Investigating the Bromoform Membrane Interactions Using Atomistic Simulations and Machine Learning: Implications for Climate Change Mitigation.

Autor: Cheng KJ; Center for Biophysics and Quantitative Biology, University of Illinois Urbana-Champaign, Urbana, Illinois 61801 United States.; IBM Accelerated Discovery and Cellular Engineering, IBM Almaden Research Center, San Jose, California 95120 United States.; NSF Center for Cellular Construction, University of California in San Francisco, San Francisco, California 94158 United States., Shi J; IBM Accelerated Discovery and Cellular Engineering, IBM Almaden Research Center, San Jose, California 95120 United States.; NSF Center for Cellular Construction, University of California in San Francisco, San Francisco, California 94158 United States., Pogorelov TV; Center for Biophysics and Quantitative Biology, University of Illinois Urbana-Champaign, Urbana, Illinois 61801 United States.; Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States.; School of Chemical Sciences, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States.; Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States.; National Center for Supercomputing Applications, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States., Capponi S; IBM Accelerated Discovery and Cellular Engineering, IBM Almaden Research Center, San Jose, California 95120 United States.; NSF Center for Cellular Construction, University of California in San Francisco, San Francisco, California 94158 United States.
Jazyk: angličtina
Zdroj: The journal of physical chemistry. B [J Phys Chem B] 2024 Dec 19; Vol. 128 (50), pp. 12493-12506. Date of Electronic Publication: 2024 Dec 06.
DOI: 10.1021/acs.jpcb.4c04930
Abstrakt: 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 storage and production in seaweeds and particularly in a cell-like environment is crucial. As a first step toward this aim, we present an atomistic description of bromoform dynamics, diffusion, and aggregation in the presence of lipid membranes. Using all-atom molecular dynamics simulations with customized CHARMM-formatted bromoform force field files, we investigate the interactions of bromoform and lipid bilayer across various concentrations. Bromoform penetrates membranes and at high concentrations forms aggregates outside the membrane without affecting membrane thickness or lipid tail order. Aggregates outside the membrane influence the membrane curvature. Within the membrane, bromoform preferentially localizes in the membrane hydrophobic core and diffuses the slowest along the membrane normal. Employing general local-atomic descriptors and unsupervised machine learning, we demonstrate the similarity of bromoform local structures between the liquid and aggregated forms.
Databáze: MEDLINE