scholarly journals Conformational Ensembles of Noncoding Elements in the SARS-CoV-2 Genome from Molecular Dynamics Simulations

Author(s):  
Sandro Bottaro ◽  
Giovanni Bussi ◽  
Kresten Lindorff-Larsen
2020 ◽  
Author(s):  
Sandro Bottaro ◽  
Giovanni Bussi ◽  
Kresten Lindorff-Larsen

The 5' untranslated region (UTR) of SARS-CoV-2 genome is a conserved, functional and structured genomic region consisting of several RNA stem-loop elements. While the secondary structure of such elements has been determined experimentally, their three-dimensional structure is not known yet. Here, we predict structure and dynamics of five RNA stem-loops in the 5'-UTR of SARS-CoV-2 by extensive atomistic molecular dynamics simulations, more than 0.5ms of aggregate simulation time, in combination with enhanced sampling techniques. We compare simulations with available experimental data, describe the resulting conformational ensembles, and identify the presence of specific structural rearrengements in apical and internal loops that may be functionally relevant. Our atomic-detailed structural predictions reveal a rich dynamics in these RNA molecules, could help the experimental characterisation of these systems, and provide putative three-dimensional models for structure-based drug design studies.


2018 ◽  
Author(s):  
M. Eric Irrgang ◽  
Jennifer M. Hays ◽  
Peter M. Kasson

AbstractSummaryMolecular dynamics simulations have found use in a wide variety of biomolecular applications, from protein folding kinetics to computational drug design to refinement of molecular structures. Two areas where users and developers frequently need to extend the built-in capabilities of most software packages are implementing custom interactions, for instance biases derived from experimental data, and running ensembles of simulations. We present a Python high-level interface for the popular simulation package GROMACS that 1) allows custom potential functions without modifying the simulation package code, 2) maintains the optimized performance of GROMACS, and 3) presents an abstract interface to building and executing computational graphs that allows transparent low-level optimization of data flow and task placement. Minimal dependencies make this integrated API for the GROMACS simulation engine simple, portable, and maintainable. We demonstrate this API for experimentally-driven refinement of protein conformational ensembles.AvailabilitySource and installation instructions are available at https://github.com/kassonlab/gmxapi.


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