Elastic Network Normal Mode Analysis Research Articles

A unique ligand-steered strategy for CC chemokine receptor 2 homology modeling to facilitate structure-based virtual screening.

CC chemokine receptor 2 (CCR2) antagonists that disrupt CCR2/MCP‐1 interaction are expected to treat a variety of inflammatory and autoimmune diseases. The lack of CCR2 crystal structure limits the application of structure‐based drug design (SBDD) to this target. Although a few three‐dimensional theoretical models have been reported, their accuracy remains to be improved in terms of templates and modeling approaches. In this study, we developed a unique ligand‐steered strategy for CCR2 homology modeling. It starts with an initial model based on the X‐ray structure of the closest homolog so far, that is, CXCR4. Then, it uses Elastic Network Normal Mode Analysis (EN‐NMA) and flexible docking (FD) by AutoDock Vina software to generate ligand‐induced fit models. It selects optimal model(s) as well as scoring function(s) via extensive evaluation of model performance based on a unique benchmarking set constructed by our in‐house tool, that is, MUBD‐DecoyMaker. The model of 81_04 presents the optimal enrichment when combined with the scoring function of PMF04, and the proposed binding mode between CCR2 and Teijin lead by this model complies with the reported mutagenesis data. To highlight the advantage of our strategy, we compared it with the only reported ligand‐steered strategy for CCR2 homology modeling, that is, Discovery Studio/Ligand Minimization. Lastly, we performed prospective virtual screening based on 81_04 and CCR2 antagonist bioassay. The identification of two hit compounds, that is, E859‐1281 and MolPort‐007‐767‐945, validated the efficacy of our model and the ligand‐steered strategy.

Flexibility within the Rotor and Stators of the Vacuolar H+-ATPase

The V-ATPase is a membrane-bound protein complex which pumps protons across the membrane to generate a large proton motive force through the coupling of an ATP-driven 3-stroke rotary motor (V1) to a multistroke proton pump (Vo). This is done with near 100% efficiency, which is achieved in part by flexibility within the central rotor axle and stator connections, allowing the system to flex to minimise the free energy loss of conformational changes during catalysis. We have used electron microscopy to reveal distinctive bending along the V-ATPase complex, leading to angular displacement of the V1 domain relative to the Vo domain to a maximum of ~30°. This has been complemented by elastic network normal mode analysis that shows both flexing and twisting with the compliance being located in the rotor axle, stator filaments, or both. This study provides direct evidence of flexibility within the V-ATPase and by implication in related rotary ATPases, a feature predicted to be important for regulation and their high energetic efficiencies.

Conformational Sampling of Maltose-Transporter Components in Cartesian Collective Variables Is Governed by the Low-Frequency Normal Modes

We have studied large-scale conformational transitions in the maltose-binding protein, and the nucleotide binding domains of a maltose-transporter using enhanced conformational sampling in Cartesian collective variables (CVs) with temperature-accelerated molecular dynamics (TAMD), and C(α)-based elastic network normal mode analysis. Significantly, every functional displacement in the TAMD-generated pathways of each protein could be rationalized via a single low-frequency soft mode, while a combination of 2 to 3 low-frequency modes were found to describe the entire conformational change suggesting that collective functional movement in TAMD trajectories is facilitated by the intrinsically accessible low-frequency normal modes. By applying a harmonic potential to facilitate functional motion in TAMD simulations, we also provide a recipe to reproducibly generate structural transitions in both proteins, which can be used to characterize large-scale conformational changes in other biomolecules.

Coarse-Grained Modeling of the Self-Association of Therapeutic Monoclonal Antibodies

Coarse-grained computational models of two therapeutic monoclonal antibodies are constructed to understand the effect of domain-level charge-charge electrostatics on the self-association phenomena at high protein concentrations. The coarse-grained representations of the individual antibodies are constructed using an elastic network normal-mode analysis. Two different models are constructed for each antibody for a compact Y-shaped and an extended Y-shaped configuration. The resulting simulations of these coarse-grained antibodies that interact through screened electrostatics are done at six different concentrations. It is observed that a particular monoclonal antibody (hereafter referred to as MAb1) forms three-dimensional heterogeneous structures with dense regions or clusters compared to a different monoclonal antibody (hereafter referred to as MAb2) that forms more homogeneous structures (no clusters). These structures, together with the potential mean force (PMF) and radial distribution functions (RDF) between pairs of coarse-grained regions on the MAbs, are qualitatively consistent with the experimental observation that MAb1 has a significantly higher viscosity compared to MAb2, especially at concentrations >50 mg/mL, even though the only difference between the MAbs lies with a few amino acids at the antigen-binding loops (CDRs). It is also observed that the structures in MAb1 are formed due to stronger Fab-Fab interactions in corroboration with experimental observations. Evidence is also shown that Fab-Fc interactions can be equally important in addition to Fab-Fab interactions. The coarse-grained representations are effective in picking up differences based on local charge distributions of domains and make predictions on the self-association characteristics of these protein solutions. This is the first computational study of its kind to show that there are differences in structures formed by two different monoclonal antibodies at high concentrations.

