Towards Sustainable Agriculture: Elucidating Ammonium Transporter Mep2
Summary
We are seeking a passionate apprentice about computational biology. You can employ molecular dynamics simulations, machine learning, and data science approaches to understand the underlying working mechanism of an ammonium transporter, Mep2.
Mep2 proteins transport ammonium from external environment, a crucial determining factor for plant growth. Understanding how Mep2 absorbs ammonium will help us understand how plants take up nutrient. This will potentially provide new insights about engineering plant proteins to achieve better crop yield.
Job Description
1. Employ molecular dynamics simulations to simulate the dynamics of proteins 2. Analyze high dimensional simulation data using Markov State Models and advanced machine learning techniques 3. Organize research findings into a scientific manuscript
Computational Resources
This project will require lots of computational resources from XSEDE-allocated supercomputers to conduct molecular dynamics simulations for the ammonium transporter, Mep2. In order to observe the dynamically relevant motions of Mep2, we will need to perform large-scale simulations to capture the dynamics and understand the working mechanism of this protein.
Contribution to Community
Position Type
Apprentice
Training Plan
Stage 1: Learn the basics of molecular dynamics simulations, markov state models, and biology proteins Stage 2: Set up system and conduct simulations Stage 3: Extract insights from simulation data by conducting detailed analysis Stage 4: Organize results into a scientific manuscript