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The centrosome, a non-membranous organelle, constrains various soluble molecules locally to execute its functions. As the centrosome is surrounded by various dense components, we hypothesized that the centrosome may be bordered by a putative diffusion barrier. After quantitatively measuring the trapping kinetics of soluble proteins of varying size at centrosomes by a chemically inducible diffusion trapping assay, we found that centrosomes were highly accessible to soluble molecules with a Stokes radius of ≤ 5.1 nm, whereas larger molecules rarely reach centrosomes, indicating the existence of a size-dependent diffusion barrier at centrosomes. The permeability of barriers was tightly regulated by branched actin filaments outside of centrosomes. Such barrier gated the microtubule nucleation. We propose that actin filaments spatiotemporally constrain the distribution of molecules at centrosomes in a size-dependent manner.Significance StatementCentrosome maintains its microenvironment without membrane. Whether the dense protein complexes outside centrosomes including pericentriolar matrix, microtubules, and branched actin filaments provide physical obstruction is unclear yet. We here established a series of new tools for quantitative evaluation of the diffusion rates of varisized soluble proteins in different sub-compartments of centrosomes. Our results demonstrated that branched actin filaments, but not pericentriolar matrix or microtubules, around centrosome have acted as a size-dependent diffusion barrier and physically constrain centrosome microtubule nucleation.

Structure-encoded conformational dynamics are crucial for biomolecular functions. However, there is insufficient evidence to support the notion that dynamics play a role in guiding protein-nucleic acid interactions. Here, we show that protein-DNA docking orientation is a function of protein intrinsic dynamics, but the binding site itself does not display unique patterns in the examined spectrum of motions. This revelation is made possible by a novel technique that locates "dynamics interfaces" in proteins across which protein parts are anticorrelated in their slowest dynamics. A striking statistic is that such interfaces intersect the DNA in 97% of the 104 examined cases. These findings were then used to screen decoys generated by rigid-body docking of DNA molecules onto DNA-binding proteins. Using our method, the chance to discern near-native poses from non-native decoys increased by 2.5- and 1.6-fold, as compared to a random guess and methods based on surface complementarity, respectively. Hence, dynamically allowed protein-DNA docking orientations can work as new filters to cull and rerank docking poses and therefore enhance the predictability of DNA-binding sites that themselves do not have distinct dynamics features. Computer software implementing the method can be accessed via http://dyn.life.nthu.edu.tw/IDD/DNA.htm .

It has been an established idea in recent years that protein is a physiochemically connected network. Allostery, understood in this new context, is a manifestation of residue communicating between remote sites in this network, and hence a rising interest to identify functionally relevant communication pathways and the frequent communicators within. Previous studies rationalized the coupling between functional sites and experimentally observed allosteric sites by theoretically discovered high positional/velocity/thermal correlations between these sites. However, for one to systematically discover previously unobserved allosteric sites in any receptor/enzyme providing the position of functional (orthosteric) sites, these high correlations may not be able to identify remote allosteric sites because of a number of false-positives while many of those are located in proximity to the functional site. Also, whether allosteric sites should be found in equilibrium or non-equilibrium state of a protein to be more biologically relevant is not clear, neither is the directionality preference of aforementioned propagating signals. In this study, we devised a time-dependent linear response theory (td-LRT) integrating intrinsic protein dynamics and perturbation forces that excite protein’s temporary reconfiguration at the non-equilibrium state, to describe atom-specific time responses as the propagating mechanical signals and discover that the most frequent remote communicators can be important allosteric sites, mutation of which would deteriorate the hydride transfer rate in DHFR by 2 to 3 orders. The preferred directionality of the signal propagation can be inferred from the asymmetric connection matrix (CM), where the coupling strength between a pair of residues is suggested by their communication score (CS) in the CM, which is found consistent with experimentally characterized nonadditivity of double mutants. Also, the intramolecular communication centers (ICCs), having high CSs, are found evolutionarily conserved, suggesting their biological importance.

Human S100A9 (Calgranulin B) is a Ca(2+)-binding protein, from the S100 family, that often presents as a homodimer in myeloid cells. It becomes an important mediator during inflammation once calcium binds to its EF-hand motifs. Human RAGE protein (receptor for advanced glycation end products) is one of the target-proteins. RAGE binds to a hydrophobic surface on S100A9. Interactions between these proteins trigger signal transduction cascades, promoting cell growth, proliferation, and tumorigenesis. Here, we present the solution structure of mutant S100A9 (C3S) homodimer, determined by multi-dimensional NMR experiments. We further characterize the solution interactions between mS100A9 and the RAGE V domain via NMR spectroscopy. CHAPS is a zwitterionic and non-denaturing molecule widely used for protein solubilizing and stabilization. We found out that CHAPS and RAGE V domain would interact with mS100A9 by using (1)H-(15)N HSQC NMR titrations. Therefore, using the HADDOCK program, we superimpose two binary complex models mS100A9-RAGE V domain and mS100A9-CHAPS and demonstrate that CHAPS molecules could play a crucial role in blocking the interaction between mS100A9 and the RAGE V domain. WST-1 assay results also support the conclusion that CHAPS inhibits the bioactivity of mS100A9. This report will help to inform new drug development against cell proliferation.