Structure modeling from small angle X-ray scattering data with elastic network normal mode analysis

Computational algorithms to construct structural models from SAXS experimental data are reviewed. SAXS data provides a wealth of information to study the structure and dynamics of biological molecules, however it does not provide atomic details of structures. Thus combining the low-resolution data with already known X-ray structure is a common approach to study conformational transitions of biological molecules. This review provides a survey of SAXS modeling approaches. In addition, we will discuss theoretical backgrounds and performance of our approach, in which elastic network normal mode analysis is used to predict reasonable conformational transitions from known X-ray structures, and find alternative conformations that are consistent with SAXS data.

Key Interactions in Integrin Ectodomain Responsible for Global Conformational Change Detected by Elastic Network Normal-Mode Analysis

Integrin, a membrane protein with a huge extracellular domain, participates in cell-cell and cell-extracellular-matrix interactions for metazoan. A group of integrins is known to perform a large-scale structural change when the protein is activated, but the activation mechanism and generality of the conformational change remain to be elucidated. We performed normal-mode analysis of the elastic network model on integrin αVβ3 ectodomain in the bent form and identified key residues that influenced molecular motions. Iterative normal-mode calculations demonstrated that the specific nonbonded interactions involving the key residues work as a snap to keep integrin in the bent form. The importance of the key residues for the conformational change was further verified by mutation experiments, in which integrin αIIbβ3 was used. The conservation pattern of amino acid residues among the integrin family showed that the characteristic pattern of residues seen around these key residues is found in the limited groups of integrin β-chains. This conservation pattern suggests that the molecular mechanism of the conformational change relying on the interactions found in integrin αVβ3 is unique to the limited types of integrins.

1P-018 エラスティックネットワークモデルの基準振動解析と電子顕微鏡構造へのあてはめ手法によるリボソームの構造解析(蛋白質・構造(1),第46回日本生物物理学会年会)

1P-018 エラスティックネットワークモデルの基準振動解析と電子顕微鏡構造へのあてはめ手法によるリボソームの構造解析(蛋白質・構造(1),第46回日本生物物理学会年会)

An NMA‐guided path planning approach for computing large‐amplitude conformational changes in proteins

This paper presents a new method for computing macromolecular motions based on the combination of path planning algorithms, originating from robotics research, and elastic network normal mode analysis. The low-frequency normal modes are regarded as the collective degrees of freedom of the molecule. Geometric path planning algorithms are used to explore these collective degrees of freedom in order to find possible large-amplitude conformational changes. To overcome the limits of the harmonic approximation, which is valid in the vicinity of the minimum energy structure, and to get larger conformational changes, normal mode calculations are iterated during the exploration. Initial results show the efficiency of our method, which requires a small number of normal mode calculations to compute large-amplitude conformational transitions in proteins. A detailed analysis is presented for the computed transition between the open and closed structures of adenylate kinase. This transition, important for its biological function, involves large-amplitude domain motions. The obtained motion correlates well with results presented in related works.

Reply to ‘Comment on elastic network models and proteins’

The Gaussian network model (GNM) is based on the underlying assumption of isotropic and Gaussian fluctuations of residues controlled by inter-residue contact topology, similar to the statistical theory of junction fluctuations developed by Flory and coworkers for polymer networks. We clarify here these underlying assumptions and emphasize the fact that the GNM predictions (e.g. mean-square fluctuations, cross-correlations and global mode shapes) are rotationally invariant and more accurate than their counterparts predicted by elastic network normal mode analysis.

Exploring Mechanical, Physical and Chemical Aspects of Virus Swelling and Assembly Using Elastic Network Normal Mode Analysis

The construction of physical models for virus capsids that utilize the simple elastic network description for strain induced by local structural distortions is reviewed. Following, a brief overview of normal mode methods and computational schemes that yield information regarding the dynamics of viral capsids and their response to structural perturbations is given. Finally, these approaches will be illustrated via applications to the swelling of several viruses, with attention focused on the similarities and differences in the pathways of conformational distortions that arise for capsids with different quasi-symmetry T numbers. Examples to be discussed include a T 1⁄4 3 virus (CCMV), a capsid displaying T 1⁄4 4 quasi-symmetry (NwV) and a T 1⁄4 7 capsid (HK97).

