Assembly of Protein Complexes in and on the Membrane with Predicted Spatial Arrangement Constraints
Copyright © 2024 Elsevier Ltd. All rights reserved..
Membrane proteins play crucial roles in various cellular processes, and their interactions with other proteins in and on the membrane are essential for their proper functioning. While an increasing number of structures of more membrane proteins are being determined, the available structure data is still sparse. To gain insights into the mechanisms of membrane protein complexes, computational docking methods are necessary due to the challenge of experimental determination. Here, we introduce Mem-LZerD, a rigid-body membrane docking algorithm designed to take advantage of modern membrane modeling and protein docking techniques to facilitate the docking of membrane protein complexes. Mem-LZerD is based on the LZerD protein docking algorithm, which has been constantly among the top servers in many rounds of CAPRI protein docking assessment. By employing a combination of geometric hashing, newly constrained by the predicted membrane height and tilt angle, and model scoring accounting for the energy of membrane insertion, we demonstrate the capability of Mem-LZerD to model diverse membrane protein-protein complexes. Mem-LZerD successfully performed unbound docking on 13 of 21 (61.9%) transmembrane complexes in an established benchmark, more than shown by previous approaches. It was additionally tested on new datasets of 44 transmembrane complexes and 92 peripheral membrane protein complexes, of which it successfully modeled 35 (79.5%) and 15 (16.3%) complexes respectively. When non-blind orientations of peripheral targets were included, the number of successes increased to 54 (58.7%). We further demonstrate that Mem-LZerD produces complex models which are suitable for molecular dynamics simulation. Mem-LZerD is made available at https://lzerd.kiharalab.org.
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:436 |
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| Enthalten in: |
Journal of molecular biology - 436(2024), 6 vom: 15. März, Seite 168486 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Christoffer, Charles [VerfasserIn] |
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Journal Article |
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Date Completed 18.03.2024 Date Revised 18.03.2024 published: Print-Electronic UpdateOf: bioRxiv. 2023 Nov 09;:. - PMID 37961264 Citation Status MEDLINE |
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| doi: |
10.1016/j.jmb.2024.168486 |
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NLM368256928 |
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| 500 | |a UpdateOf: bioRxiv. 2023 Nov 09;:. - PMID 37961264 | ||
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| 520 | |a Copyright © 2024 Elsevier Ltd. All rights reserved. | ||
| 520 | |a Membrane proteins play crucial roles in various cellular processes, and their interactions with other proteins in and on the membrane are essential for their proper functioning. While an increasing number of structures of more membrane proteins are being determined, the available structure data is still sparse. To gain insights into the mechanisms of membrane protein complexes, computational docking methods are necessary due to the challenge of experimental determination. Here, we introduce Mem-LZerD, a rigid-body membrane docking algorithm designed to take advantage of modern membrane modeling and protein docking techniques to facilitate the docking of membrane protein complexes. Mem-LZerD is based on the LZerD protein docking algorithm, which has been constantly among the top servers in many rounds of CAPRI protein docking assessment. By employing a combination of geometric hashing, newly constrained by the predicted membrane height and tilt angle, and model scoring accounting for the energy of membrane insertion, we demonstrate the capability of Mem-LZerD to model diverse membrane protein-protein complexes. Mem-LZerD successfully performed unbound docking on 13 of 21 (61.9%) transmembrane complexes in an established benchmark, more than shown by previous approaches. It was additionally tested on new datasets of 44 transmembrane complexes and 92 peripheral membrane protein complexes, of which it successfully modeled 35 (79.5%) and 15 (16.3%) complexes respectively. When non-blind orientations of peripheral targets were included, the number of successes increased to 54 (58.7%). We further demonstrate that Mem-LZerD produces complex models which are suitable for molecular dynamics simulation. Mem-LZerD is made available at https://lzerd.kiharalab.org | ||
| 650 | 4 | |a Journal Article | |
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| 700 | 1 | |a Harini, Kannan |e verfasserin |4 aut | |
| 700 | 1 | |a Archit, Gupta |e verfasserin |4 aut | |
| 700 | 1 | |a Kihara, Daisuke |e verfasserin |4 aut | |
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