Abstract Molecular Dynamics (MD) simulation of biomolecules provides important insights into conformational changes and dynamic behavior, revealing critical information about folding and interactions with other molecules. The collection of simulations stored in computers across the world holds immense potential to serve as training data for future Machine Learning models that will transform the prediction of structure, dynamics, drug interactions, and more. Ideally, there should exist an open access repository that enables scientists to submit and store their MD simulations of proteins and protein-drug interactions, and to find, retrieve, analyze, and visualize simulations produced by others. However, despite the ubiquity of MD simulation in structural biology, no such repository exists; as a result, simulations are instead stored in scattered locations without uniform metadata or access protocols. Here, we introduce MDRepo, a robust infrastructure that provides a relatively simple process for standardized community contribution of simulations, activates common downstream analyses on stored data, and enables search, retrieval, and visualization of contributed data. MDRepo is built on top of the open-source CyVerse research cyber-infrastructure, and is capable of storing petabytes of simulations, while providing high bandwidth upload and download capabilities and laying a foundation for cloud-based access to its stored data.
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Computational microscopy: Revealing molecular mechanisms in plants using molecular dynamics simulations
Structural biology has provided valuable insights and high-resolution views of the biophysical processes in plants, such as photosynthesis, hormone signaling, nutrient transport, and toxin efflux. However, structural biology only provides a few “snapshots” of protein structure, whereas in vivo, protein function involves complex dynamical processes such as ligand binding and conformational changes that structures alone are unable to capture in full detail. Here, we present all-atom molecular dynamics (MD) simulations as a “computational microscope” that can be used to capture detailed structural and dynamical information about the molecular machinery in plants and gain high-resolution insights into plant growth and function. In addition to the background information provided here, we have prepared a set of tutorials that allow students to run and explore MD simulations of plant proteins.
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- Award ID(s):
- 1845606
- PAR ID:
- 10132021
- Date Published:
- Journal Name:
- The Plant Cell
- Volume:
- 31
- Issue:
- 12
- ISSN:
- 1040-4651
- Page Range / eLocation ID:
- tpc.119.tt1219
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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