Motion Of Biomolecules Research Articles

Molecular dynamics simulation of the Brownian motion of biomolecules in liquid phase electron microscopy

Molecular dynamics simulation of the Brownian motion of biomolecules in liquid phase electron microscopy

Simulation-based inference for non-parametric statistical comparison of biomolecule dynamics.

Numerous models have been developed to account for the complex properties of the random walks of biomolecules. However, when analysing experimental data, conditions are rarely met to ensure model identification. The dynamics may simultaneously be influenced by spatial and temporal heterogeneities of the environment, out-of-equilibrium fluxes and conformal changes of the tracked molecules. Recorded trajectories are often too short to reliably discern such multi-scale dynamics, which precludes unambiguous assessment of the type of random walk and its parameters. Furthermore, the motion of biomolecules may not be well described by a single, canonical random walk model. Here, we develop a two-step statistical testing scheme for comparing biomolecule dynamics observed in different experimental conditions without having to identify or make strong prior assumptions about the model generating the recorded random walks. We first train a graph neural network to perform simulation-based inference and thus learn a rich summary statistics vector describing individual trajectories. We then compare trajectories obtained in different biological conditions using a non-parametric maximum mean discrepancy (MMD) statistical test on their so-obtained summary statistics. This procedure allows us to characterise sets of random walks regardless of their generating models, without resorting to model-specific physical quantities or estimators. We first validate the relevance of our approach on numerically simulated trajectories. This demonstrates both the statistical power of the MMD test and the descriptive power of the learnt summary statistics compared to estimates of physical quantities. We then illustrate the ability of our framework to detect changes in α-synuclein dynamics at synapses in cultured cortical neurons, in response to membrane depolarisation, and show that detected differences are largely driven by increased protein mobility in the depolarised state, in agreement with previous findings. The method provides a means of interpreting the differences it detects in terms of single trajectory characteristics. Finally, we emphasise the interest of performing various comparisons to probe the heterogeneity of experimentally acquired datasets at different levels of granularity (e.g., biological replicates, fields of view, and organelles).

SpecDB: A relational database for archiving biomolecular NMR spectral data

NMR is a valuable experimental tool in the structural biologist’s toolkit to elucidate the structures, functions, and motions of biomolecules. The progress of machine learning, particularly in structural biology, reveals the critical importance of large, diverse, and reliable datasets in developing new methods and understanding in structural biology and science more broadly. Biomolecular NMR research groups produce large amounts of data, and there is renewed interest in organizing these data to train new, sophisticated machine learning architectures and to improve biomolecular NMR analysis pipelines. The foundational data type in NMR is the free-induction decay (FID). There are opportunities to build sophisticated machine learning methods to tackle long-standing problems in NMR data processing, resonance assignment, dynamics analysis, and structure determination using NMR FIDs. Our goal in this study is to provide a lightweight, broadly available tool for archiving FID data as it is generated at the spectrometer, and grow a new resource of FID data and associated metadata. This study presents a relational schema for storing and organizing the metadata items that describe an NMR sample and FID data, which we call Spectral Database (SpecDB). SpecDB is implemented in SQLite and includes a Python software library providing a command-line application to create, organize, query, backup, share, and maintain the database. This set of software tools and database schema allow users to store, organize, share, and learn from NMR time domain data. SpecDB is freely available under an open source license at https://github.rpi.edu/RPIBioinformatics/SpecDB.

Diffracted X-ray Tracking Method for Measuring Intramolecular Dynamics of Membrane Proteins.

Membrane proteins change their conformations in response to chemical and physical stimuli and transmit extracellular signals inside cells. Several approaches have been developed for solving the structures of proteins. However, few techniques can monitor real-time protein dynamics. The diffracted X-ray tracking method (DXT) is an X-ray-based single-molecule technique that monitors the internal motion of biomolecules in an aqueous solution. DXT analyzes trajectories of Laue spots generated from the attached gold nanocrystals with a two-dimensional axis by tilting (θ) and twisting (χ). Furthermore, high-intensity X-rays from synchrotron radiation facilities enable measurements with microsecond-timescale and picometer-spatial-scale intramolecular information. The technique has been applied to various membrane proteins due to its superior spatiotemporal resolution. In this review, we introduce basic principles of DXT, reviewing its recent and extended applications to membrane proteins and living cells, respectively.

Conformational Dynamics of Intrinsically Disordered Proteins Regulate Biomolecular Condensate Chemistry.

