{"title":"优先结合作为脂质结构域形成的驱动机制。","authors":"Roman Ye. Brodskii , Olga V. Vashchenko","doi":"10.1016/j.jsb.2025.108226","DOIUrl":null,"url":null,"abstract":"<div><div>Lipid membranes are uniquely complex biological structures with large and still undisclosed regulatory potential in many living processes caused by versatile changes in their structure while adsorption of various guest molecules (dopants). This work is devoted to exploring spontaneous dopant-driven formation of lipid domains in a monolipid membrane observed experimentally for dopants with bimodal adsorption. The work offers the results obtained for a wide range of different cases exploiting our proposed original simulation method and numerical model. The central idea of the approach is dopant binding ‘like the surroundings’, i.e. preferential binding.</div><div>The value range of the preferential binding extent was determined, where stable domains are formed and their size distribution becomes steady. The density of domain size distribution is power-law, i.e. the domain patterns possesses self-similarity. Outside this range, only one phase dominates if the extent is too large, whereas if it is too small, great dispersion of membrane was observed, so the membrane is physically homogeneous. Various neighboring as well as different methods of calculation of dopant binding probabilities are considered. The results obtained differed quantitatively but not qualitatively. The suggested model and the domain definition are similar to those used in percolation theory. Thus, the results can be applicated to percolation problems.</div><div>Grounding on analysis of literature data on domain patterns formed in various lipid systems, we suggested that the preferential binding mechanism is in line with the mechanism of preferential neighboring which is implicitly assumed in such systems irrespective of their specific nature.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 3","pages":"Article 108226"},"PeriodicalIF":3.0000,"publicationDate":"2025-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Preferential binding as a driving mechanism of lipid domains formation\",\"authors\":\"Roman Ye. Brodskii , Olga V. Vashchenko\",\"doi\":\"10.1016/j.jsb.2025.108226\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Lipid membranes are uniquely complex biological structures with large and still undisclosed regulatory potential in many living processes caused by versatile changes in their structure while adsorption of various guest molecules (dopants). This work is devoted to exploring spontaneous dopant-driven formation of lipid domains in a monolipid membrane observed experimentally for dopants with bimodal adsorption. The work offers the results obtained for a wide range of different cases exploiting our proposed original simulation method and numerical model. The central idea of the approach is dopant binding ‘like the surroundings’, i.e. preferential binding.</div><div>The value range of the preferential binding extent was determined, where stable domains are formed and their size distribution becomes steady. The density of domain size distribution is power-law, i.e. the domain patterns possesses self-similarity. Outside this range, only one phase dominates if the extent is too large, whereas if it is too small, great dispersion of membrane was observed, so the membrane is physically homogeneous. Various neighboring as well as different methods of calculation of dopant binding probabilities are considered. The results obtained differed quantitatively but not qualitatively. The suggested model and the domain definition are similar to those used in percolation theory. Thus, the results can be applicated to percolation problems.</div><div>Grounding on analysis of literature data on domain patterns formed in various lipid systems, we suggested that the preferential binding mechanism is in line with the mechanism of preferential neighboring which is implicitly assumed in such systems irrespective of their specific nature.</div></div>\",\"PeriodicalId\":17074,\"journal\":{\"name\":\"Journal of structural biology\",\"volume\":\"217 3\",\"pages\":\"Article 108226\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of structural biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1047847725000619\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of structural biology","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1047847725000619","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Preferential binding as a driving mechanism of lipid domains formation
Lipid membranes are uniquely complex biological structures with large and still undisclosed regulatory potential in many living processes caused by versatile changes in their structure while adsorption of various guest molecules (dopants). This work is devoted to exploring spontaneous dopant-driven formation of lipid domains in a monolipid membrane observed experimentally for dopants with bimodal adsorption. The work offers the results obtained for a wide range of different cases exploiting our proposed original simulation method and numerical model. The central idea of the approach is dopant binding ‘like the surroundings’, i.e. preferential binding.
The value range of the preferential binding extent was determined, where stable domains are formed and their size distribution becomes steady. The density of domain size distribution is power-law, i.e. the domain patterns possesses self-similarity. Outside this range, only one phase dominates if the extent is too large, whereas if it is too small, great dispersion of membrane was observed, so the membrane is physically homogeneous. Various neighboring as well as different methods of calculation of dopant binding probabilities are considered. The results obtained differed quantitatively but not qualitatively. The suggested model and the domain definition are similar to those used in percolation theory. Thus, the results can be applicated to percolation problems.
Grounding on analysis of literature data on domain patterns formed in various lipid systems, we suggested that the preferential binding mechanism is in line with the mechanism of preferential neighboring which is implicitly assumed in such systems irrespective of their specific nature.
期刊介绍:
Journal of Structural Biology (JSB) has an open access mirror journal, the Journal of Structural Biology: X (JSBX), sharing the same aims and scope, editorial team, submission system and rigorous peer review. Since both journals share the same editorial system, you may submit your manuscript via either journal homepage. You will be prompted during submission (and revision) to choose in which to publish your article. The editors and reviewers are not aware of the choice you made until the article has been published online. JSB and JSBX publish papers dealing with the structural analysis of living material at every level of organization by all methods that lead to an understanding of biological function in terms of molecular and supermolecular structure.
Techniques covered include:
• Light microscopy including confocal microscopy
• All types of electron microscopy
• X-ray diffraction
• Nuclear magnetic resonance
• Scanning force microscopy, scanning probe microscopy, and tunneling microscopy
• Digital image processing
• Computational insights into structure