Terahertz vibration modes in Na/K-ATPase

Study on the Influence of UV Light on Selective Antibacterial Activity of Silver Nanoparticle Synthesized Utilizing Protein/Polypeptide-Rich Aqueous Extract from The Common Walkingstick, Diapheromera femorata

Common walkingstick (Diapheromera femorata) aqueous extract (CWSAE) can induce the synthesis of useful bionanomaterials. CWSAE is rich in water-soluble organic compounds such as proteins and polypeptides that function as reducing/stabilizing agents for nanoparticle formation from Ag+ ion precursors. The synthesized AgNPs exhibited a moderately uniform size, with the majority falling within the range of 20-80 nm. These AgNPs were UV-treated and tested as antibacterial agents to inhibit the growth of four pathogenic bacteria (Burkholderia cenocepacia K-56, Klebsiella pneumoniae ST258, Pseudomonas aeruginosa PAO1, and Staphylococcus aureus USA300), as well as one common bacterium (Escherichia coli BW25113). The disk diffusion test demonstrated that the UV-treated AgNPs significantly and selectively inhibited the growth of Staphylococcus aureus USA300 and P. aeruginosa, while showing a small effect on the other two species. This suggests the potential application of green-chemically synthesized AgNPs as selective antibacterial agents. Furthermore, we studied the effects of short-term (1-2 min) and long-term (5-30 min) UV treatment on the selective cytotoxicity of the AgNPs and found that the cytotoxicity of the AgNPs could depend on the duration of UV exposure against certain bacteria.

Selectivity of Protein Interactions Stimulated by Terahertz Signals

It has been established that Terahertz (THz) band signals can interact with biomolecules through resonant modes. Specifically, of interest here, protein activation. Our research goal is to show how directing the mechanical signaling inside protein molecules using THz signals can control changes in their structure and activate associated biochemical and biomechanical events. To establish that, we formulate a selectivity metric that quantifies the system performance and captures the capability of the nanoantenna to induce a conformational change in the desired protein molecule/population. The metric provides a score between -1 and 1 that indicates the degree of control we have over the system to achieve targeted protein interactions. To develop the selectivity measure, we first use the Langevin stochastic equation driven by an external force to model the protein behavior. We then determine the probability of protein folding by computing the steady-state energy of the driven protein and then generalize our model to account for protein populations. Our numerical analysis results indicate that a maximum selectivity score is attained when only the targeted population experiences a folding behavior due to the impinging THz signal. From the achieved selectivity values, we conclude that the system response not only depends on the resonant frequency but also on the system controlling parameters namely, the nanoantenna force, the damping constant, and the abundance of each protein population. Based on the selectivity metric, the nanoantenna must be tuned to a frequency that is not necessarily the resonant frequency of the protein. The presented work sheds light on the potential associated with the electromagnetic-based control of protein networks, which could lead to a plethora of applications in the medical field ranging from bio-sensing to targeted therapy.

Response of Terahertz Protein Vibrations to Ligand Binding: Calmodulin-Peptide Complexes as a Case Study

Terahertz vibrations are sensitive reporters of the structure and interactions of proteins. Ligand binding alters the nature and distribution of these collective vibrations. The ligand-induced changes in the terahertz protein vibrations contribute to the binding entropy and to the overall thermodynamic stability of the resultant protein-ligand complexes. Here, we have examined the response of the low-frequency (below 6 terahertz) collective vibrations of the calcium-loaded calmodulin (CaM) to binding to five different ligands, both in the presence and absence of water, using normal-mode analysis and molecular dynamics simulations. A comparison of the vibrational spectra of hydrated and dry systems reveals that protein-solvent interactions stiffen the terahertz protein vibrations and that these solvent-coupled collective vibrations contribute significantly to the hydration-sensitive variation in the vibrational entropy of CaM. In the absence of water, the low-frequency vibrations of CaM are stiffened by ligand binding. On the contrary, the number and the cumulative vibrational entropy of low-frequency vibrational modes (ω < 200 cm^-1) of the hydrated CaM are increased noticeably after binding to the peptides, indicating binding-induced softening of collective vibrations of the protein. Although the calculated and experimental binding affinities of the chosen complexes correlated reasonably well, no systematic correlation was observed between the protein vibrational entropy and the binding affinity. The results underscored the importance of the interplay of protein-ligand and solvent interactions in modulating the low-frequency vibrations of proteins.

