Implicit solvent systematic coarse-graining of dioleoylphosphatidylethanolamine lipids: From the inverted hexagonal to the bilayer structure

Abstract

Lamellar and hexagonal lipid structures are of particular importance in the biological processes such as membrane fusion and budding. Atomistic simulations of formation of these phases and transitions between them are computationally prohibitive, hence development of coarse-grained models is an important part of the methodological development in this area. Here we apply systematic bottom-up coarse-graining to model different phase structures formed by 1,2-dioleoylphosphatidylethanolamine (DOPE) lipid molecules. We started from atomistic simulations of DOPE lipids in water carried out at two different water/lipid molar ratio corresponding to the lamellar L α and inverted hexagonal H II structures at low and high lipid concentrations respectively. The atomistic trajectories were mapped to coarse-grained trajectories, in which each lipid was represented by 14 coarse-grained sites. Then the inverse Monte Carlo method was used to compute the effective coarse-grained potentials which for the coarse-grain model reproduce the same structural properties as the atomistic simulations. The potentials derived from the low concentration atomistic simulation were only able to form a bilayer structure, while both L α and H II lipid phases were formed in simulations with potentials obtained at high concentration. The typical atomistic configurations of lipids at high concentration combine fragments of both lamellar and non-lamellar structures, that is reflected in the extracted coarse-grained potentials which become transferable and can form a wide range of structures including the inverted hexagonal, bilayer, tubule, vesicle and micellar structures.

Microfluidic investigation of the effect of graphene oxide on mechanical properties of cell and actin cytoskeleton networks: experimental and theoretical approaches

“…The CG models of GO involved 48% oxygen bead (SP1) and 52% CG bead of graphene (SG4). For building CG models, we used a home code written in Python, which was tested in our previous work to lipid modeling and is available from this link: https://github.com/saeedMRT/scg4py 31 .…”

Coarse-Grained Model Incorporating Short- and Long-Range Effective Potentials for the Fast Simulation of Micelle Formation in Solutions of Ionic Surfactants

“…The method proposes a numerical scheme for computing effective interactions in an iterative fashion by refining the CG potential at iteration (i + 1) by examining whether or not the corresponding probability distribution or pair distribution function obtained from the CG simulation at iteration (i) matches the target one derived from the all-atom system (the reference system). 32,56,57 Over the years, the IBI method has been used to derive effective potentials for (1) simple liquids, 58−61 (2) systems exhibiting liquid crystalline behavior, 62−65 (3) bulk polymer melts 66−74 and copolymers, 75 (4) polymer solutions, 76−78 (5) lipids, 79,80 and (6) small peptides. 81,82 In the present work, we extend the above studies to micellar solutions of surfactant molecules.…”

“…This happens because the new effective potentials are derived with the help of iterative Boltzmann inversion (IBI), a rather general method that in principle can be applied to any class of systems in soft matter. The method proposes a numerical scheme for computing effective interactions in an iterative fashion by refining the CG potential at iteration ( i + 1) by examining whether or not the corresponding probability distribution or pair distribution function obtained from the CG simulation at iteration ( i ) matches the target one derived from the all-atom system (the reference system). ,, Over the years, the IBI method has been used to derive effective potentials for (1) simple liquids, − (2) systems exhibiting liquid crystalline behavior, − (3) bulk polymer melts − and copolymers, (4) polymer solutions, − (5) lipids, , and (6) small peptides. , …”