Motions in biomolecules are critical for biochemical reactions. In cells, many biochemical reactions are executed inside of biomolecular condensates formed by ultradynamic intrinsically disordered proteins. A deep understanding of the conformational dynamics of intrinsically disordered proteins in biomolecular condensates is therefore of utmost importance but is complicated by diverse obstacles. Here we review emerging data on the motions of intrinsically disordered proteins inside of liquidlike condensates. We discuss how liquid–liquid phase separation modulates internal motions across a wide range of time and length scales. We further highlight the importance of intermolecular interactions that not only drive liquid–liquid phase separation but appear as key determinants for changes in biomolecular motions and the aging of condensates in human diseases. The review provides a framework for future studies to reveal the conformational dynamics of intrinsically disordered proteins in the regulation of biomolecular condensate chemistry.

Remotely controllable supramolecular rotor mounted inside a porphyrinic cage

Remotely controllable supramolecular rotor mounted inside a porphyrinic cage

Role of ergodicity, aging, and Gaussianity in resolving the origins of biomolecule subdiffusion.

The internal motions of biomolecules are essential to their function. Although biological macromolecules conventionally show subdiffusive dynamics, only recently has subdiffusion been associated with non-ergodicity. These findings have stimulated new questions in biophysics and statistical mechanics. Is non-ergodic subdiffusion a general strategy shared by biomolecules? What underlying mechanisms are responsible for it? Here, we performed extensive molecular dynamics (MD) simulations to characterize the internal dynamics of six different biomolecules, ranging from single or double-stranded DNA, a single domain protein (KRAS), two globular proteins (PGK and SHP2), to an intrinsically disordered protein (SNAP-25). We found that the subdiffusive behavior of these biomolecules falls into two classes. The internal motion of the first three cases is ergodic subdiffusion and can be interpreted by fractional Brownian motion (FBM), while the latter three cases involve non-ergodic subdiffusion and can be modeled by mixed origins of continuous-time random walk (CTRW) and FBM.

Interpolation Methods Applied on Biomolecules and Condensed Matter Brownian Motion

Biophysical and condensed matter systems connection is of great importance nowadays due to the need for a new approach in microelectronic biodevices, biocomputers or biochips advanced development. Considering that the living and nonliving systems’ submicroparticles are identical, we can establish the biunivocally correspondent relation between these two particle systems, as a biomimetic correlation based on Brownian motion fractal nature similarities, as the integrative property. In our research, we used the experimental results of bacterial motion under the influence of energetic impulses, like music, and also some biomolecule motion data. Our goal is to define the relation between biophysical and physical particle systems, by introducing mathematical analytical forms and applying Brownian motion fractal nature characterization and fractal interpolation. This work is an advanced research in the field of new solutions for high-level microelectronic integrations, which include submicrobiosystems like part of even organic microelectronic considerations, together with some physical systems of particles in solid-state solutions as a nonorganic part. Our research is based on Brownian motion minimal joint properties within the integrated biophysical systems in the wholeness of nature.

Probing the Viscosity of Aqueous Solutions Containing Ribosome-Bound Nascent Proteins

Understanding protein folding and metabolism within cells requires a fair evaluation of the complex solution conditions of the intracellular milieu. Viscosity is one important cellular property that affects the rotational and translational motion of biomolecules. Previous studies yielded information on the viscosity of a variety of aqueous solutions of protein, DNA, and RNA, and demonstrated that these solutions typically show Newtonian behavior at shear rates less than 10,000 s−1. However, it is not known how ribosomes carrying nascent protein chains (RNCs) affect solution viscosity.

Subnanometer-Precision Measurements of Transmembrane Motions of Biomolecules in Plasma Membranes Using Quenchers in Extracellular Environment.

Characterization of biomolecular dynamics at cellular membranes lags far behind that in solutions because of challenges to measure transmembrane trafficking with subnanometer precision. Herein, by introducing nonfluorescent quenchers into extracellular environment of live cells, we adopted Förster resonance energy transfer from one donor to multiple quenchers to measure positional changes of biomolecules in plasma membranes. We demonstrated the method by monitoring flip-flops of individual lipids and by capturing transient states of the host defense peptide LL-37 in plasma membranes. The method was also applied to investigate the interaction of the necroptosis-associated protein MLKL with plasma membranes, showing a few distinct depths of MLKL insertion. Our method is especially powerful to quantitate the dynamics of proteins at the cytosolic leaflets of plasma membranes which are usually not accessible by conventional techniques. The method will find wide applications in the systematic analysis of fundamental cellular processes at plasma membranes.

Deleterious effects of carbon-carbon dipolar coupling on RNA NMR dynamics.

