Suppr超能文献

结构异质性在跨膜蛋白同源二聚化中的作用。

The role of structural heterogeneity in the homodimerization of transmembrane proteins.

机构信息

Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, USA.

出版信息

J Chem Phys. 2023 Oct 7;159(13). doi: 10.1063/5.0159801.

Abstract

The equilibrium association of transmembrane proteins plays a fundamental role in membrane protein function and cellular signaling. While the study of the equilibrium binding of single pass transmembrane proteins has received significant attention in experiment and simulation, the accurate assessment of equilibrium association constants remains a challenge to experiment and simulation. In experiment, there remain wide variations in association constants derived from experimental studies of the most widely studied transmembrane proteins. In simulation, state-of-the art methods have failed to adequately sample the thermodynamically relevant structures of the dimer state ensembles using coarse-grained models. In addition, all-atom force fields often fail to accurately assess the relative free energies of the dimer and monomer states. Given the importance of this fundamental biophysical process, it is essential to address these shortcomings. In this work, we establish an effective computational protocol for the calculation of equilibrium association constants for transmembrane homodimer formation. A set of transmembrane protein homodimers, used in the parameterization of the MARTINI v3 force field, are simulated using metadynamics, based on three collective variables. The method is found to be accurate and computationally efficient, providing a standard to be used in the future simulation studies using coarse-grained or all-atom models.

摘要

跨膜蛋白的平衡缔合在膜蛋白功能和细胞信号转导中起着至关重要的作用。虽然对单次跨膜蛋白的平衡结合的研究在实验和模拟中受到了广泛关注,但准确评估平衡缔合常数仍然是实验和模拟的一个挑战。在实验中,从最广泛研究的跨膜蛋白的实验研究中得出的缔合常数仍存在广泛的差异。在模拟中,最先进的方法未能使用粗粒模型充分采样二聚体状态集合的热力学相关结构。此外,全原子力场通常无法准确评估二聚体和单体状态的相对自由能。鉴于这个基本生物物理过程的重要性,解决这些缺点至关重要。在这项工作中,我们建立了一种计算跨膜同源二聚体形成平衡缔合常数的有效计算方案。使用基于三个集体变量的元动力学方法对 MARTINI v3 力场参数化中使用的一组跨膜蛋白同源二聚体进行了模拟。该方法被证明是准确和计算高效的,为未来使用粗粒或全原子模型进行模拟研究提供了一个标准。

相似文献

2
On Computing Equilibrium Binding Constants for Protein-Protein Association in Membranes.
J Chem Theory Comput. 2022 Jun 14;18(6):3961-3971. doi: 10.1021/acs.jctc.2c00106. Epub 2022 May 17.
3
Addressing the Excessive Aggregation of Membrane Proteins in the MARTINI Model.
J Chem Theory Comput. 2021 Apr 13;17(4):2513-2521. doi: 10.1021/acs.jctc.0c01253. Epub 2021 Mar 15.
4
MARTINI-Compatible Coarse-Grained Model for the Mesoscale Simulation of Peptoids.
J Phys Chem B. 2020 Sep 10;124(36):7745-7764. doi: 10.1021/acs.jpcb.0c04567. Epub 2020 Aug 31.
5
Machine Learning Derived Collective Variables for the Study of Protein Homodimerization in Membrane.
J Chem Theory Comput. 2024 Jul 9;20(13):5774-5783. doi: 10.1021/acs.jctc.4c00454. Epub 2024 Jun 25.
6
Free-energy landscapes of transmembrane homodimers by bias-exchange adaptively biased molecular dynamics.
Biophys Chem. 2024 Apr;307:107190. doi: 10.1016/j.bpc.2024.107190. Epub 2024 Jan 22.
8
Automated Parameterization of Coarse-Grained Polyethylenimine under a Martini Framework.
J Chem Inf Model. 2023 Jul 24;63(14):4328-4341. doi: 10.1021/acs.jcim.3c00103. Epub 2023 Jul 9.
9
Effect of Protein Flexibility from Coarse-Grained Elastic Network Parameterizations on the Calculation of Free Energy Profiles of Ligand Binding.
J Chem Theory Comput. 2020 Jul 14;16(7):4734-4743. doi: 10.1021/acs.jctc.0c00418. Epub 2020 Jun 18.
10
All-atom and coarse-grained simulations of the forced unfolding pathways of the SNARE complex.
Proteins. 2014 Jul;82(7):1376-86. doi: 10.1002/prot.24505. Epub 2014 Feb 6.

引用本文的文献

1
Machine Learning Derived Collective Variables for the Study of Protein Homodimerization in Membrane.
J Chem Theory Comput. 2024 Jul 9;20(13):5774-5783. doi: 10.1021/acs.jctc.4c00454. Epub 2024 Jun 25.
2
A Rigorous Framework for Calculating Protein-Protein Binding Affinities in Membranes.
J Chem Theory Comput. 2023 Dec 26;19(24):9077-9092. doi: 10.1021/acs.jctc.3c00941. Epub 2023 Dec 13.

本文引用的文献

1
Synergistic computational and experimental studies of a phosphoglycosyl transferase membrane/ligand ensemble.
J Biol Chem. 2023 Oct;299(10):105194. doi: 10.1016/j.jbc.2023.105194. Epub 2023 Aug 25.
3
On Computing Equilibrium Binding Constants for Protein-Protein Association in Membranes.
J Chem Theory Comput. 2022 Jun 14;18(6):3961-3971. doi: 10.1021/acs.jctc.2c00106. Epub 2022 May 17.
5
Martini 3: a general purpose force field for coarse-grained molecular dynamics.
Nat Methods. 2021 Apr;18(4):382-388. doi: 10.1038/s41592-021-01098-3. Epub 2021 Mar 29.
6
Addressing the Excessive Aggregation of Membrane Proteins in the MARTINI Model.
J Chem Theory Comput. 2021 Apr 13;17(4):2513-2521. doi: 10.1021/acs.jctc.0c01253. Epub 2021 Mar 15.
8
Atomistic mechanism of transmembrane helix association.
PLoS Comput Biol. 2020 Jun 4;16(6):e1007919. doi: 10.1371/journal.pcbi.1007919. eCollection 2020 Jun.
9
Balancing Force Field Protein-Lipid Interactions To Capture Transmembrane Helix-Helix Association.
J Chem Theory Comput. 2018 Mar 13;14(3):1706-1715. doi: 10.1021/acs.jctc.7b00983. Epub 2018 Feb 9.
10
Excessive aggregation of membrane proteins in the Martini model.
PLoS One. 2017 Nov 13;12(11):e0187936. doi: 10.1371/journal.pone.0187936. eCollection 2017.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验