The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Spatial arrangement of proteins in planar and curved membranes by PPM 3.0
Open accessAbstract
Cellular protrusions, invaginations, and many intracellular organelles have strongly curved membrane regions. Transmembrane and peripheral membrane proteins that induce, sense, or stabilize such regions cannot be properly fitted into a single flat bilayer. To treat such proteins, we developed a new method and a web tool, PPM 3.0, for positioning proteins in curved or planar, single or multiple membranes. This method determines the energetically optimal spatial position, the hydrophobic thickness, and the radius of intrinsic curvature of a membrane‐deforming protein structure by arranging it in a single or several sphere‐shaped or planar membrane sections. In addition, it can define the lipid‐embedded regions of a protein that simultaneously spans several membranes or determine the optimal position of a peptide in a spherical micelle. The PPM 3.0 web server operates with 17 types of biological membranes and 4 types of artificial bilayers. It is publicly available at https://opm.phar.umich.edu/ppm_server3. PPM 3.0 was applied to identify and characterize arrangements in membranes of 128 proteins with a significant intrinsic curvature, such as BAR domains, annexins, Piezo, and MscS mechanosensitive channels, cation‐chloride cotransporters, as well as mitochondrial ATP synthases, calcium uniporters, and TOM complexes. These proteins form large complexes that are mainly localized in mitochondria, plasma membranes, and endosomes. Structures of bacterial drug efflux pumps, AcrAB‐TolC, MexAB‐OrpM, and MacAB‐TolC, were positioned in both membranes of the bacterial cell envelop, while structures of multimeric gap‐junction channels were arranged in two opposed cellular membranes.
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Cites
OPM database and PPM web server: resources for positioning of proteins in membranes
Lomize, M. A., Pogozheva, I. D., Joo, H., Mosberg, H. I., & Lomize, A. L. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr703 · Cited by 2,151
Self-citationMembrane recognition by phospholipid-binding domains
Lemmon, M. A. (2008) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2328 · Cited by 1,419
Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures
Sehnal, D., Bittrich, S., Deshpande, M., Svobodová, R., Berka, K., Bazgier, V., Velankar, S., Burley, S. K., Koča, J., & Rose, A. S. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab314 · Cited by 1,154
Protein Data Bank (PDB): The Single Global Macromolecular Structure Archive
Burley, S. K., Berman, H. M., Kleywegt, G. J., Markley, J. L., Nakamura, H., & Velankar, S. (2017) · Methods in Molecular Biology · doi:10.1007/978-1-4939-7000-1_26 · Cited by 1,141
Structure of the mechanically activated ion channel Piezo1
Saotome, K., Murthy, S. E., Kefauver, J. M., Whitwam, T., Patapoutian, A., & Ward, A. B. (2018) · Nature · doi:10.1038/nature25453 · Cited by 649
Mechanism of endophilin N‐BAR domain‐mediated membrane curvature
Gallop, J. L., Jao, C. C., Kent, H. M., Butler, P. J. G., Evans, P. R., Langen, R., & McMahon, H. T. (2006) · The EMBO Journal · doi:10.1038/sj.emboj.7601174 · Cited by 617
Structure of the yeast F 1 F o -ATP synthase dimer and its role in shaping the mitochondrial cristae
Davies, K. M., Anselmi, C., Wittig, I., Faraldo-Gómez, J. D., & Kühlbrandt, W. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1204593109 · Cited by 473
Structure-based membrane dome mechanism for Piezo mechanosensitivity
Guo, Y. R., & MacKinnon, R. (2017) · eLife · doi:10.7554/elife.33660 · Cited by 446
The Hydrophobic Insertion Mechanism of Membrane Curvature Generation by Proteins
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Structure and mechanogating of the mammalian tactile channel PIEZO2
Wang, L., Zhou, H., Zhang, M., Liu, W., Deng, T., Zhao, Q., Li, Y., Lei, J., Li, X., & Xiao, B. (2019) · Nature · doi:10.1038/s41586-019-1505-8 · Cited by 373
Cited by
PMIpred: a physics-informed web server for quantitative protein–membrane interaction prediction
van Hilten, N., Verwei, N., Methorst, J., Nase, C., Bernatavicius, A., & Risselada, H. J. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae069 · Cited by 41
An integrative modelling approach to the mitochondrial cristae
(2025) · doi:10.1038/s42003-025-08381-5 · Cited by 21
MAVISp: A Modular Structure-Based Framework for Protein Variant Effects
Arnaudi, M., Utichi, M., Degn, K., Tiberti, M., Beltrame, L., Krzesińska, K., Sánchez-Izquierdo Besora, P., Kiachaki, E., Scrima, S., Bauer, L., et al. (2022) · doi:10.1101/2022.10.22.513328 · Cited by 20
Nordquist, E. B., Zhao, M., Kumar, A., & MacKerell, A. D. (2024) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.4c01189 · Cited by 15
Nogueira, K. M. V., Mendes, V., Kamath, K. S., Cheruku, A., Oshiquiri, L. H., de Paula, R. G., Carraro, C., Pedersoli, W. R., Pereira, L. M. S., Vieira, L. C., et al. (2024) · Microbial Cell Factories · doi:10.1186/s12934-023-02279-9 · Cited by 12
Metadata
- Authors
- Lomize, A. L., Todd, S. C., & Pogozheva, I. D.
- Venue
- Protein Science
- Publisher
- Wiley
- Published
- 2021-11-08
- Volume
- 31
- Issue
- 1
- Pages
- 209-220
- ISSN
- 0961-8368 (ISSN-L)
- 1469-896X
- OpenAlex
- W3210500140
- Cited by
- 339
- References
- 52
- FWCI
- 9.86
- Type
- journal article
- Language
- en
- Open access
- bronze
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