TS2CG as a Membrane Builder

Abstract

Molecular dynamics (MD) simulations excel at capturing biological processes at the molecular scale but rely on a well-defined initial structure. As MD simulations now extend to whole-cell-level modeling, new tools are needed to efficiently build initial structures. Here, we introduce TS2CG version 2, designed to construct coarse-grained membrane structures with any desired shape and lateral organization. This version enables precise placement of lipids and proteins based on curvature preference, facilitating the creation of large, near-equilibrium membranes. Additional features include controlled pore generation and the placement of specific lipids at membrane edges for stabilization. Moreover, a Python interface allows users to extend functionality while maintaining the high performance of the C++ core. To demonstrate its capabilities, we showcase challenging simulations, including a Möbius strip membrane, a vesicle with lipid domains as continental plates (Martini globe), and entire mitochondrial membranes exhibiting lipid heterogeneity due to curvature, along with a comprehensive set of tutorials.

1

The TS2CG 2.0 membrane creation workflow. A workflow diagram explaining the overall steps of TS2CG 2.0 to generate complex membranes. The process can be started via an analytical shape or an arbitrary triangulated surface. Here, we consider a sin shape. Through PLM or PCG, a point directory can be created which is then manipulated using the Point class to place proteins, exclusions or introduce a different domain (inclusions (proteins) as black dots, domains in dark orange, and the center of an exclusion is marked in red). A second execution of PCG turns the point folder including the changes into a membrane structure ready for subsequent simulation. PLM and PCG are names for TS2CG 2.0 subroutines, which are explained in the step-by-step guide.

2

A flat membrane. A membrane with a single protein is shown after initialization through TS2CG (A) followed by a subsequent energy minimization (B). The image has been centered around the protein.

3

Generating membranes by sorted lipids according to their curvature preference. A) Presents the community scores of the 90 membranes generated with DOP and visualizes the impact of varying C ₀ and k values for CDL while C ₀ and k remain constant for POPC (C ₀ = 0, k = 1). B) Density distribution comparison for different k-values, 20 systems generated with C ₀ = −0.3 and different k-values are evaluated against the reference. The blue box highlights the k-values used for the community score. C) The reference system, with natural sorting of the lipids through simulations. D) Resulting system for C ₀ of −0.3 and k of 1. E) Resulting system for C ₀ of −0.3 and k of 10. The differences between Panels D and E become best visible in the right valley. The high k placement of Panel E places a collection of CDL precisely, while the low k placement does not. The blue lines in Panels C to E resemble the periodic boundary condition.

4

Mitochondrial membrane with real shape from Cryo-ET. A) Inner mitochondrial membrane colored by mean curvature: positive mean curvature (H > 0) in blue, negative mean curvature (H < 0) in green. B) Martini 3 model of the inner mitochondrial membrane with lipids distributed by curvature preference (PAPI/SAPE pink, CDL blue, POPC/POPS green). C) Curvature-dependent distribution of mitochondrial lipids plotted as the relative distribution in function of membrane curvature. A large k was chosen to strongly bias the lipids for a clearer visualization of the tool. Therefore, the curves appear skewed as it is highly unlikely for a lipid to be placed in the region opposite its own preference.

5

Model of a mitochondrial cristae. The model shows lipids and membrane proteins arranged by curvature preference. MIC60/TIM complexes (top), ANT1/ANT2 transporters and respiratory complex (sides), and ATPase dimers (bottom) are shown. Zoom panels highlight the lipid sorting patterns: PAPI/SAPE (pink), CDL (purple), POPC/POPS (green).

6

The Martini Möbius strip. Representative snapshots of lipid Möbius strips transforming into vesicles. A) 70%POPC/30%CHOL composition transitioning to an oblate vesicle with complete bilayer formation within 300 ns. B) 68%POPC/29% CHOL/3% DLPC composition, where DLPC was placed in the open edges resulting in a delayed bilayer formation occurring at 400 ns. Cutouts reveal the topological transition from a single continuous monolayer to two separate lipid bilayer leaflets in each oblate vesicle.

7

Monoolein diamonds. Snapshots of a monoolein diamond cubic phase at two different lattice sizes (1 × 1 × 1 and 2 × 2 × 2). The left panels show the molecular representation with lipid tails in green, headgroups in purple, and the water channels displayed in hues of blue. The right panels display the fitted surface of the cubic phase lipids colored according to their Gaussian curvature.

8

The Martini globe. The lipids of the globe colored by their continent based on the tectonic plates. The Kingdom of Denmark is colored dark red. Panel A shows the whole surface. Panel B shows a cutout of the globe visualizing the inner and outer monolayer and the lipid tails in between.