AIMC Topic: Lipid Bilayers
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The EMC acts as a chaperone for membrane proteins.
Nature communications
Aug 2, 2025
Structure formation of membrane proteins is error-prone and thus requires chaperones that oversee this essential process in cell biology. The ER membrane protein complex (EMC) is well-defined as a transmembrane domain (TMD) insertase. In this study, ...
ABEEM Polarizable Force Field for PC Lipids: Parameterization and Molecular Dynamics Simulations.
Journal of chemical theory and computation
Jul 3, 2025
In additive force fields, the charge is a tunable parameter designed to represent average polarization effects through a mean-field average, which could not accurately respond to different environments. The polarizable force field (PFF) offers enhanc...
Investigating the Bromoform Membrane Interactions Using Atomistic Simulations and Machine Learning: Implications for Climate Change Mitigation.
The journal of physical chemistry. B
Dec 6, 2024
Methane emissions from livestock contribute to global warming. Seaweeds used as food additive offer a promising emission mitigation strategy because seaweeds are enriched in bromoform─a methanogenesis inhibitor. Therefore, understanding bromoform sto...
Application of Generative Artificial Intelligence in Predicting Membrane Partitioning of Drugs: Combining Denoising Diffusion Probabilistic Models and MD Simulations Reduces the Computational Cost to One-Third.
Journal of chemical theory and computation
Jun 28, 2024
The optimal interaction of drugs with plasma membranes and membranes of subcellular organelles is a prerequisite for desirable pharmacology. Importantly, for drugs targeting the transmembrane lipid-facing sites of integral membrane proteins, the rela...
An active machine learning discovery platform for membrane-disrupting and pore-forming peptides.
Physical chemistry chemical physics : PCCP
Jun 26, 2024
Membrane-disrupting and pore-forming peptides (PFPs) play a substantial role in bionanotechnology and can determine the life and death of cells. The control of chemical and ion transport through cell membranes is essential to maintaining concentratio...
Topological Learning Approach to Characterizing Biological Membranes.
Journal of chemical information and modeling
Jun 24, 2024
Biological membranes play key roles in cellular compartmentalization, structure, and its signaling pathways. At varying temperatures, individual membrane lipids sample from different configurations, a process that frequently leads to higher-order pha...
Cryo-EM images of phase-separated lipid bilayer vesicles analyzed with a machine-learning approach.
Biophysical journal
Apr 30, 2024
Lateral lipid heterogeneity (i.e., raft formation) in biomembranes plays a functional role in living cells. Three-component mixtures of low- and high-melting lipids plus cholesterol offer a simplified experimental model for raft domains in which a li...
Parallel transmission in a synthetic nerve.
Nature chemistry
Apr 21, 2022
Bioelectronic devices that are tetherless and soft are promising developments in medicine, robotics and chemical computing. Here, we describe bioinspired synthetic neurons, composed entirely of soft, flexible biomaterials, capable of rapid electroche...
A machine learning approach to estimation of phase diagrams for three-component lipid mixtures.
Biochimica et biophysica acta. Biomembranes
May 11, 2020
The plasma membrane of eukaryotic cells is commonly believed to contain ordered lipid domains. The interest in understanding the origin of such domains has led to extensive studies on the phase behavior of mixed lipid systems. Three-component phase d...
Unsupervised Machine Learning for Analysis of Phase Separation in Ternary Lipid Mixture.
Journal of chemical theory and computation
Oct 7, 2019
Phase separation in mixed lipid systems has been extensively studied both experimentally and theoretically because of its biological importance. A detailed description of such complex systems undoubtedly requires novel mathematical frameworks that ar...
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