hdANM: a new comprehensive dynamics model for protein hinges

Hinge motions are essential for many protein functions, and their dynamics are important to understand underlying biological mechanisms. The ways that these motions are represented by various computational methods differ significantly. By focusing on a specific class of motion, we have developed a new hinge-domain anisotropic network model (hdANM) that is based on the prior identification of flexible hinges and rigid domains in the protein structure and the subsequent generation of global hinge motions. This yields a set of motions in which the relative translations and rotations of the rigid domains are modulated and controlled by the deformation of the flexible hinges, leading to a more restricted, specific view of these motions. hdANM is the first model, to our knowledge, that combines information about protein hinges and domains to model the characteristic hinge motions of a protein. The motions predicted with this new elastic network model provide important conceptual advantages for understanding the underlying biological mechanisms. As a matter of fact, the generated hinge movements are found to resemble the expected mechanisms required for the biological functions of diverse proteins. Another advantage of this model is that the domain-level coarse graining makes it significantly more computationally efficient, enabling the generation of hinge motions within even the largest molecular assemblies, such as those from cryo-electron microscopy. hdANM is also comprehensive as it can perform in the same way as the well-known protein dynamics models (anisotropic network model, rotations-translations of blocks, and nonlinear rigid block normal mode analysis), depending on the definition of flexible and rigid parts in the protein structure and on whether the motions are extrapolated in a linear or nonlinear fashion. Furthermore, our results indicate that hdANM produces more realistic motions as compared to the anisotropic network model. hdANM is an open-source software, freely available, and hosted on a user-friendly website.

Low-Frequency Harmonic Perturbations Drive Protein Conformational Changes

Protein dynamics has been investigated since almost half a century, as it is believed to constitute the fundamental connection between structure and function. Elastic network models (ENMs) have been widely used to predict protein dynamics, flexibility and the biological mechanism, from which remarkable results have been found regarding the prediction of protein conformational changes. Starting from the knowledge of the reference structure only, these conformational changes have been usually predicted either by looking at the individual mode shapes of vibrations (i.e., by considering the free vibrations of the ENM) or by applying static perturbations to the protein network (i.e., by considering a linear response theory). In this paper, we put together the two previous approaches and evaluate the complete protein response under the application of dynamic perturbations. Harmonic forces with random directions are applied to the protein ENM, which are meant to simulate the single frequency-dependent components of the collisions of the surrounding particles, and the protein response is computed by solving the dynamic equations in the underdamped regime, where mass, viscous damping and elastic stiffness contributions are explicitly taken into account. The obtained motion is investigated both in the coordinate space and in the sub-space of principal components (PCs). The results show that the application of perturbations in the low-frequency range is able to drive the protein conformational change, leading to remarkably high values of direction similarity. Eventually, this suggests that protein conformational change might be triggered by external collisions and favored by the inherent low-frequency dynamics of the protein structure.

Modal Analysis of the Lysozyme Protein Considering All-Atom and Coarse-Grained Finite Element Models

Proteins are the fundamental entities of several organic activities. They are essential for a broad range of tasks in a way that their shapes and folding processes are crucial to achieving proper biological functions. Low-frequency modes, generally associated with collective movements at terahertz (THz) and sub-terahertz frequencies, have been appointed as critical for the conformational processes of many proteins. Dynamic simulations, such as molecular dynamics, are vastly applied by biochemical researchers in this field. However, in the last years, proposals that define the protein as a simplified elastic macrostructure have shown appealing results when dealing with this type of problem. In this context, modal analysis based on different modelization techniques, i.e., considering both an all-atom (AA) and coarse-grained (CG) representation, is proposed to analyze the hen egg-white lysozyme. This work presents new considerations and conclusions compared to previous analyses. Experimental values for the B-factor, considering all the heavy atoms or only one representative point per amino acid, are used to evaluate the validity of the numerical solutions. In general terms, this comparison allows the assessment of the regional flexibility of the protein. Besides, the low computational requirements make this approach a quick method to extract the protein’s dynamic properties under scrutiny.