Many regulatory RNAs undergo dynamic exchanges that are crucial for their biological functions and NMR spectroscopy is a versatile tool for monitoring dynamic motions of biomolecules. Meaningful information on biomolecular dynamics requires an accurate measurement of relaxation parameters such as longitudinal (R1) rates, transverse (R2) rates and heteronuclear Overhauser effect (hNOE). However, earlier studies have shown that the large 13C-13C interactions complicate analysis of the carbon relaxation parameters. To investigate the effect of 13C-13C interactions on RNA dynamic studies, we performed relaxation measurements on various RNA samples with different labeling patterns and compared these measurements with the computational simulations. For uniformly labeled samples, contributions of the neighboring carbon to R1 measurements were observed. These contributions increased with increasing magnetic field and overall correlation time ([Formula: see text]) for R1 rates, necessitating more careful analysis for uniformly labeled large RNAs. In addition, the hNOE measurements were also affected by the adjacent carbon nuclei. Unlike R1 rates, R1ρ rates showed relatively good agreement between uniformly- and site-selectively labeled samples, suggesting no dramatic effect from their attached carbon, in agreement with previous observations. Overall, having more accurate rate measurements avoids complex analysis and will be a key for interpreting 13C relaxation rates for molecular motion that can provide valuable insights into cellular molecular recognition events.

Chemical Dynamics in Living Cells

We introduce a new type of kinetic model and theory for biological networks, useful for a quantitative description of chemical dynamics in living cells. One advantage of our approach is its applicability to networks producing biomolecules with arbitrary lifetime distributions to which the conventional approaches, such as the classical chemical kinetics, chemical master equation, and chemical Langevin equation, are not applicable. Our approach also enables quantitative investigation into biological networks composed of multi-step or multi-channel reactions whose rates may fluctuate due to their coupling to cell environments. We demonstrate these advantages by providing an unprecedented quantitative explanation of non-classical chemical dynamics observed in various biological systems including single enzymes, in vivo motor-protein multiplexes, and cell systems with various synthetic gene networks. Time-permitting, we will also introduce a new transport equation governing thermal motion of biomolecules in living cells.

A cryo-EM grid preparation device for time-resolved structural studies.

Structural biology generally provides static snapshots of protein conformations that can provide information on the functional mechanisms of biological systems. Time-resolved structural biology provides a means to visualize, at near-atomic resolution, the dynamic conformational changes that macromolecules undergo as they function. X-ray free-electron-laser technology has provided a powerful tool to study enzyme mechanisms at atomic resolution, typically in the femtosecond to picosecond timeframe. Complementary to this, recent advances in the resolution obtainable by electron microscopy and the broad range of samples that can be studied make it ideally suited to time-resolved approaches in the microsecond to millisecond timeframe to study large loop and domain motions in biomolecules. Here we describe a cryo-EM grid preparation device that permits rapid mixing, voltage-assisted spraying and vitrification of samples. It is shown that the device produces grids of sufficient ice quality to enable data collection from single grids that results in a sub-4 Å reconstruction. Rapid mixing can be achieved by blot-and-spray or mix-and-spray approaches with a delay of ∼10 ms, providing greater temporal resolution than previously reported mix-and-spray approaches.

Biomolecular Simulations for Structural Biology: Integrating Co-Evolution, Saxs and FRET

Exploring the interrelationship of structure and function is crucial for the understanding of molecular life. Yet despite significant progress of experimental methods, full characterization of functional cycles for proteins and RNA remains an ongoing challenge. Biomolecular simulations offer a complementary option to experiments. One can use such simulations akin to an atomically resolved microscope to gain insight into the dynamical motion of biomolecules. It is also possible to include additional information as constraints into such simulations. The increasingly ubiquitous availability of sequential information and novel statistical analysis has allowed to trace the co-evolution of residues [1], which can be exploited in structure prediction tools and is, e.g., sufficient for the blind prediction of proteins and RNA[2]. Similarly, one can use low-resolution experimental information such as SAXS data to model suitable biomolecular conformations [submitted] or compare data from simulations directly against experimental measurements such as smFRET data [3].

Water-Compression Gating of Nanopore Transport.

Electric field-driven motion of biomolecules is a process essential to many analytics methods, in particular, to nanopore sensing, where a transient reduction of nanopore ionic current indicates the passage of a biomolecule through the nanopore. However, before any molecule can be examined by a nanopore, the molecule must first enter the nanopore from the solution. Previously, the rate of capture by a nanopore was found to increase with the strength of the applied electric field. Here, we theoretically show that, in the case of narrow pores in graphene membranes, increasing the strength of the electric field can not only decrease the rate of capture, but also repel biomolecules from the nanopore. As the strong electric field polarizes water near and within the nanopore, the high gradient of the field also produces a strong dielectrophoretic force that compresses the water. The pressure difference caused by the sharp water density gradient produces a hydrostatic force that repels DNA or proteins from the nanopore, preventing, in certain conditions, their capture. We show that such local compression of fluid can regulate the transport of biomolecules through nanoscale passages in the absence of physical gates and sort proteins according to their phosphorylated states.

