly predicting multiple protein structures through combination of agglomerative clustering and bioinformatics. This approach allows us to initiate molecular dynamics simulations from multiple starting coordinates even for proteins without structural information available. To accelerate the analysis of transporter dynamics, we have developed a genetic algorithm based technique to optimize feature selection for interpreting high-dimensional simulation data. We then integrated the developed algorithms with all-atom molecular dynamics simulations to characterize the conformational transitions and the complete substrate translocation cycle of two different types of nitrate transporters: plant nitrate transporter NRT1.1 (~150 µs) and bacterial nitrate transporter NarK (~300 µs). NRT1.1 is a proton-coupled symporter, whereas NarK is a nitrate/nitrite antiporter. To the best of authors’ knowledge, this study reports the first large-scale unbiased simulations of these key nitrate transporters. These simulations have not only revealed the key conformations of transporters along the transport cycle, but also explained the post-translational regulation of transporter affinity. In particular, this study (1) captures nitrate recognition, binding, and translocation in NRT1.1, (2) shows that phosphorylation switches the affinity of NRT1.1 by enhancing structural flexibility of each monomer and decoupling the dimer, and (3) explores the complete nitrate/nitrite exchange cycle in NarK.