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. 2023 Aug 3;18(8):e0288264.
doi: 10.1371/journal.pone.0288264. eCollection 2023.

Protocol for the development of coarse-grained structures for macromolecular simulation using GROMACS

Vidya Niranjan  1 , Purushotham Rao  1 , Akshay Uttarkar  1 , Jitendra Kumar  2
Affiliations

Protocol for the development of coarse-grained structures for macromolecular simulation using GROMACS

Vidya Niranjan et al. PLoS One. .

Abstract

Coarse-grained simulations have emerged as a valuable tool in the study of large and complex biomolecular systems. These simulations, which use simplified models to represent complex biomolecules, reduce the computational cost of simulations and enable the study of larger systems for longer periods of time than traditional atomistic simulations. GROMACS is a widely used software package for performing coarse-grained simulations of biomolecules, and several force fields have been developed specifically for this purpose. In this protocol paper, we explore the advantages of using coarse-grained simulations in the study of biomolecular systems, focusing specifically on simulations performed using GROMACS. We discuss the force fields required for these simulations and the types of research questions that can be addressed using coarse-grained simulations. We also highlight the potential benefits of coarse-grained simulations for the development of new force fields and simulation methodologies. We then discuss the expected results from coarse-grained simulations using GROMACS and the various techniques that can be used to analyze these results. We explore the use of trajectory analysis tools, as well as thermodynamic and structural analysis techniques, to gain insight into the behavior of biomolecular systems.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Conversion of AA model and expected results from CG simulation and analysis.
A) A protein all atom model 3D structure in wireframe representation colored in blue. B) The protein all atom model converted to CG model with bead representation. C) The RMSD plot after 200ns CG simulation. D) The plot of radius of gyration versus time during protein ligand CG simulation. E) The scree plot with eigenvalues vs component number. The green section highlighted in the main plot is enhanced in the secondary in-plot to show the elbow region of the plot. F) PCA plot of projection of eigenvectors 1 versus eigenvectors 2 in nm.
Fig 2
Fig 2. Occupancy map of compounds in protein compound system.
A) The occupancy map of kanamycin on the surface of protein (green) in shown in blue. B) The occupancy map of kanamycin on the surface of protein (green) in shown in blue and streptomycin in red.
See this image and copyright information in PMC

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