We provide a stand-alone software, the BioAFMviewer, which transforms biomolecular structures into the graphical representation corresponding to the outcome of atomic force microscopy (AFM) experiments. The AFM graphics is obtained by performing simulated scanning over the molecular structure encoded in the corresponding PDB file. A versatile molecular viewer integrates the visualization of PDB structures and control over their orientation, while synchronized simulated scanning with variable spatial resolution and tip-shape geometry produces the corresponding AFM graphics. We demonstrate the applicability of the BioAFMviewer by comparing simulated AFM graphics to high-speed AFM observations of proteins. The software can furthermore process molecular movies of conformational motions, e.g. those obtained from servers which model functional transitions within a protein, and produce the corresponding simulated AFM movie. The BioAFMviewer software provides the platform to employ the plethora of structural and dynamical data of proteins in order to help in the interpretation of biomolecular AFM experiments. Nowadays nanotechnology allows to observe single proteins at work. Under atomic force microscopy (AFM), e.g., their surface can be rapidly scanned and functional motions monitored, which is of great importance for applications in all fields of Life science. The analysis and interpretation of experimental results remains however challenging, because the resolution of obtained images or molecular movies is far from perfect. On the other side, high-resolution static structures of most proteins are known and their conformational dynamics can be computed in molecular simulations. This enormous amount of available data offers a great opportunity to better understand the outcome of resolution-limited scanning experiments. Our software provides the computational package towards this goal. The BioAFMviewer computationally emulates the scanning of any biomolecular structure to produce graphical images that mimic the outcome of AFM experiments. This makes the comparison of all available structural data and computational molecular movies to AFM results possible. We demonstrate that simulated AFM images are of great value to facilitate the interpretation of high-speed AFM observations. With its versatile interactive interface and rich functionality, the BioAFMviewer provides a convenient platform for the broad Bio-AFM community to better understand experiments.

Allosteric effects often underlie the activity of proteins, and elucidating generic design aspects and functional principles unique to allosteric phenomena represent a major challenge. Here an approach consisting of the in silico design of synthetic structures, which, as the principal element of allostery, encode dynamical long-range coupling among two sites, is presented. The structures are represented by elastic networks, similar to coarse-grained models of real proteins. A strategy of evolutionary optimization was implemented to iteratively improve allosteric coupling. In the designed structures, allosteric interactions were analyzed in terms of strain propagation, and simple pathways that emerged during evolution were identified as signatures through which long-range communication was established. Moreover, robustness of allosteric performance with respect to mutations was demonstrated. As it turned out, the designed prototype structures reveal dynamical properties resembling those found in real allosteric proteins. Hence, they may serve as toy models of complex allosteric systems, such as proteins. Application of the developed modeling scheme to the allosteric transition in the myosin V molecular motor was also demonstrated.

Atomic force microscopy (AFM) can visualize the dynamics of single biomolecules under near-physiological conditions. However, the scanning tip probes only the molecular surface with limited resolution, missing details required to fully deduce functional mechanisms from imaging alone. To overcome such drawbacks, we developed a computational framework to reconstruct 3D atomistic structures from AFM surface scans, employing simulation AFM and automatized fitting to experimental images. We provide applications to AFM images ranging from single molecular machines, protein filaments, to large-scale assemblies of 2D protein lattices, and demonstrate how the obtained full atomistic information advances the molecular understanding beyond the original topographic AFM image. We show that simulation AFM further allows for quantitative molecular feature assignment within measured AFM topographies. Implementation of the developed methods into the versatile interactive interface of the BioAFMviewer software, freely available at www.bioafmviewer.com, presents the opportunity for the broad Bio-AFM community to employ the enormous amount of existing structural and modeling data to facilitate the interpretation of resolution-limited AFM images.

Hepatitis C virus helicase is a molecular motor that splits duplex DNA while actively moving over it. An approximate coarse-grained dynamical description of this protein, including its interactions with DNA and ATP, is constructed. Using such a mechanical model, entire operation cycles of an important protein machine could be followed in structurally resolved dynamical simulations. Ratcheting inchworm translocation and spring-loaded DNA unwinding, suggested by experimental data, were reproduced. Thus, feasibility of coarse-grained simulations, bridging a gap between full molecular dynamics and reduced phenomenological theories of molecular motors, has been demonstrated.

Structural biology is currently undergoing a transformation into dynamic structural biology, which reveals the dynamic structure of proteins during their functional activity to better elucidate how they function. Among the various approaches in dynamic structural biology, high-speed atomic force microscopy (HS-AFM) is unique in the ability to film individual molecules in dynamic action, although only topographical information is acquirable. This review provides a guide to the use of HS-AFM for biomolecular imaging and showcases several examples, as well as providing information on up-to-date progress in HS-AFM technology. Finally, we discuss the future prospects of HS-AFM in the context of dynamic structural biology in the upcoming era.

Elastic networks have been used as simple models of proteins to study their slow structural dynamics. They consist of point-like particles connected by linear Hookean springs and hence are convenient for linear normal mode analysis around a given reference structure. Furthermore, dynamic simulations using these models can provide new insights. As the computational cost associated with these models is considerably lower compared to that of all-atom models, they are also convenient for comparative studies between multiple protein structures. In this review, we introduce examples of coarse-grained molecular dynamics studies using elastic network models and their derivatives, focusing on the nonlinear phenomena, and discuss their applicability to large-scale macromolecular assemblies.