The Requirement for Mechanical Coupling Between Head and S2 Domains in Smooth Muscle Myosin ATPase Regulation and its Implications for Dimeric Motor Function

A combination of experimental structural data, homology modelling and elastic network normal mode analysis is used to explore how coupled motions between the two myosin heads and the dimerization domain (S2) in smooth muscle myosin II determine the domain movements required to achieve the inhibited state of this ATP-dependent molecular motor. These physical models rationalize the empirical requirement for at least two heptads of non-coiled alpha-helix at the junction between the myosin heads and S2, and the dependence of regulation on S2 length. The results correlate well with biochemical data regarding altered conformational-dependent solubility and stability. Structural models of the conformational transition between putative active states and the inhibited state show that torsional flexibility of the S2 alpha-helices is a key mechanical requirement for myosin II regulation. These torsional motions of the myosin heads about their coiled coil alpha-helices affect the S2 domain structure, which reciprocally affects the motions of the myosin heads. This inter-relationship may explain a large body of data on function of molecular motors that form dimers through a coiled-coil domain.

Diversity and Identity of Mechanical Properties of Icosahedral Viral Capsids Studied with Elastic Network Normal Mode Analysis

We analyze the mechanical properties and putative dynamical fluctuations of a variety of viral capsids comprising different sizes and quasi-equivalent symmetries by performing normal mode analysis using the elastic network model. The expansion of the capsid to a swollen state is studied using normal modes and is compared with the experimentally observed conformational change for three of the viruses for which experimental data exist. We show that a combination of one or two normal modes captures remarkably well the overall translation that dominates the motion between the two conformational states, and reproduces the overall conformational change. We observe for all of the viral capsids that the nature of the modes is different. In particular for the T=7 virus, HK97, for which the shape of the capsid changes from spherical to faceted polyhedra, two modes are necessary to accomplish the conformational transition. In addition, we extend our study to viral capsids with other T numbers, and discuss the similarities and differences in the features of virus capsid conformational dynamics. We note that the pentamers generally have higher flexibility and propensity to move freely from the other capsomers, which facilitates the shape adaptation that may be important in the viral life cycle.

Flexible Multi-scale Fitting of Atomic Structures into Low-resolution Electron Density Maps with Elastic Network Normal Mode Analysis

A novel method is presented for the quantitative flexible docking of high-resolution structure into low-resolution maps of macromolecular complexes from electron microscopy. This method uses a linear combination of low-frequency normal modes from elastic network description of the molecular framework in an iterative manner to deform the structure optimally to conform to the low-resolution electron density map. The methodology utilizes gradient following techniques in collective normal modes to locally optimize the overall correlation coefficient between computed and measured electron density. To evaluate the performance of our approach, several proteins, which undergo large conformational changes, have been studied. We demonstrate that refinement based on normal mode analysis provides an accurate and fast alternative for the flexible fitting of high-resolution structure into a low-resolution density map. Additionally, we show that lower resolution (multi-scale) structural models can be used for the normal mode searching in lieu of fully atomic models with little loss of overall accuracy.

Dynamic reorganization of the functionally active ribosome explored by normal mode analysis and cryo-electron microscopy.

Combining structural data for the ribosome from x-ray crystallography and cryo-electron microscopy with dynamic models based on elastic network normal mode analysis, an atomically detailed picture of functionally important structural rearrangements that occur during translocation is elucidated. The dynamic model provides a near-atomic description of the ratchet-like rearrangement of the 70S ribosome seen in cryo-electron microscopy, and permits the identification of bridging interactions that either facilitate the conformational switching or maintain structural integrity of the 50S/30S interface. Motions of the tRNAs residing in the A and P sites also suggest the early stages of tRNA translocation as a result of this ratchet-like movement. Displacement of the L1 stalk, alternately closing and opening the intersubunit space near the E site, is observed in the dynamic model, in line with growing experimental evidence for the role of this structural component in facilitating the exiting of tRNA. Finally, a hinge-like transition in the 30S ribosomal subunit, similar to that observed in crystal structures of this complex, is also manifest as a dynamic mode of the ribosome. The coincidence of these dynamic transitions with the individual normal modes of the ribosome and the good correspondence between these motions and those observed in experiment suggest an underlying principle of nature to exploit the shape of molecular assemblies such as the ribosome to provide robustness to functionally important motions.