Osamu Miyashita

Nonlinear elasticity, proteinquakes, and the energy landscapes of functional transitions in proteins

Large-scale motions of biomolecules involve linear elastic deformations along low-frequency normal modes, but for function nonlinearity is essential. In addition, unlike macroscopic machines, biological machines can locally break and then reassemble during function. We present a model for global structural transformations, such as allostery, that involve large-scale motion and possible partial unfolding, illustrating the method with the conformational transition of adenylate kinase. Structural deformation between open and closed states occurs via low-frequency modes on separate reactant and product surfaces, switching from one state to the other when energetically favorable. The switching model is the most straightforward anharmonic interpolation, which allows the barrier for a process to be estimated from a linear normal mode calculation, which by itself cannot be used for activated events. Local unfolding, or cracking, occurs in regions where the elastic stress becomes too high during the transition. Cracking leads to a counterintuitive catalytic effect of added denaturant on allosteric enzyme function. It also leads to unusual relationships between equilibrium constant and rate like those seen recently in single-molecule experiments of motor proteins.

Biased coarse-grained molecular dynamics simulation approach for flexible fitting of X-ray structure into cryo electron microscopy maps.

Several approaches have been introduced to interpret, in terms of high-resolution structure, low-resolution structural data as obtained from cryo-EM. As conformational changes are often observed in biological molecules, these techniques need to take into account the flexibility of proteins. Flexibility has been described in terms of movement between rigid domains and between rigid secondary structure elements, which present some limitations for studying dynamical properties. Normal mode analysis has also been used, but is limited to medium resolution data. All-atom molecular dynamics fitting techniques are more appropriate to fit structures into higher-resolution data as full protein flexibility is considered, but are cumbersome in terms of computational time. Here, we introduce a coarse-grained approach; a Go-model was used to represent biological molecules, combined with biased molecular dynamics to reproduce accurately conformational transitions. Illustrative examples on simulated data are shown. Accurate fittings can be obtained for resolution ranging from 5 to 20A. The approach was also tested on experimental data of Elongation Factor G and Escherichia coli RNA polymerase, where its validity is compared to previous models obtained from different techniques. This comparison demonstrates that quantitative flexible techniques, as opposed to manual docking, need to be considered to interpret low-resolution data.

Macromolecular structures probed by combining single-shot free-electron laser diffraction with synchrotron coherent X-ray imaging

Nanostructures formed from biological macromolecular complexes utilizing the self-assembly properties of smaller building blocks such as DNA and RNA hold promise for many applications, including sensing and drug delivery. New tools are required for their structural characterization. Intense, femtosecond X-ray pulses from X-ray free-electron lasers enable single-shot imaging allowing for instantaneous views of nanostructures at ambient temperatures. When combined judiciously with synchrotron X-rays of a complimentary nature, suitable for observing steady-state features, it is possible to perform ab initio structural investigation. Here we demonstrate a successful combination of femtosecond X-ray single-shot diffraction with an X-ray free-electron laser and coherent diffraction imaging with synchrotron X-rays to provide an insight into the nanostructure formation of a biological macromolecular complex: RNA interference microsponges. This newly introduced multimodal analysis with coherent X-rays can be applied to unveil nano-scale structural motifs from functional nanomaterials or biological nanocomplexes, without requiring a priori knowledge.

Crystal molecular dynamics simulations to speed up MM/PB(GB)SA evaluation of binding free energies of di-mannose deoxy analogs with P51G-m4-Cyanovirin-N

Complexes of two Cyanovirin‐N (CVN) mutants, m4‐CVN and P51G‐m4‐CVN, with deoxy di‐mannose analogs were employed as models to generate conformational ensembles using explicit water Molecular Dynamics (MD) simulations in solution and in crystal environment. The results were utilized for evaluation of binding free energies with the molecular mechanics Poisson‐Boltzmann (or Generalized Born) surface area, MM/PB(GB)SA, methods. The calculations provided the ranking of deoxy di‐mannose ligands affinity in agreement with available qualitative experimental evidences. This confirms the importance of the hydrogen‐bond network between di‐mannose 3′‐ and 4′‐hydroxyl groups and the protein binding site BM as a basis of the CVN activity as an effective HIV fusion inhibitor. Comparison of binding free energies averaged over snapshots from the solution and crystal simulations showed high promises in the use of the crystal matrix for acceleration of the conformational ensemble generation, the most time consuming step in MM/PB(GB)SA approach. Correlation between energy values based on solution versus crystal ensembles is 0.95 for both MM/PBSA and MM/GBSA methods.