With advances in structure genomics, it is now recognized that knowledge of structure alone is insufficient to understand and control the mechanisms of biomolecular function. Additional information in the form of dynamics is needed. As demonstrated in a large number of studies, the machinery of proteins and their complexes can be understood to a good approximation by adopting Gaussian (or elastic) network models (GNM) for simplified normal mode analyses. While this approximation lacks chemical details, it provides us with a means for assessing the collective motions of large structures/assemblies and perform a comparative analysis of a series of proteins, thus providing insights into the mechanical aspects of biomolecular dynamics. In this paper, we discuss recent applications of GNM to a series of enzymes as well as large structures such as the HK97 bacteriophage viral capsids. Understanding the dynamics of large protein structures can be computationally challenging. To this end, we introduce a new approach for building a hierarchical, reduced rank representation of the protein topology and consequently the fluctuation dynamics.

Octaprenyl pyrophosphate synthase (OPPs) catalyzes the sequential condensation of five molecules of isopentenyl pyrophosphate with farnesyl pyrophosphate to generate all- trans C 40 -octaprenyl pyrophosphate, which constitutes the side chain of ubiquinone. Due to the slow product release, a long-chain polyprenyl pyrophosphate synthase often requires detergent or another factor for optimal activity. Our previous studies in examining the activity enhancement of Escherichia coli undecaprenyl pyrophosphate synthase have demonstrated a switch of the rate-determining step from product release to isopentenyl pyrophosphate (IPP) condensation reaction in the presence of Triton [12]. In order to understand the mechanism of enzyme activation for E. coli OPPs, a single-turnover reaction was performed and the measured IPP condensation rate (2 s −1 ) was 100 times larger than the steady-state rate (0.02 s −1 ). The high molecular weight fractions and Triton could accelerate the steady-state rate by 3-fold (0.06 s −1 ) but insufficient to cause full activation (100-fold). A burst product formation was observed in enzyme multiple turnovers indicating a slow product release.

In this study, a general linear response theory (LRT) is formulated to describe time-dependent and -independent protein conformational changes upon CO binding with myoglobin. Using the theory, we are able to monitor protein relaxation in two stages. The slower relaxation is found to occur from 4.4 to 81.2 picoseconds and the time constants characterized for a couple of aromatic residues agree with those observed by UV Resonance Raman (UVRR) spectrometry and time resolved x-ray crystallography. The faster “early responses”, triggered as early as 400 femtoseconds, can be best described by the theory when impulse forces are used. The newly formulated theory describes the mechanical propagation following ligand-binding as a function of time, space and types of the perturbation forces. The “disseminators”, defined as the residues that propagate signals throughout the molecule the fastest among all the residues in protein when perturbed, are found evolutionarily conserved and the mutations of which have been shown to largely change the CO rebinding kinetics in myoglobin.

S100B is a calcium sensing protein belonging to the S100 protein family with intracellular and extracellular roles. It is one of the EF hand homodimeric proteins, which is known to interact with various protein targets to regulate varied biological functions. Extracellular S100B has been recently reported to interact with FGF2 in a RAGE-independent manner. However, the recognition mechanism of S100B-FGF2 interaction at the molecular level remains unclear. In this study, the critical residues on S100B-FGF2 interface were mapped by combined information derived from NMR spectroscopy and site directed mutagenesis experiments. Utilizing NMR titration data, we generated the structural models of S100B-FGF2 complex from the computational docking program, HADDOCK which were further proved stable during 15ns unrestrained molecular dynamics (MD) simulations. Isothermal titration calorimetry studies indicated S100B interaction with FGF2 is an entropically favored process implying dominant role of hydrophobic contacts at the protein-protein interface. Residue level information of S100B interaction with FGF2 was useful to understand the varied target recognition ability of S100B and further explained its role in effecting extracellular signaling diversity. Mechanistic insights into the S100B-FGF2 complex interface and cell-based assay studies involving mutants led us to conclude the novel role of S100B in FGF2 mediated FGFR1 receptor inactivation.

