Developing a Coarse-Grained Model for Bacterial Cell Walls and Evaluating Mechanical Properties and Free Energy Barriers

Abstract

The bacterial cell envelope of Gram-negative bacteria is a complex biological barrier with multiple layers consisting of the inner membrane, periplasm of peptidoglycan and the outer membrane with lipopolysaccharides (LPS). With rising antimicrobial resistance there is increasing interest in understanding interactions of small molecules with the cell membrane to aid in the development of novel drug molecules. Hence suitable representations of the bacterial membrane are required to carry out meaningful molecular dynamics simulations. Given the complexity of the cell envelope, fully atomistic descriptions of the cell membrane with explicit solvent are computationally prohibitive, allowing limited sampling with small system sizes. However coarse-grained (CG) models such as MARTINI allow one to study phenomena at physiologically relevant length and time scales. Although MARTINI models for lipids and the LPS are available in literature, a suitable CG model of peptidoglycan is lacking. In this manuscript we develop a CG model of the peptidoglycan network within the MARTINI framework using an all-atom model developed by Gumbart et al. 1. The model is parametrized to reproduce the structural properties of the glycan strands, such as the end-to-end distance, equilibrium angle between adjacent peptides along the strands and area per disaccharide. Mechanical properties such as the area compressibility and the bending modulus are accurately reproduced. While developing novel antibiotics it is important to assess barrier properties of the peptidogylcan network. We evaluate and compare the free energy of insertion for a thymol molecule using umbrella sampling on both the MARTINI and all-atom peptidoglycan models. The insertion free energy was found to be less than kBT for both the MARTINI and all-atom models. Additional restraint free simulations reveal rapid translocation of thymol across peptidogylcan. We expect that the proposed MARTINI model for peptidoglycan will be useful in understanding phenomena associated with bacterial cell walls at larger length and time scales, thereby overcoming the current limitations of all-atom models.