Solution and Crystal Molecular Dynamics Simulation Study of m4-Cyanovirin-N Mutants Complexed with Di-Mannose

Cyanovirin-N (CVN) is a highly potent anti-HIV carbohydrate-binding agent that establishes its microbicide activity through interaction with mannose-rich glycoprotein gp120 on the virion surface. The m4-CVN and P51G-m4-CVN mutants represent simple models for studying the high-affinity binding site, B(M). A recently determined 1.35 A high-resolution structure of P51G-m4-CVN provided details on the di-mannose binding mechanism, and suggested that the Arg-76 and Glu-41 residues are critical components of high mannose specificity and affinity. We performed molecular-dynamics simulations in solution and a crystal environment to study the role of Arg-76. Network analysis and clustering were used to characterize the dynamics of Arg-76. The results of our explicit solvent solution and crystal simulations showed a significant correlation with conformations of Arg-76 proposed from x-ray crystallographic studies. However, the crystal simulation showed that the crystal environment strongly biases conformational sampling of the Arg-76 residue. The solution simulations demonstrated no conformational preferences for Arg-76, which would support its critical role as the residue that locks the ligand in the bound state. Instead, a comparative analysis of trajectories from >50 ns of simulation for two mutants revealed the existence of a very stable eight-hydrogen-bond network between the di-mannose ligand and predominantly main-chain atoms. This network may play a key role in the specific recognition and strong binding of mannose oligomers in CVN and its homologs.

Exploring biomolecular machines: energy landscape control of biological reactions

For almost 15 years, our Pathway model has been the most powerful model in terms of predicting the tunnelling mechanism for electron transfer (ET) in biological systems, particularly proteins. Going beyond the conventional Pathway models, we have generalized our method to understand how protein dynamics modulate not only the Franck–Condon factor, but also the tunnelling matrix element. We have demonstrated that when interference among pathways modulates the electron tunnelling interactions in proteins (particularly destructive interference), dynamical effects are of critical importance. Tunnelling can be controlled by protein conformations that lie far from equilibrium—those that minimize the effect of destructive interference during tunnelling, for example. In the opposite regime, electron tunnelling is mediated by one (or a few) constructively interfering pathway tubes and dynamical effects are modest. This new mechanism for dynamical modulation of the ET rate has been able to explain and/or predict several rates that were later confirmed by experiment. However, thermal fluctuations can also affect these molecular machines in many other ways. For example, we show how global transformations, which control protein functions such as allostery, may involve large-scale motion and possibly partial unfolding during the reaction event.

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.

Thermodynamic properties of water molecules in the presence of cosolute depend on DNA structure: a study using grid inhomogeneous solvation theory

In conditions that mimic those of the living cell, where various biomolecules and other components are present, DNA strands can adopt many structures in addition to the canonical B-form duplex. Previous studies in the presence of cosolutes that induce molecular crowding showed that thermal stabilities of DNA structures are associated with the properties of the water molecules around the DNAs. To understand how cosolutes, such as ethylene glycol, affect the thermal stability of DNA structures, we investigated the thermodynamic properties of water molecules around a hairpin duplex and a G-quadruplex using grid inhomogeneous solvation theory (GIST) with or without cosolutes. Our analysis indicated that (i) cosolutes increased the free energy of water molecules around DNA by disrupting water–water interactions, (ii) ethylene glycol more effectively disrupted water–water interactions around Watson–Crick base pairs than those around G-quartets or non-paired bases, (iii) due to the negative electrostatic potential there was a thicker hydration shell around G-quartets than around Watson–Crick-paired bases. Our findings suggest that the thermal stability of the hydration shell around DNAs is one factor that affects the thermal stabilities of DNA structures under the crowding conditions.

Analysis of the bacterial luciferase mobile loop by replica-exchange molecular dynamics.

Bacterial luciferase contains an extended 29-residue mobile loop. Movements of this loop are governed by binding of either flavin mononucleotide (FMNH2) or polyvalent anions. To understand this process, loop dynamics were investigated using replica-exchange molecular dynamics that yielded conformational ensembles in either the presence or absence of FMNH2. The resulting data were analyzed using clustering and network analysis. We observed the closed conformations that are visited only in the simulations with the ligand. Yet the mobile loop is intrinsically flexible, and FMNH2 binding modifies the relative populations of conformations. This model provides unique information regarding the function of a crystallographically disordered segment of the loop near the binding site. Structures at or near the fringe of this network were compatible with flavin binding or release. Finally, we demonstrate that the crystallographically observed conformation of the mobile loop bound to oxidized flavin was influenced by crystal packing. Thus, our study has revealed what we believe are novel conformations of the mobile loop and additional context for experimentally determined structures.

Flexible fitting to cryo-EM density map using ensemble molecular dynamics simulations

Flexible fitting is a computational algorithm to derive a new conformational model that conforms to low‐resolution experimental data by transforming a known structure. A common application is against data from cryo‐electron microscopy to obtain conformational models in new functional states. The conventional flexible fitting algorithms cannot derive correct structures in some cases due to the complexity of conformational transitions. In this study, we show the importance of conformational ensemble in the refinement process by performing multiple fittings trials using a variety of different force constants. Application to simulated maps of Ca2+ ATPase and diphtheria toxin as well as experimental data of release factor 2 revealed that for these systems, multiple conformations with similar agreement with the density map exist and a large number of fitting trials are necessary to generate good models. Clustering analysis can be an effective approach to avoid over‐fitting models. In addition, we show that an automatic adjustment of the biasing force constants during the fitting process, implemented as replica‐exchange scheme, can improve the success rate.