In this study, I present a new elastic network model, to our knowledge, that addresses insufficiencies of two conventional models—the Gaussian network model (GNM) and the anisotropic network model (ANM). It has been shown previously that the GNM is not rotation-invariant due to its energy, which penalizes rigid-body rotation (external rotation). As a result, GNM models are found contaminated with rigid-body rotation, especially in the most collective ones. A new model (EPIRM) is proposed to remove such external component in modes. The extracted internal motions result from a potential that penalizes interresidue stretching and rotation in a protein. The new model is shown to pertinently describe crystallographic temperature factors (B-factors) and protein open↔closed transitions. Also, the capability of separating internal and external motions in GNM slow modes permits reexamining important mechanochemical properties in enzyme active sites. The results suggest that catalytic residues stay closer to rigid-body rotation axes than their immediate backbone neighbors. I show that the cumulative density of states for EPIRM and ANM follow different power laws as functions of low-mode frequencies. When using a cutoff distance of 7.5 Å, The cumulative density of states of EPIRM scales faster than that of all-atom normal mode analysis and slower than that of simple lattices.

Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold.

Atoms in proteins, viewed as interlinked hubs, communicate with each other in complying with governed physical forces. The deviations of their positions from the mean, known as fluctuations, are essential in mediating functionally relevant biological processes maintaining one's daily life. The coupled fluctuations between pairs of atoms, the fluctuation covariance, can be determined analytically by Normal Mode Analysis, or numerically by MD simulations. Our study considers how this network of atoms reacts in response to external perturbations. Effects of such perturbations are exemplified by ligand- or (another) protein-induced conformational changes as well as the appreciated structural distortion of crystalline structures from its solution conformers. We assume the response of the system has linear departure from the mean under small perturbations on the Hamiltonian at equilibrium state. The formulated linear response theories, either time-dependent or -independent [1], says that the positional change of a given atom i is the accumulative sum of fluctuation covariance ij, at unperturbed state, multiplied by the force exerted on atom j. The time-dependent response function determined from MD simulation of carbonmonoxy myoglobin is used to track time-dependent conformational changes upon photo-dissociation of CO. The consequently obtained understanding of perturbation propagation is compared with experimental results. Also, the structural distortion of X-ray-characterized ubiquitin from its solution conformer can be well explained by the induce-fit theory, in a wider sense, while population-shift does not account for such a deviation.[1] Ikeguchi M, Ueno J, Sato M, and Kidera A. (2005) Phys Rev Lett, 94, 078102.

The dnaX gene in Escherichia coli encodes comparable amounts of τ and γ subunits of DNA polymerase III by programmed ribosomal frameshifting (PRF). An early termination codon in the −1 frame of dnaX produces the γ subunit, which is a truncated form of the τ subunit. PRF is also involved in protein expression in many viruses, such as the Gag-Pol polyprotein in HIV. Thus, PRF provides an intrinsic regulating pathway at the translation level from the same mRNA.In the dnaX mRNA, an upstream internal Shine-Dalgarno (SD) sequence, which lies within the open reading frame and forms base-pairing with the 3’-end of 16S rRNA, together with a downstream stem-loop structure promote PRF on the slippery site. However, the detailed mechanisms for ribosome stalling and backtracking during PRF remain to be elucidated. Here, we combine coarse-grained elastic network model (ENM) and linear response theory to model the intrinsic and perturbed dynamics of the ribosome; the latter results from the formation of SD-helix and the forces exerted by stem-loop hindrance during translation. We hypothesize that these opposing forces for ribosome progression, albeit from different RNA elements, induce similar conformational changes for the ribosome, possibly in an allosteric fashion. These changes in the ribosome are expected to promote the observed PRF efficiency. Ultimately, we wish to provide the mechanochemical bases of PRF through computational modelling and validations by single-molecule force measurements.

Current study suggests that there exists an entropic restraint on protein-protein docking orientations. A physics-based, parameter-free approach has been developed to define intrinsic dynamic domains (IDDs) of proteins. Equilibrium dynamics of unbound protein pairs in 8 ‘difficult cases’ are sampled by Gaussian Network Model (GNM) and dimension-reduced Elastic Network Model (dr-ENM). IDDs are defined for proteins in accord with the slowest motions projected onto reduced dimensions. Domain planes and axes are thereby determined using Linear Discriminant Analysis (LDA) and principal components (PCs) of the position covariance of the unbound partners. The unbound partners are then best-fitted onto themselves in the complexes and the relative orientations of domain axes/planes of the paired proteins are examined. Our results show that proteins dock into each other with clear dynamic preferences in their orientations such that the binding planes of proteins cut through their docking partners, and also the bending axes of the docking pairs tend to be perpendicular to each other, implying proteins in the complexes are dynamically silent in the direction of their docking pairs’ vibrant movement. The dynamics-imposed restraints on protein docking orientations/locations shed light on entropic demands for proteins forming into complexes.

SummaryGrowing evidence supports the view that enzymatic activity results from a subtle interplay between chemical kinetics and molecular motions. A systematic analysis is performed here to delineate the type and level of coupling between catalysis and conformational mechanics. The dynamics of a set of 98 enzymes representative of different EC classes are analyzed with the Gaussian network model (GNM) and compared with experimental data. In more than 70% of the examined enzymes, the global hinge centers predicted by the GNM are found to be colocalized with the catalytic sites experimentally identified. Low translational mobility (