LAMBADA and InflateGRO2: Efficient Membrane Alignment and Insertion of Membrane Proteins for Molecular Dynamics Simulations

Abstract

At the beginning of each molecular dynamics membrane simulation stands the generation of a suitable starting structure which includes the working steps of aligning membrane and protein and seamlessly accommodating the protein in the membrane. Here we introduce two efficient and complementary methods based on pre-equilibrated membrane patches, automating these steps. Using a voxel-based cast of the coarse-grained protein, LAMBADA computes a hydrophilicity profile-derived scoring function based on which the optimal rotation and translation operations are determined to align protein and membrane. Employing an entirely geometrical approach, LAMBADA is independent from any precalculated data and aligns even large membrane proteins within minutes on a regular workstation. LAMBADA is the first tool performing the entire alignment process automatically while providing the user with the explicit 3D coordinates of the aligned protein and membrane. The second tool is an extension of the InflateGRO method addressing the shortcomings of its predecessor in a fully automated workflow. Determining the exact number of overlapping lipids based on the area occupied by the protein and restricting expansion, compression and energy minimization steps to a subset of relevant lipids through automatically calculated and system-optimized operation parameters, InflateGRO2 yields optimal lipid packing and reduces lipid vacuum exposure to a minimum preserving as much of the equilibrated membrane structure as possible. Applicable to atomistic and coarse grain structures in MARTINI format, InflateGRO2 offers high accuracy, fast performance, and increased application flexibility permitting the easy preparation of systems exhibiting heterogeneous lipid composition as well as embedding proteins into multiple membranes. Both tools can be used separately, in combination with other methods, or in tandem permitting a fully automated workflow while retaining a maximum level of usage control and flexibility. To assess the performance of both methods, we carried out test runs using 22 membrane proteins of different size and transmembrane structure.

Modulation of Plasma Membrane Ca2+-ATPase by Neutral Phospholipids

“…Simulations were performed in GROMACS version 4.5.4 (27) using the G53a6 force field. To embed the protein, the InflateGRO2 package was used (28), and the final membranes were composed of 454 DMPC or 467 DOPC molecules. The systems were hydrated with simple point charge water molecules, and sodium and chlorine ions were added until a 0.15 M final concentration.…”

Investigating Small-Molecule Ligand Binding to G Protein-Coupled Receptors with Biased or Unbiased Molecular Dynamics Simulations

“…The CHARMM-GUI webserver (charmm-gui.org) [22] is very user friendly and can be used to build membranes of many different compositions. An alternative is to use a tool known as InflateGRO2 [23], which can automatically and efficiently embed the receptor in a pre-equilibrated membrane.In most cases, the parameters of a small-molecule ligand are not readily available in standard force fields and need to be generated by the user in a manner that is consistent with the force field used to describe the protein and lipids ( see Note 1 ). We generally use the CHARMM force field and generate initial ligand parameters using the CHARMM General Force Field (CGenFF) webserver (cgenff.paramchem.org [24, 25]).…”

Homology modeling, molecular dynamic simulation, and docking based binding site analysis of human dopamine (D4) receptor

“…Different algorithms have been presented to equilibrate a receptor inside lipid membrane. A very useful and convenient method with less consumption of time during equilibrium is called InflatGRO [43]. Therefore, to equilibrate the resulted system of lipid-protein, InflateGRO perl script was used [43].…”

“…A very useful and convenient method with less consumption of time during equilibrium is called InflatGRO [43]. Therefore, to equilibrate the resulted system of lipid-protein, InflateGRO perl script was used [43]. At first, lipids and protein were placed on an expanded grid and then shrinking process was done consecutively to reach the favorable density area per lipid for DPPC membranes (62.9-64 Å 2 ) [44].…”