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蛋白质“液-液相分离”的理论和计算方法进展

张鹏程 方文玉 鲍磊 康文斌

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蛋白质“液-液相分离”的理论和计算方法进展

张鹏程, 方文玉, 鲍磊, 康文斌

Theoretical and computational methods of protein liquid-liquid phase separation

Zhang Peng-Cheng, Fang Wen-Yu, Bao Lei, Kang Wen-Bin
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  • 蛋白质分子的“液-液相分离”是近几年生物物理学领域迅速发展起来的研究热点. 蛋白质相分离在一系列生物学过程中发挥着重要的作用. 蛋白质分子序列和构象的多样性和复杂性, 给蛋白质分子的理论研究、计算机模拟和实验研究都带来了巨大的挑战. 当前, 多尺度理论模型和多分辨率计算方法被广泛地用于蛋白质分子的“液-液相分离”的研究中. 本文将对蛋白质分子“液-液相分离”的理论基础和计算机模拟方法进行简要的综述, 并对这些理论和方法未来的发展趋势进行了初步的探讨和展望. 期望为进一步研究蛋白质“液-液相分离”的物理化学机制和过程提供理论基础和方法借鉴.
    Liquid-liquid phase separation (LLPS) of proteins is an emerging field in the research of biophysics. Many intrinsically disordered proteins (IDPs) are known to have the ability to assemble via LLPS and to organize into protein-rich and dilute phases both in vivo and in vitro. Such a kind of phase separation of proteins plays an important role in a wide range of cellular processes, such as the formation of membraneless organelles (MLOs), signaling transduction, intracellular organization, chromatin organization, etc. In recent years, there appeared a great number of theoretical analysis, computational simulation and experimental research focusing on the physical principles of LLPS. In this article, the theoretical and computational simulation methods for the LLPS are briefly reviewed. To elucidate the physical principle of LLPS and to understand the phase behaviors of the proteins, biophysicists have introduced the concepts and theories from statistical mechanics and polymer sciences. Flory-Huggins theory and its extensions, such as mean-field model, random phase approximation (RPA) and field theory simulations, can conduce to understanding the phase diagram of the LLPS. To reveal the hidden principles in the sequence-dependent phase behaviors of different biomolecular condensates, different simulation methods including lattice models, off-lattice coarse-grained models, and all-atom simulations are introduced to perform computer simulations. By reducing the conformational space of the proteins, lattice models can capture the key points in LLPS and simplify the computations. In the off-lattice models, a polypeptide can be coarse-grained as connected particles representing repeated short peptide fragments. All-atom simulations can describe the structure of proteins at a higher resolution but consume higher computation-power. Multi-scale simulation may provide the key to understanding LLPS at both high computational efficiency and high accuracy. With these methods, we can elucidate the sequence-dependent phase behaviors of proteins at different resolutions. To sum up, it is necessary to choose the appropriate method to model LLPS processes according to the interactions within the molecules and the specific phase behaviors of the system. The simulations of LLPS can facilitate the comprehensive understanding of the key features which regulate the membraneless compartmentalization in cell biology and shed light on the design of artificial cells and the control of neurodegeneration.
      通信作者: 康文斌, wbkang@hbmu.edu.cn
    • 基金项目: 国家级-国家自然科学基金(11947006)
      Corresponding author: Kang Wen-Bin, wbkang@hbmu.edu.cn
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  • 图 1  研究蛋白质“液-液相分离”的计算方法: 从左至右分别是解析模型、粗粒化模型(包括多个残基单个粒子、单个残基单个粒子、单个残基多个粒子的模型)和全原子模型, 分辨率的提升对计算资源的耗费程度急剧增高, 而模型假设数的减少会减弱研究涌现行为的能力[35]

    Fig. 1.  Computational approaches utilized to study protein liquid-liquid phase separation (LLPS). From left to right are the analytical model, the coarse-grained model (multiple-residues per bead, single-bead per residue and multiple-beads per residue coarse-grained models), and all-atom model. High-resolution descriptions increase the computational cost of the simulations. All-atom model is often impractical for the study of emergent behavior of LLPS[35].

  • [1]

    McCarty J, Delaney K T, Danielsen S P, Fredrickson G H, Shea J E 2019 J. Phys. Chem. Lett. 10 1644Google Scholar

    [2]

    Lin Y H, Song J H, Forman-Kay J D, Chan H S 2017 J. Mol. Liq. 228 176Google Scholar

    [3]

    Lin Y H, Song J H, Forman-Kay J D, Chan H S 2019 J. Mol. Liq. 273 676Google Scholar

    [4]

    Dignon G L, Zheng W W, Kim Y C, Mittal J, Best R B 2018 Biophys. J. 114 431aGoogle Scholar

    [5]

    Dignon G L, Zheng W W, Best R B, Mittal J 2017 Biophys. J. 112 200a

    [6]

