prosECCo75 is an optimized force field effectively incorporating electronic polarization via charge scaling. It aims to enhance the accuracy of nominally nonpolarizable molecular dynamics simulations for interactions in biologically relevant systems involving water, ions, proteins, lipids, and saccharides. Recognizing the inherent limitations of nonpolarizable force fields in precisely modeling electrostatic interactions essential for various biological processes, we mitigate these shortcomings by accounting for electronic polarizability in a physically rigorous mean-field way that does not add to computational costs. With this scaling of (both integer and partial) charges within the CHARMM36 framework, prosECCo75 addresses overbinding artifacts. This improves agreement with experimental ion binding data across a broad spectrum of systems─lipid membranes, proteins (including peptides and amino acids), and saccharides─without compromising their biomolecular structures. prosECCo75 thus emerges as a computationally efficient tool providing enhanced accuracy and broader applicability in simulating the complex interplay of interactions between ions and biomolecules, pivotal for improving our understanding of many biological processes.

• MeSH
• Peptides chemistry   MeSH
• Proteins chemistry   MeSH
• Molecular Dynamics Simulation * MeSH
• Static Electricity * MeSH
• Water chemistry   MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Peptides MeSH
• Proteins MeSH
• Water MeSH

Tools based on artificial intelligence (AI) are currently revolutionising many fields, yet their applications are often limited by the lack of suitable training data in programmatically accessible format. Here we propose an effective solution to make data scattered in various locations and formats accessible for data-driven and machine learning applications using the overlay databank format. To demonstrate the practical relevance of such approach, we present the NMRlipids Databank-a community-driven, open-for-all database featuring programmatic access to quality-evaluated atom-resolution molecular dynamics simulations of cellular membranes. Cellular membrane lipid composition is implicated in diseases and controls major biological functions, but membranes are difficult to study experimentally due to their intrinsic disorder and complex phase behaviour. While MD simulations have been useful in understanding membrane systems, they require significant computational resources and often suffer from inaccuracies in model parameters. Here, we demonstrate how programmable interface for flexible implementation of data-driven and machine learning applications, and rapid access to simulation data through a graphical user interface, unlock possibilities beyond current MD simulation and experimental studies to understand cellular membranes. The proposed overlay databank concept can be further applied to other biomolecules, as well as in other fields where similar barriers hinder the AI revolution.

• MeSH
• Cell Membrane MeSH
• Membrane Lipids * MeSH
• Molecular Dynamics Simulation MeSH
• Machine Learning MeSH
• Artificial Intelligence * MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Membrane Lipids * MeSH

The routinely employed periodic boundary conditions complicate molecular simulations of physiologically relevant asymmetric lipid membranes together with their distinct solvent environments. Therefore, separating the extracellular fluid from its cytosolic counterpart has often been performed using a costly double-bilayer setup. Here, we demonstrate that the lipid membrane and solvent asymmetry can be efficiently modeled with a single lipid bilayer by applying an inverted flat-bottom potential to ions and other solute molecules, thereby restraining them to only interact with the relevant leaflet. We carefully optimized the parameters of the suggested method so that the results obtained using the flat-bottom and double-bilayer approaches become mutually indistinguishable. Then, we apply the flat-bottom approach to lipid bilayers with various compositions and solvent environments, covering ions and cationic peptides to validate the approach in a realistic use case. We also discuss the possible limitations of the method as well as its computational efficiency and provide a step-by-step guide on how to set up such simulations in a straightforward manner.

• MeSH
• Lipid Bilayers * chemistry   MeSH
• Solvents MeSH
• Molecular Dynamics Simulation * MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Lipid Bilayers * MeSH
• Solvents MeSH

