Change search
Link to record
Permanent link

Direct link
Alternative names
Publications (4 of 4) Show all publications
Elias-Wolff, F., Lindén, M., Lyubartsev, A. P. & Brandt, E. G. (2019). Curvature sensing by cardiolipin in simulated buckled membranes. Soft Matter, 15(4), 792-802
Open this publication in new window or tab >>Curvature sensing by cardiolipin in simulated buckled membranes
2019 (English)In: Soft Matter, ISSN 1744-683X, E-ISSN 1744-6848, Vol. 15, no 4, p. 792-802Article in journal (Refereed) Published
Abstract [en]

Cardiolipin is a non-bilayer phospholipid with a unique dimeric structure. It localizes to negative curvature regions in bacteria and is believed to stabilize respiratory chain complexes in the highly curved mitochondrial membrane. Cardiolipin's localization mechanism remains unresolved, because important aspects such as the structural basis and strength for lipid curvature preferences are difficult to determine, partly due to the lack of efficient simulation methods. Here, we report a computational approach to study curvature preferences of cardiolipin by simulated membrane buckling and quantitative modeling. We combine coarse-grained molecular dynamics with simulated buckling to determine the curvature preferences in three-component bilayer membranes with varying concentrations of cardiolipin, and extract curvature-dependent concentrations and lipid acyl chain order parameter profiles. Cardiolipin shows a strong preference for negative curvatures, with a highly asymmetric chain order parameter profile. The concentration profiles are consistent with an elastic model for lipid curvature sensing that relates lipid segregation to local curvature via the material constants of the bilayers. These computations constitute new steps to unravel the molecular mechanism by which cardiolipin senses curvature in lipid membranes, and the method can be generalized to other lipids and membrane components as well.

National Category
Chemical Sciences Materials Engineering Physical Sciences
Identifiers
urn:nbn:se:su:diva-166789 (URN)10.1039/c8sm02133c (DOI)000457329700020 ()30644502 (PubMedID)
Available from: 2019-03-12 Created: 2019-03-12 Last updated: 2022-03-23Bibliographically approved
Elías-Wolff, F., Lindén, M., Lyubartsev, A. P. & Brandt, E. G. (2018). Computing Curvature Sensitivity of Biomolecules in Membranes by Simulated Buckling. Journal of Chemical Theory and Computation, 14(3), 1643-1655
Open this publication in new window or tab >>Computing Curvature Sensitivity of Biomolecules in Membranes by Simulated Buckling
2018 (English)In: Journal of Chemical Theory and Computation, ISSN 1549-9618, E-ISSN 1549-9626, Vol. 14, no 3, p. 1643-1655Article in journal (Refereed) Published
Abstract [en]

Membrane curvature sensing, where the binding free energies of membrane-associated molecules depend on the local membrane curvature, is a key factor to modulate and maintain the shape and organization of cell membranes. However, the microscopic mechanisms are not well understood, partly due to absence of efficient simulation methods. Here, we describe a method to compute the curvature dependence of the binding free energy of a membrane associated probe molecule that interacts with a buckled membrane, which has been created by lateral compression of a flat bilayer patch. This buckling approach samples a wide range of curvatures in a single simulation, and anisotropic effects can be extracted from the orientation statistics. We develop an efficient and robust algorithm to extract the motion of the probe along the buckled membrane surface, and evaluate its numerical properties by extensive sampling of three coarse-grained model systems: local lipid density in a curved environment for single-component bilayers, curvature preferences of individual lipids in two-component membranes, and curvature sensing by a homotrimeric transmembrane protein. The method can be used to complement experimental data from curvature partition assays and provides additional insight into mesoscopic theories and molecular mechanisms for curvature sensing.

National Category
Biophysics
Research subject
Biophysics
Identifiers
urn:nbn:se:su:diva-154791 (URN)10.1021/acs.jctc.7b00878 (DOI)000427661400043 ()29350922 (PubMedID)
Available from: 2018-04-17 Created: 2018-04-17 Last updated: 2025-02-20Bibliographically approved
Elías-Wolff, F., Lindén, M., Lyubartsev, A. P. & Brandt, E. G. Curvature sensing by cardiolipin in simulated buckled membranes.
Open this publication in new window or tab >>Curvature sensing by cardiolipin in simulated buckled membranes
(English)In: Article in journal (Refereed) Submitted
National Category
Biophysics
Research subject
Biophysics
Identifiers
urn:nbn:se:su:diva-157413 (URN)
Funder
Swedish Research CouncilSwedish National Infrastructure for Computing (SNIC)EU, Horizon 2020Swedish Foundation for Strategic Research
Available from: 2018-06-18 Created: 2018-06-18 Last updated: 2025-02-20Bibliographically approved
Lindén, M., Elías-Wolff, F., Lyubartsev, A. P. & Brandt, E. G.Curvature sensing by multimeric proteins.
Open this publication in new window or tab >>Curvature sensing by multimeric proteins
(English)Manuscript (preprint) (Other academic)
National Category
Biophysics
Research subject
Biophysics
Identifiers
urn:nbn:se:su:diva-157407 (URN)
Available from: 2018-06-18 Created: 2018-06-18 Last updated: 2025-02-20Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-4200-0191

Search in DiVA

Show all publications