    Choi J M, Mitrea D M, Stanley C B, Ruff K M, Holehouse A S, Kriwacki R W, Pappu R V 2019 Biophys. J. 116 349aGoogle Scholar

    [7]

    Chin A F, Hilser V J, Zheng Y X 2019 Biophys. J. 116 179aGoogle Scholar

    [8]

    周丰茂, 孙东科, 朱鸣芳 2010 物理学报 59 3394Google Scholar

    Zhou F M, Sun D K, Zhu M F 2010 Acta Phys. Sin. 59 3394Google Scholar

    [9]

    张长胜, 来鲁华 2010 物理化学学报 36 1907053Google Scholar

    Zhang C S, Lai L H 2010 Acta Phys. Chim. Sin. 36 1907053Google Scholar

    [10]

    Burke K A, Janke A M, Rhine C L, Fawzi N L 2015 Mol. Cell 60 231Google Scholar

    [11]

    Brangwynne C P, Tompa P, Pappu R V 2015 Nat. Phys. 11 899Google Scholar

    [12]

    Uversky V N 2017 Curr. Opin. Struct. Biol. 44 18Google Scholar

    [13]

    Feric M, Vaidya N, Harmon T S, Mitrea D M, Zhu L, Richardson T M, Kriwacki R W, Pappu R V, Brangwynne C P 2016 Cell 165 1686Google Scholar

    [14]

    Falahati H, Wieschaus E 2017 Proc. Natl. Acad. Sci. U.S.A. 114 1335Google Scholar

    [15]

    Sabari B R, Dall'Agnese A, Boija A, Klein I A, Coffey E L, Shrinivas K, Abraham B J, Hannett N M, Zamudio A V, Manteiga J C, Li C H, Guo Y E, Day D S, Schuijers J, Vasile E, Malik S, Hnisz D, Lee T I, Cisse, I I, Roeder R G, Sharp P A, Chakraborty A K, Young R A 2018 Science 361 eaar3958Google Scholar

    [16]

    Das R K, Pappu R V 2013 Proc. Natl. Acad. Sci. U.S.A. 110 13392Google Scholar

    [17]

    Dignon G L, Zheng W W, Best R B, Kim Y C, Mittal J 2018 Proc. Natl. Acad. Sci. U.S.A. 115 9929Google Scholar

    [18]

    Harmon T S, Holehouse A S, Rosen M K, Pappu R V 2017 ELIFE 6 e30294Google Scholar

    [19]

    Kang W B, He C, Liu Z X, Wang J, Wang W 2019 J. Biomol. Struct. Dyn. 37 1956Google Scholar

    [20]

    Lin Y, Currie S L, Rosen M K 2017 J. Biol. Chem. 292 19110Google Scholar

    [21]

    Lin Y H, Brady J P, Forman-Kay J D, Chan H S 2017 New J. Phys. 19 115003Google Scholar

    [22]

    Schuster B S, Dignon G, Jahnke C, Good M C, Hammer D A, Mittal J 2019 Biophys. J. 116 453aGoogle Scholar

    [23]

    Smith J, Calidas D, Schmidt H, Lu T, Seydoux G 2016 ELIFE 5 e21337Google Scholar

    [24]

    Uebel C J, Anderson D C, Mandarino L M, Manage K I, Aynaszyan S, Phillips C M 2018 Plos Genet. 14 e1007542Google Scholar

    [25]

    康文斌, 王骏, 王炜 2018 物理学报 67 058701Google Scholar

    Kang W B, Wang J, Wang W 2018 Acta Phys. Sin. 67 058701Google Scholar

    [26]

    Pak C W, Kosno M, Holehouse A S, Padrick S B, Mittal A, A R, Yunus A A, Liu D R, Pappu R V, Rosen M K 2016 Mol. Cell 63 72Google Scholar

    [27]

    Gates Z P, Baxa M C, Yu W, Riback J A, Li H, Roux B, Kent S B, Sosnick T R 2017 Proc. Natl. Acad. Sci. U.S.A. 114 2241Google Scholar

    [28]

    Riback J A, Katanski C D, Kear-Scott J L, Pilipenko E V, Rojek A E, Sosnick T R, Drummond D A 2017 Cell 168 1028Google Scholar

    [29]

    Das R K, Ruff K M, Pappu R V 2015 Curr. Opin. Struct. Biol. 32 102Google Scholar

    [30]

    Vitalis A, Wang X, Pappu R V 2007 Biophys. J. 93 1923Google Scholar

    [31]

    Papoian G A 2008 Proc. Natl. Acad. Sci. U. S. A. 105 14237Google Scholar

    [32]

    Levine Z A, Shea J E 2017 Curr. Opin. Struct. Biol. 43 95Google Scholar

    [33]

    Dignon G L, Zheng W, Kim Y C, Mittal J 2019 ACS Central Sci. 5 821Google Scholar

    [34]

