Dynamic features of homodimer interfaces calculated by normal‐mode analysis

Tsuchiya, Yuko; Kinoshita, Kengo; Endo, Shigeru; Wako, Hiroshi

doi:10.1002/pro.2140

Cited by 4 publications

(5 citation statements)

References 34 publications

(57 reference statements)

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“…Moreover, when internal–internal, internal–external, and external–internal couplings were considered, a majority of the atom‐pairs showed positive correlation. This is in accordance with a recent study by Tsuchiya et al which showed that on average intersubunit contacts across homodimeric interfaces involved positive correlations 36. It is previously demonstrated that the in‐phase motions favor the formation of bound state 30.…”

Section: Resultssupporting

confidence: 93%

Counterbalance of ligand‐ and self‐coupled motions characterizes multispecificity of ubiquitin

2012

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Date hub proteins are a type of proteins that show multispecificity in a time-dependent manner. To understand dynamic aspects of such multispecificity we studied Ubiquitin as a typical example of a date hub protein. Here we analyzed 9 biologically relevant Ubiquitin-protein (ligand) heterodimer structures by using normal mode analysis based on an elastic network model. Our result showed that the self-coupled motion of Ubiquitin in the complex, rather than its ligandcoupled motion, is similar to the motion of Ubiquitin in the unbound condition. The ligand-coupled motions are correlated to the conformational change between the unbound and bound conditions of Ubiquitin. Moreover, ligand-coupled motions favor the formation of the bound states, due to its in-phase movements of the contacting atoms at the interface. The self-coupled motions at the interface indicated loss of conformational entropy due to binding. Therefore, such motions disfavor the formation of the bound state. We observed that the ligand-coupled motions are embedded in the motions of unbound Ubiquitin. In conclusion, multispecificity of Ubiquitin can be characterized by an intricate balance of the ligand-and self-coupled motions, both of which are embedded in the motions of the unbound form.

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Section: Resultssupporting

confidence: 93%

Counterbalance of ligand‐ and self‐coupled motions characterizes multispecificity of ubiquitin

2012

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“…The opposing motions between the external and internal motions were indicated for an interface between an enzyme protein and its inhibitor [5]. Then, it verified in dimers [39] and trimers [8]. In this study, they have been verified in other oligomers.…”

Section: Interface Residues Between Subunitssupporting

confidence: 53%

“…We examined one trimer, two tetramers, and one hexamer in this study. We had already studied the inter-subunit interface of dimers [39]. We were interested in oligomers with over two subunits because they were expected to have significantly different features from dimers.…”

Section: Discussionmentioning

confidence: 99%

Dynamic properties of oligomers that characterize low-frequency normal modes

Wako

Endo

2019

BIOPHYSICS

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Dynamics of oligomeric proteins (one trimer, two tetramers, and one hexamer) were studied by elastic network model-based normal mode analysis to characterize their large-scale concerted motions. First, the oligomer motions were simplified by considering rigid-body motions of individual subunits. The subunit motions were resolved into three components in a cylindrical coordinate system: radial, tangential, and axial ones. Single component is dominant in certain normal modes. However, more than one component is mixed in others. The subunits move symmetrically in certain normal modes and as a standing wave with several wave nodes in others. Secondly, special attention was paid to atoms on inter-subunit interfaces. Their displacement vectors were decomposed into intrasubunit deformative (internal) and rigid-body (external) motions in individual subunits. The fact that most of the cosines of the internal and external motion vectors were negative for the atoms on the inter-subunit interfaces, indicated their opposing movements. Finally, a structural network of residues defined for each normal mode was investigated; the network was constructed by connecting two residues in contact and moving coherently. The centrality measure "betweenness" of each residue was calculated for the networks. Several residues with significantly high betweenness were observed on the inter-subunit interfaces. The results indicate that these residues are responsible for oligomer dynamics. It was also observed that amino acid residues with significantly high betweenness were more conservative. This supports that the betweenness is an effective characteristic for identifying an important residue in protein dynamics.Key words: betweenness, degeneracy of normal modes, conservation of amino acid residues, protein structure network, cylindrical coordinate system Most proteins function in an oligomeric form [1]. An advantage of oligomers over monomers is that the oligomeric form permits proteins to initiate allostery and cooperativity in achieving their function. Studies on the dynamics of oligomers can provide key information that reveals the mechanism of the allostery and cooperativity. Molecular dynamics (MD) simulation and normal mode analysis (NMA) can be effective theoretical methods to address this problem [2-9]. Although they can generate a large amount of data regarding protein motions at the atomic level and the motions Dynamics of oligomeric proteins were studied by elastic network model-based normal mode analysis to characterize their large-scale concerted motions. (1) The rigid-body motions of individual subunits were characterized by the radial, tangential, and axial components in a cylindrical coordinate system. (2) The motions of atoms on the intersubunit interfaces were characterized by the opposing motions of intra-subunit deformation and rigid-body motion of the subunit. (3) A dynamic protein structure network was defined in each mode, and the centrality measure, betweenness, was calculated for each residue. The results indicate tha...

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“…For example, Liang et al [ 73 ] studied various states (active and autoinhibitory) of DNMT3A in dimeric and tetrameric assemblies to determine its intrinsic dynamics and showed how the central interface infers allosteric properties. Tsuchiya et al [ 74 ] used a protein representation based on the dihedral angle space and NMA [ 75 ] to study the interface dynamics in over 500 homodimers.…”

Section: Tools For Calculating Ppi Dynamicsmentioning

confidence: 99%

Modeling the Dynamics of Protein–Protein Interfaces, How and Why?

2022

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Protein–protein assemblies act as a key component in numerous cellular processes. Their accurate modeling at the atomic level remains a challenge for structural biology. To address this challenge, several docking and a handful of deep learning methodologies focus on modeling protein–protein interfaces. Although the outcome of these methods has been assessed using static reference structures, more and more data point to the fact that the interaction stability and specificity is encoded in the dynamics of these interfaces. Therefore, this dynamics information must be taken into account when modeling and assessing protein interactions at the atomistic scale. Expanding on this, our review initially focuses on the recent computational strategies aiming at investigating protein–protein interfaces in a dynamic fashion using enhanced sampling, multi-scale modeling, and experimental data integration. Then, we discuss how interface dynamics report on the function of protein assemblies in globular complexes, in fuzzy complexes containing intrinsically disordered proteins, as well as in active complexes, where chemical reactions take place across the protein–protein interface.

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Dynamic features of homodimer interfaces calculated by normal‐mode analysis

Cited by 4 publications

References 34 publications

Counterbalance of ligand‐ and self‐coupled motions characterizes multispecificity of ubiquitin

Counterbalance of ligand‐ and self‐coupled motions characterizes multispecificity of ubiquitin

Dynamic properties of oligomers that characterize low-frequency normal modes

Modeling the Dynamics of Protein–Protein Interfaces, How and Why?

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