Understanding the molecular mechanisms of pore formation is crucial for elucidating fundamental biological processes and developing therapeutic strategies, such as the design of drug delivery systems and antimicrobial agents. Although experimental methods can provide valuable information, they often lack the temporal and spatial resolution necessary to fully capture the dynamic stages of pore formation. In this study, we present two novel collective variables (CVs) designed to characterize membrane pore behavior, particularly its energetics, through molecular dynamics (MD) simulations. The first CV─termed Full-Path─effectively tracks both the nucleation and expansion phases of pore formation. The second CV─called Rapid─is tailored to accurately assess pore expansion in the limit of large pores, providing quick and reliable method for evaluating membrane line tension under various conditions. Our results clearly demonstrate that the line tension predictions from both our CVs are in excellent agreement. Moreover, these predictions align qualitatively with available experimental data. Specifically, they reflect higher line tension of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) membranes containing 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-l-serine (POPS) lipids compared to pure POPC, the decrease in line tension of POPC vesicles as the 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol (POPG) content increases, and higher line tension when ionic concentration is increased. Notably, these experimental trends are accurately captured only by the all-atom CHARMM36 and prosECCo75 force fields. In contrast, the all-atom Slipids force field, along with the coarse-grained Martini 2.2, Martini 2.2 polarizable, and Martini 3 models, show varying degrees of agreement with experiments. Our developed CVs can be adapted to various MD simulation engines for studying pore formation, with potential implications in membrane biophysics. They are also applicable to simulations involving external agents, offering an efficient alternative to existing methodologies.

• MeSH
• Cell Membrane * chemistry   metabolism   MeSH
• Phosphatidylcholines chemistry   MeSH
• Lipid Bilayers * chemistry   MeSH
• Porosity MeSH
• Molecular Dynamics Simulation * MeSH
• Thermodynamics * MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• 1-palmitoyl-2-oleoylphosphatidylcholine MeSH Browser
• Phosphatidylcholines MeSH
• Lipid Bilayers * MeSH

In the last quarter-century, the field of molecular dynamics (MD) has undergone a remarkable transformation, propelled by substantial enhancements in software, hardware, and underlying methodologies. In this Perspective, we contemplate the future trajectory of MD simulations and their possible look at the year 2050. We spotlight the pivotal role of artificial intelligence (AI) in shaping the future of MD and the broader field of computational physical chemistry. We outline critical strategies and initiatives that are essential for the seamless integration of such technologies. Our discussion delves into topics like multiscale modeling, adept management of ever-increasing data deluge, the establishment of centralized simulation databases, and the autonomous refinement, cross-validation, and self-expansion of these repositories. The successful implementation of these advancements requires scientific transparency, a cautiously optimistic approach to interpreting AI-driven simulations and their analysis, and a mindset that prioritizes knowledge-motivated research alongside AI-enhanced big data exploration. While history reminds us that the trajectory of technological progress can be unpredictable, this Perspective offers guidance on preparedness and proactive measures, aiming to steer future advancements in the most beneficial and successful direction.

• Publication type
• Journal Article MeSH
• Review MeSH

Cell membranes act as semi-permeable barriers, often restricting the entry of large or hydrophilic molecules. Nonetheless, certain amphiphilic molecules, such as antimicrobial and cell-penetrating peptides, can cross these barriers. In this study, we demonstrate that specific properties of transmembrane proteins/peptides can enhance membrane permeation of amphiphilic peptides. Using coarse-grained molecular dynamics with free-energy calculations, we identify key translocation-enhancing attributes of transmembrane proteins/peptides: a continuous hydrophilic patch, charged residues preferably in the membrane center, and aromatic hydrophobic residues. By employing both coarse-grained and atomistic simulations, complemented by experimental validation, we show that these properties not only enhance peptide translocation but also speed up lipid flip-flop. The enhanced flip-flop reinforces the idea that proteins such as scramblases and insertases not only share structural features but also operate through identical biophysical mechanisms enhancing the insertion and translocation of amphiphilic molecules. Our insights offer guidelines for the designing of translocation-enhancing proteins/peptides that could be used in medical and biotechnological applications.

• MeSH
• Cell Membrane metabolism   chemistry   MeSH
• Hydrophobic and Hydrophilic Interactions * MeSH
• Lipid Bilayers chemistry   metabolism   MeSH
• Membrane Proteins * chemistry   metabolism   MeSH
• Molecular Dynamics Simulation * MeSH
• Protein Transport MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Lipid Bilayers MeSH
• Membrane Proteins * MeSH

Alamethicin (ALM) is an antimicrobial peptide that is frequently employed in studies of the mechanism of action of pore-forming molecules. Advanced techniques of solid-state NMR spectroscopy (SSNMR) are important in these studies, as they are capable of describing the alignment of helical peptides, such as ALM, in lipid bilayers. Here, it is demonstrated how an analysis of the SSNMR measurements can benefit from fully periodic calculations, which employ the plane-wave density-functional theory (PW DFT) of the solid-phase geometry and related spectral parameters of ALM. The PW DFT calculations are used to obtain the structure of desolvated crystalline ALM and predict the NMR chemical shift tensors (CSTs) of its nuclei. A variation in the CSTs of the amidic nitrogens and carbonyl carbons along the ALM backbone is evaluated and included in simulations of the orientation-dependent anisotropic 15N and 13C chemical shift components. In this way, the influence of the site-specific structural effects on the experimentally determined orientation of ALM is shown in models of cell membranes.

• Keywords
• DFT, alamethicin, antimicrobial peptides, solid-state NMR,
• Publication type
• Journal Article MeSH