Cholesterol is a central building block in biomembranes, where it induces orientational order, slows diffusion, renders the membrane stiffer, and drives domain formation. Molecular dynamics (MD) simulations have played a crucial role in resolving these effects at the molecular level; yet, it has recently become evident that different MD force fields predict quantitatively different behavior. Although easily neglected, identifying such limitations is increasingly important as the field rapidly progresses toward simulations of complex membranes mimicking the in vivo conditions: pertinent multicomponent simulations must capture accurately the interactions between their fundamental building blocks, such as phospholipids and cholesterol. Here, we define quantitative quality measures for simulations of binary lipid mixtures in membranes against the C-H bond order parameters and lateral diffusion coefficients from NMR spectroscopy as well as the form factors from X-ray scattering. Based on these measures, we perform a systematic evaluation of the ability of commonly used force fields to describe the structure and dynamics of binary mixtures of palmitoyloleoylphosphatidylcholine (POPC) and cholesterol. None of the tested force fields clearly outperforms the others across the tested properties and conditions. Still, the Slipids parameters provide the best overall performance in our tests, especially when dynamic properties are included in the evaluation. The quality evaluation metrics introduced in this work will, particularly, foster future force field development and refinement for multicomponent membranes using automated approaches.

• MeSH
• Cholesterol chemistry   MeSH
• Phosphatidylcholines * chemistry   MeSH
• Lipid Bilayers * chemistry   MeSH
• Molecular Dynamics Simulation MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• 1-palmitoyl-2-oleoylphosphatidylcholine MeSH Browser
• Cholesterol MeSH
• Phosphatidylcholines * MeSH
• Lipid Bilayers * MeSH

Mounting evidence suggests that the neuronal cell membrane is the main site of oligomer-mediated neuronal toxicity of amyloid-β peptides in Alzheimer's disease. To gain a detailed understanding of the mutual interference of amyloid-β oligomers and the neuronal membrane, we carried out microseconds of all-atom molecular dynamics (MD) simulations on the dimerization of amyloid-β (Aβ)42 in the aqueous phase and in the presence of a lipid bilayer mimicking the in vivo composition of neuronal membranes. The dimerization in solution is characterized by a random coil to β-sheet transition that seems on pathway to amyloid aggregation, while the interactions with the neuronal membrane decrease the order of the Aβ42 dimer by attenuating its propensity to form a β-sheet structure. The main lipid interaction partners of Aβ42 are the surface-exposed sugar groups of the gangliosides GM1. As the neurotoxic activity of amyloid oligomers increases with oligomer order, these results suggest that GM1 is neuroprotective against Aβ-mediated toxicity.

• Keywords
• Alzheimer’s disease, amyloid-β, molecular dynamics, neuronal membrane, transition network,
• MeSH
• Amyloid chemistry   MeSH
• Amyloid beta-Peptides chemistry   metabolism   MeSH
• Cell Membrane metabolism   MeSH
• G(M1) Ganglioside metabolism   MeSH
• Protein Conformation MeSH
• Humans MeSH
• Lipid Bilayers metabolism   MeSH
• Protein Multimerization * MeSH
• Neurons metabolism   MeSH
• Molecular Dynamics Simulation MeSH
• Protein Binding MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Amyloid MeSH
• Amyloid beta-Peptides MeSH
• G(M1) Ganglioside MeSH
• Lipid Bilayers MeSH

Interactions at the solid-body fluid interfaces play a vital role in bone tissue formation at the implant surface. In this study, fully atomistic molecular dynamics (MD) simulations were performed to investigate interactions between the physiological components of body fluids (Ca2+, HPO42-, H2PO4-, Na+, Cl-, and H2O) and functionalized parylene C surface. In comparison to the native parylene C (-Cl surface groups), the introduction of -OH, -CHO, and -COOH surface groups significantly enhances the interactions between body fluid ions and the polymeric surface. The experimentally observed formation of calcium phosphate nanocrystals is discussed in terms of MD simulations of the calcium phosphate clustering. Surface functional groups promote the clustering of calcium and phosphate ions in the following order: -OH > -CHO > -Cl (parent parylene C) ≈ -COO-. This promoting role of surface functional groups is explained as stimulating the number of Ca2+ and HPO42- surface contacts as well as ion chemisorption. The molecular mechanism of calcium phosphate cluster formation at the functionalized parylene C surface is proposed.

• Keywords
• calcium phosphate, functional groups, molecular dynamics, nucleation mechanism, parylene C, polymer surface,
• Publication type
• Journal Article MeSH