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Assembly of Protein Complexes In and On the Membrane with Predicted Spatial Arrangement Constraints

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 s...

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Autores principales: Christoffer, Charles, Harini, Kannan, Archit, Gupta, Kihara, Daisuke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634698/
https://www.ncbi.nlm.nih.gov/pubmed/37961264
http://dx.doi.org/10.1101/2023.10.20.563303
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author Christoffer, Charles
Harini, Kannan
Archit, Gupta
Kihara, Daisuke
author_facet Christoffer, Charles
Harini, Kannan
Archit, Gupta
Kihara, Daisuke
author_sort Christoffer, Charles
collection PubMed
description 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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spelling pubmed-106346982023-11-13 Assembly of Protein Complexes In and On the Membrane with Predicted Spatial Arrangement Constraints Christoffer, Charles Harini, Kannan Archit, Gupta Kihara, Daisuke bioRxiv Article 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. Cold Spring Harbor Laboratory 2023-11-09 /pmc/articles/PMC10634698/ /pubmed/37961264 http://dx.doi.org/10.1101/2023.10.20.563303 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Christoffer, Charles
Harini, Kannan
Archit, Gupta
Kihara, Daisuke
Assembly of Protein Complexes In and On the Membrane with Predicted Spatial Arrangement Constraints
title Assembly of Protein Complexes In and On the Membrane with Predicted Spatial Arrangement Constraints
title_full Assembly of Protein Complexes In and On the Membrane with Predicted Spatial Arrangement Constraints
title_fullStr Assembly of Protein Complexes In and On the Membrane with Predicted Spatial Arrangement Constraints
title_full_unstemmed Assembly of Protein Complexes In and On the Membrane with Predicted Spatial Arrangement Constraints
title_short Assembly of Protein Complexes In and On the Membrane with Predicted Spatial Arrangement Constraints
title_sort assembly of protein complexes in and on the membrane with predicted spatial arrangement constraints
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634698/
https://www.ncbi.nlm.nih.gov/pubmed/37961264
http://dx.doi.org/10.1101/2023.10.20.563303
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