It is emerging to become a generic phenomenon that biomolecules involved in cell signal transduction do not interact with each other through a stochastic process, but tend to organize into high-ordered spatial patterns via physical processes of phase separation. Recent revolution of experimental technology in biophysics and structural biology such as electron microscopy or super-resolution imaging harness the discovery of such spatial organizations in a large variety of distinctive signaling events. For instance, the polymerization of death domain proteins into filamentous complexes called inflammasome provides a spatial platform for the downstream recruitment of caspases, therefore activating cell apoptosis. In another example, the aggregation and clustering of cell adhesion molecules such as neurexin at the synaptic interface between neurons play an important role in regulating the development of the nervous system. In contrast to these examples of experimental progress, the molecular mechanisms underlying the biomolecular pattern formation and their further implication in cellular functions remain poorly understood.

Intuitively, the cooperativity during the assembly of large molecular signaling machinery facilitates cells to exhibit an all-or-none transition only when there is a persistent and high dose of stimulation, which is called a threshold response. Additionally, biological noises due to conformational fluctuations of macromolecules or randomness in molecular diffusions can be significantly reduced through the spatial formation of high-order molecular patterns. We hypothesize that micrometer-scale spatial organization of proteins has evolved as a ubiquitous procedure in signaling and is a critical factor for these molecules to pursue their functions in cells. Consequently, the researches of my laboratory are focusing on developing multiscale simulation methods, machine-learning models, and bioinformatics tools to quantitatively unravel the molecular mechanisms in phase separation of signaling molecules and their biomedical impacts. Based on our predictive models and experimental validation, we can further design and engineer new interfaces of molecule recognition to modulate different signaling pathways including immune responses and neural connectivity. This integrative and collaborative study paves the way for novel therapeutic approaches to the treatment of various diseases such as cancer and age-related disorders.        

1. Computational Simulation of Holin S105 in Membrane Bilayer and Its Dimerization Through a Helix-Turn-Helix Motif.

Zhou B, Wu Y, Su Z.

J Membr Biol. 2021 Jun 29. doi: 10.1007/s00232-021-00187-w. Online ahead of print.

2. Mechanistic dissection of spatial organization in NF-κB signaling pathways by hybrid simulations.

Wu Y, Dhusia K, Su Z.

Integr Biol (Camb). 2021 May 18;13(5):109-120. doi: 10.1093/intbio/zyab006.

3. A multiscale study on the mechanisms of spatial organization in ligand-receptor interactions on cell surfaces.

Su Z, Dhusia K, Wu Y.

Comput Struct Biotechnol J. 2021 Mar 23;19:1620-1634. doi: 10.1016/j.csbj.2021.03.024. eCollection 2021.

4. Computational Assessment of Protein-Protein Binding Affinity by Reverse Engineering the Energetics in Protein Complexes.

Wang B, Su Z, Wu Y.

Genomics Proteomics Bioinformatics. 2021 Apr 7:S1672-0229(21)00076-0. doi: 10.1016/j.gpb.2021.03.004. Online ahead of print.

5. A computational study of co-inhibitory immune complex assembly at the interface between T cells and antigen presenting cells.

Su Z, Dhusia K, Wu Y.

PLoS Comput Biol. 2021 Mar 8;17(3):e1008825. doi: 10.1371/journal.pcbi.1008825. eCollection 2021 Mar.

6. Characterizing the function of domain linkers in regulating the dynamics of multi-domain fusion proteins by microsecond molecular dynamics simulations and artificial intelligence.

Wang B, Su Z, Wu Y.

Proteins. 2021 Jul;89(7):884-895. doi: 10.1002/prot.26066. Epub 2021 Mar 27.

7. Understanding the impacts of cellular environments on ligand binding of membrane receptors by computational simulations.

Su Z, Dhusia K, Wu Y.

J Chem Phys. 2021 Feb 7;154(5):055101. doi: 10.1063/5.0035970.

8. Understanding the Targeting Mechanisms of Multi-Specific Biologics in Immunotherapy with Multiscale Modeling.

Su Z, Wang B, Almo SC, Wu Y.

iScience. 2020 Nov 20;23(12):101835. doi: 10.1016/j.isci.2020.101835. eCollection 2020 Dec 18.

9. Understand the Functions of Scaffold Proteins in Cell Signaling by a Mesoscopic Simulation Method.

Su Z, Dhusia K, Wu Y.

Biophys J. 2020 Nov 17;119(10):2116-2126. doi: 10.1016/j.bpj.2020.10.002. Epub 2020 Oct 14.

10. Cadherin clusters stabilized by a combination of specific and nonspecific cis-interactions.

Thompson CJ, Su Z, Vu VH, Wu Y, Leckband DE, Schwartz DK.