    Murthy A C, Dignon G L, Kan Y, Zerze G H, Parekh S H, Mittal J, Fawzi N L 2019 Nat. Struct. Mol. Biol. 26 637Google Scholar

    [35]

    Ruff K M, Pappu R V, Holehouse A S 2019 Curr. Opin. Struct. Biol. 56 1Google Scholar

    [36]

    Monahan Z, Ryan V H, Janke A M, Burke K A, Rhoads S N, Zerze G H, O'Meally R, Dignon G L, Conicella A E, Zheng W W, Best R B, Cole R N, Mittal J, Shewmaker F, Fawzi N L 2017 EMBO J. 36 2951Google Scholar

    [37]

    Best R B 2017 Curr. Opin. Struct. Biol. 42 147Google Scholar

    [38]

    Robustelli P, Piana S, Shaw D E 2018 Proc. Natl. Acad. Sci. U.S.A. 115 E4758Google Scholar

    [39]

    van L R, Buljan M, Lang B, Weatheritt R J, Daughdrill G W, Dunker A K, Fuxreiter M, Gough J, Gsponer J, Jones D T, Kim P M, Kriwacki R W, Oldfield C J, Pappu R V, Tompa P, Uversky V N, Wright P E, Babu M M 2014 Chem. Rev. 114 6589Google Scholar

    [40]

    Mittag T, Forman-Kay J D 2007 Curr. Opin. Struct. Biol. 17 3Google Scholar

    [41]

    Flory P J 1942 J. Chem. Phys. 10 51Google Scholar

    [42]

    Huggins M L 1942 J. Chem. Phys. 46 151Google Scholar

    [43]

    Samanta H S, Zhuravlev P I, Hinczewski M, Hori N, Chakrabarti S, Thirumalai D 2017 Soft Matter 13 3622Google Scholar

    [44]

    Zhou H X, Nguemaha V, Mazarakos K, Qin S B 2018 Trends Biochem. Sci. 43 499Google Scholar

    [45]

    Lin Y H, Forman-Kay J D, Chan H S 2016 Phys. Rev. Lett. 117 178101Google Scholar

    [46]

    Liu Y X, Zhang H D, Tong C H, Yang Y L 2011 Macromolecules 44 8261Google Scholar

    [47]

    Speck T, Menzel A M, Bialke J, Lowen H 2015 J. Chem. Phys. 142 224109Google Scholar

    [48]

    Burke M G, Woscholski R, Yaliraki S N 2003 Proc. Natl. Acad. Sci. U.S.A. 100 13928Google Scholar

    [49]

    Ruff K M, Khan S J, Pappu R V 2014 Biophys. J. 107 1226Google Scholar

    [50]

    Zuccato C, Valenza M, Cattaneo E 2010 Physiol. Rev. 90 905Google Scholar

    [51]

    Condon J E, Martin T B, Jayaraman A 2017 Soft Matter 13 2907Google Scholar

    [52]

    Dignon G L, Zheng W, Kim Y C, Best R B, Mittal J 2018 PLOS Comput. Biol. 14 e1005941Google Scholar

    [53]

    Das S, Eisen A, Lin Y H, Chan H S 2018 J. Phys. Chem. B 122 5418Google Scholar

    [54]

    Kapcha L H, Rossky P J 2014 J. Mol. Boil. 426 484Google Scholar

    [55]

    Ashbaugh H S, Hatch H W 2008 J. Am. Chem. Soc. 130 9536Google Scholar

    [56]

    Ghavami A, Veenhoff L M, van der Giessen E, Onck P R 2014 Biophys. J. 107 1393Google Scholar

    [57]

    Borgia A, Borgia M B, Bugge K, Kissling V M, Heidarsson P O, Fernandes C B, Sottini A, Soranno A, Buholzer K J, Nettels D, Kragelund B B, Best R B, Schuler B 2018 Nature 555 61Google Scholar

    [58]

    Wang J, Choi J M, Holehouse A S, Lee H O, Zhang X, Jahnel M, Maharana S, Lemaitre R, Pozniakovsky A, Drechsel D, Poser I, Pappu R V, Alberti S, Hyman A A 2018 Cell 174 688Google Scholar

    [59]

    Song J, Gomes G N, Shi T, Gradinaru C C, Chan H S 2017 Biophys. J. 113 1012Google Scholar

    [60]

    Noid W G 2013 J. Chem. Phys. 139 090901Google Scholar

    [61]

    Voegler Smith A, Hall C K 2001 Proteins 44 344Google Scholar

    [62]

    Marchut A J, Hall C K 2006 Biophys. J. 90 4574Google Scholar

    [63]

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出版历程
  • 收稿日期:  2020-03-24
  • 修回日期:  2020-04-10
  • 上网日期:  2020-05-09
  • 刊出日期:  2020-07-05

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