Rigid‐body motions of interacting proteins dominate multispecific binding of ubiquitin in a shape‐dependent manner

Abstract

To understand the dynamic aspects of multispecificity of ubiquitin, we studied nine ubiquitin-ligand (partner protein) complexes by normal mode analysis based on an elastic network model. The coupling between ubiquitin and ligand motions was analyzed by decomposing it into rigid-body (external) and vibrational (internal) motions of each subunit. We observed that in total the external motions in one of the subunits largely dominated the coupling. The combination of external motions of ubiquitin and the ligands showed general trends of rotations and translations. Moreover, we observed that the rotational motions of ubiquitin were correlated to the ligand orientations. We also identified ubiquitin atomic vibrations that differentiated the orientation of the ligand molecule. We observed that the extents of coupling were correlated to the shapes of the ligands, and this trend was more pronounced when the coupling involved vibrational motions of the ligand. In conclusion, an intricate interplay between internal and external motions of ubiquitin and the ligands help understand the dynamics of multispecificity, which is mostly guided by the shapes of the ligands and the complex.

cNMA: a framework of encounter complex-based normal mode analysis to model conformational changes in protein interactions

“…The Hessian matrix of in our cANM is constructed by deriving the second order partial derivatives of . The complex-derived Hessian matrix possesses a special structure of , also investigated similarly in ( Dasgupta et al , 2014 ). Specifically, [a matrix where m and n are the number of nodes of R(eceptor) and L(igand), respectively] has two diagonal submatrices ( ) and ( ) capturing the coupled intramolecular motions of R and L , respectively.…”

Specific Non-Local Interactions Are Not Necessary for Recovering Native Protein Dynamics

“…The source codes to perform NMA of CND were written in the R programming language [54] and that of ENM was written in C [12], [55]. In CND and ENM we set d cut to 5 Å.…”

Computational Ways to Enhance Protein Inhibitor Design

“…The Elastic Network Models (ENM) have proven themselves to be highly useful in representing the global motions for a wide variety of diverse protein structures (Bahar and Jernigan, 1997Bahar et al, 1997a,b,c;Demirel et al, 1998;Keskin et al, 1998Keskin et al, , 2000Keskin et al, , 2002aJernigan et al, 1999Jernigan et al, , 2000Jernigan et al, , 2008Atilgan et al, 2001;Bahar and Rader, 2005;Sen et al, 2006;Jernigan and Kloczkowski, 2007;Yang et al, 2007Yang et al, , 2008Yang et al, , 2009Zhu and Hummer, 2010;Bakan et al, 2011;Karaca and Bonvin, 2011;May and Brooks, 2011;Peng and Head-Gordon, 2011;Uyar et al, 2011;Wieninger et al, 2011;Zheng, 2011;Zheng and Auerbach, 2011;Zimmermann et al, 2011a,b;Duttmann et al, 2012;Gniewek et al, 2012;Isin et al, 2012;Martin et al, 2012;Ruvinsky et al, 2012;Globisch et al, 2013;Kim et al, 2013;Sanejouand, 2013;Dasgupta et al, 2014). Since they have proven to be so successful in capturing the most important motions of protein structures, it is reasonable to expect that they should also be able to estimate the conformational entropies of structures.…”