Elife. 2020 Sep 2;9:e59035. doi: 10.7554/eLife.59035.

11. Using Coarse-Grained Simulations to Characterize the Mechanisms of Protein-Protein Association.

Dhusia K, Su Z, Wu Y.

Biomolecules. 2020 Jul 15;10(7):1056. doi: 10.3390/biom10071056.

12. Understanding the Impacts of Conformational Dynamics on the Regulation of Protein-Protein Association by a Multiscale Simulation Method.

Dhusia K, Su Z, Wu Y.

J Chem Theory Comput. 2020 Aug 11;16(8):5323-5333. doi: 10.1021/acs.jctc.0c00439. Epub 2020 Jul 29.

13. A Multiscale and Comparative Model for Receptor Binding of 2019 Novel Coronavirus and the Implication of its Life Cycle in Host Cells.

Su Z, Wu Y.

bioRxiv. 2020 Feb 21:2020.02.20.958272. doi: 10.1101/2020.02.20.958272. Preprint.

14. A Systematic Test of Receptor Binding Kinetics for Ligands in Tumor Necrosis Factor Superfamily by Computational Simulations.

Su Z, Wu Y.

Int J Mol Sci. 2020 Mar 5;21(5):1778. doi: 10.3390/ijms21051778.

15. A computational model for understanding the oligomerization mechanisms of TNF receptor superfamily.

Su Z, Wu Y.

Comput Struct Biotechnol J. 2020 Jan 18;18:258-270. doi: 10.1016/j.csbj.2019.12.016. eCollection 2020.

16. Multiscale simulation unravel the kinetic mechanisms of inflammasome assembly.

Su Z, Wu Y.

Biochim Biophys Acta Mol Cell Res. 2020 Feb;1867(2):118612. doi: 10.1016/j.bbamcr.2019.118612. Epub 2019 Nov 21.

17. Computational simulations of TNF receptor oligomerization on plasma membrane.

Su Z, Wu Y.

Proteins. 2020 May;88(5):698-709. doi: 10.1002/prot.25854. Epub 2019 Nov 18.

18. A Multiscale Model for the Self-Assembly of Coat Proteins in Bacteriophage MS2.

Wang B, Zhang J, Wu Y.

J Chem Inf Model. 2019 Sep 23;59(9):3899-3909. doi: 10.1021/acs.jcim.9b00514. Epub 2019 Aug 23.

19. Understanding Effects of PAMAM Dendrimer Size and Surface Chemistry on Serum Protein Binding with Discrete Molecular Dynamics Simulations.

Wang B, Sun Y, Davis TP, Ke PC, Wu Y, Ding F.

ACS Sustain Chem Eng. 2018 Sep 4;6(9):11704-11715. doi: 10.1021/acssuschemeng.8b01959. Epub 2018 Jul 31.

20. Computational studies of protein-protein dissociation by statistical potential and coarse-grained simulations: a case study on interactions between colicin E9 endonuclease and immunity proteins.

Su Z , Wu Y .

Phys Chem Chem Phys. 2019 Jan 30;21(5):2463-2471. doi: 10.1039/c8cp05644g.

21. Integrating Structural Information to Study the Dynamics of Protein-Protein Interactions in Cells.

Wang B, Xie ZR, Chen J, Wu Y.

Structure. 2018 Oct 2;26(10):1414-1424.e3. doi: 10.1016/j.str.2018.07.010. Epub 2018 Aug 30.

22. A Multiscale Computational Model for Simulating the Kinetics of Protein Complex Assembly.

Chen J, Wu Y.

Methods Mol Biol. 2018;1764:401-411. doi: 10.1007/978-1-4939-7759-8_26.

23. Structural Characterization and Function Prediction of Immunoglobulin-like Fold in Cell Adhesion and Cell Signaling.

Chen J, Wang B, Wu Y.

J Chem Inf Model. 2018 Feb 26;58(2):532-542. doi: 10.1021/acs.jcim.7b00580. Epub 2018 Jan 30.

24. General principles of binding between cell surface receptors and multi-specific ligands: A computational study.

Chen J, Almo SC, Wu Y.

PLoS Comput Biol. 2017 Oct 10;13(10):e1005805. doi: 10.1371/journal.pcbi.1005805. eCollection 2017 Oct.

25. Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning.

Xie ZR, Chen J, Wu Y.

Sci Rep. 2017 Apr 18;7:46622. doi: 10.1038/srep46622.

26. Understanding the Functional Roles of Multiple Extracellular Domains in Cell Adhesion Molecules with a Coarse-Grained Model.

Chen J, Wu Y.

J Mol Biol. 2017 Apr 7;429(7):1081-1095. doi: 10.1016/j.jmb.2017.02.013. Epub 2017 Feb 22.

27. Understand protein functions by comparing the similarity of local structural environments.

Chen J, Xie ZR, Wu Y.

Biochim Biophys Acta Proteins Proteom. 2017 Feb;1865(2):142-152. doi: 10.1016/j.bbapap.2016.11.008. Epub 2016 Nov 22.

PMID: 27884635

28. A Computational Model for Kinetic Studies of Cadherin Binding and Clustering.

Chen J, Newhall J, Xie ZR, Leckband D, Wu Y.

Biophys J. 2016 Oct 4;111(7):1507-1518. doi: 10.1016/j.bpj.2016.08.038.

29. Elucidating the Functional Roles of Spatial Organization in Cross-Membrane Signal Transduction by a Hybrid Simulation Method.

Chen J, Xie ZR, Wu Y.

J Comput Biol. 2016 Jul;23(7):566-84. doi: 10.1089/cmb.2015.0227. Epub 2016 Mar 30.

30. Multiscale Model for the Assembly Kinetics of Protein Complexes.

Xie ZR, Chen J, Wu Y.

J Phys Chem B. 2016 Feb 4;120(4):621-32. doi: 10.1021/acs.jpcb.5b08962. Epub 2016 Jan 20.

31. Elucidating the general principles of cell adhesion with a coarse-grained simulation model.

Chen J, Xie ZR, Wu Y.

Mol Biosyst. 2016 Jan;12(1):205-18. doi: 10.1039/c5mb00612k. Epub 2015 Nov 19.

32. Study of protein structural deformations under external mechanical perturbations by a coarse-grained simulation method.

Chen J, Xie ZR, Wu Y.

Biomech Model Mechanobiol. 2016 Apr;15(2):317-29. doi: 10.1007/s10237-015-0690-0. Epub 2015 Jun 7.

33. Decomposing the space of protein quaternary structures with the interface fragment pair library.

Xie ZR, Chen J, Zhao Y, Wu Y.

BMC Bioinformatics. 2015 Jan 16;16(1):14. doi: 10.1186/s12859-014-0437-4.

34. Linking 3D and 2D binding kinetics of membrane proteins by multiscale simulations.

Xie ZR, Chen J, Wu Y.

Protein Sci. 2014 Dec;23(12):1789-99. doi: 10.1002/pro.2574. Epub 2014 Oct 21.

35. Computational modeling of the interplay between cadherin-mediated cell adhesion and Wnt signaling pathway.

Chen J, Xie ZR, Wu Y.

PLoS One. 2014 Jun 26;9(6):e100702. doi: 10.1371/journal.pone.0100702. eCollection 2014.

36. A multiscale model for simulating binding kinetics of proteins with flexible linkers.

Chen J, Xie ZR, Wu Y.

Proteins. 2014 Oct;82(10):2512-22. doi: 10.1002/prot.24614. Epub 2014 Jun 9.

37. A coarse-grained model for the simulations of biomolecular interactions in cellular environments.

Xie ZR, Chen J, Wu Y.

J Chem Phys. 2014 Feb 7;140(5):054112. doi: 10.1063/1.4863992.

38. Theory and simulations of adhesion receptor dimerization on membrane surfaces.

Wu Y, Honig B, Ben-Shaul A.

Biophys J. 2013 Mar 19;104(6):1221-9. doi: 10.1016/j.bpj.2013.02.009. Epub 2013 Mar 19.

39. Transforming binding affinities from three dimensions to two with application to cadherin clustering.

Wu Y, Vendome J, Shapiro L, Ben-Shaul A, Honig B.

Nature. 2011 Jul 27;475(7357):510-3. doi: 10.1038/nature10183.

40. The extracellular architecture of adherens junctions revealed by crystal structures of type I cadherins.

Harrison OJ, Jin X, Hong S, Bahna F, Ahlsen G, Brasch J, Wu Y, Vendome J, Felsovalyi K, Hampton CM, Troyanovsky RB, Ben-Shaul A, Frank J, Troyanovsky SM, Shapiro L, Honig B.

Structure. 2011 Feb 9;19(2):244-56. doi: 10.1016/j.str.2010.11.016.

41. Cooperativity between trans and cis interactions in cadherin-mediated junction formation.

Wu Y, Jin X, Harrison O, Shapiro L, Honig BH, Ben-Shaul A.

Proc Natl Acad Sci U S A. 2010 Oct 12;107(41):17592-7. doi: 10.1073/pnas.1011247107. Epub 2010 Sep 27.