Translational mobilities of proteins in nanochannels: A coarse-grained molecular dynamics study

We investigated the translation of a protein through model nanopores using coarse-grained (CG) nonequilibrium molecular dynamics (NEMD) simulations and compared the mobilities with those obtained from previous coarse-grained equilibrium molecular dynamics model. We considered the effects of nanopore confinement and external force on the translation of streptavidin through nanopores of dimensions representative of experiments. As the nanopore radius approaches the protein hydrodynamic radius, r_{h}/r_{p}→1 (where r_{h} is the hydrodynamic radius of protein and r_{p} is the pore radius), the translation times are observed to increase by two orders of magnitude. The translation times are found to be in good agreement with the one-dimensional biased diffusion model. The results presented in this paper provide useful insights on nanopore designs intended to control the motion of biomolecules.

Nanoplasmonic Upconverting Nanoparticles as Orientation Sensors for Single Particle Microscopy

We showed that the anisotropic disk shape of nanoplasmonic upconverting nanoparticles (NP-UCNPs) creates changes in fluorescence intensity during rotational motion. We determined the orientation by a three-fold change in fluorescence intensity. We further found that the luminescence intensity was strongly dependent on the particle orientation and on polarization of the excitation light. The luminescence intensity showed a three-fold difference between flat and on-edge orientations. The intensity also varied sinusoidally with the polarization of the incident light, with an Imax/Imin ratio of up to 2.02. Both the orientation dependence and Imax/Imin are dependent on the presence of a gold shell on the UCNP. Because the fluorescence depends on the NP’s orientation, the rotational motion of biomolecules coupled to the NP can be detected. Finally, we tracked the real-time rotational motion of a single NP-UCNP in solution between slide and coverslip with diffusivity up to 10−2 μm2s−1.

Studying Solvation of Small Biomolecules via Molecular Dynamics using a Polarizable Force Field

Interactions with solvent have been shown to affect the dynamics of small biomolecules. While bulk properties of solvation can be studied via experiments like spectral measurements, understanding the precise impact of solvent interactions on specific motions of biomolecules, and the spatial extent of impact of the biomolecules on the solvent are accessible through simulations. We have used the polarizable AMOEBA molecular mechanics force field to simulate terahertz (THz) spectra of two zwitterionic peptides, glycine and valine in aqueous solution. Ab initio molecular dynamics (AIMD) simulations have been previously used to study these spectra. An analysis method has been previously developed by Marx and co-workers (Sun et. al. JACS 2014) to decompose the THz spectrum into the component motion modes for specific molecules, as well as modes arising from intermolecular interactions, for AIMD simulations. We present here an approach whereby classical MD simulations performed via the AMOEBA forcefield can be analyzed with that mode decomposition method to obtain dynamic modes for the zwitterions. Based on this decomposition, overall we find very good agreement of the AMOEBA classical MD simulations with AIMD. THz spectral assignments and the spectral decomposition of the total spectrum into intramolecular peptide motions and peptide-water cross-correlation modes shows substantial agreement between AMOEBA and AIMD. The unique feature of this approach comes from the good agreement of the peptide-water cross-correlation modes, which involve distortions of the electron density as a result of polarization and hence cannot be captured by fixed charge force fields. This is a promising first step towards future studies for simulating and decomposing the THz observable for larger solutes such as polymers or proteins where AIMD studies are currently intractable.

Geometric somersaults of a polymer chain through cyclic twisting motions.

This study explores the significance of geometric angle shifts, which we call geometric somersaults, arising from cyclic twisting motions of a polymer chain. A five-bead polymer chain serves as a concise and minimal model of a molecular shaft throughout this study. We first show that this polymer chain can change its orientation about its longitudinal axis largely, e.g., 120^{∘}, under conditions of zero total angular momentum by changing the two dihedral angles in a cyclic manner. This phenomenon is an example of the so-called "falling cat" phenomenon, where a falling cat undergoes a geometric somersault by changing its body shape under conditions of zero total angular momentum. We then extend the geometric somersault of the polymer chain to a noisy and viscous environment, where the polymer chain is steered by external driving forces. This extension shows that the polymer chain can achieve an orientation change keeping its total angular momentum and total external torque fluctuating around zero in a noisy and viscous environment. As an application, we argue that the geometric somersault of the polymer chain by 120^{∘} may serve as a prototypical and coarse-grained model for the rotary motion of the central shaft of ATP synthase (F_{O}F_{1}-ATPase). This geometric somersault is in clear contrast to the standard picture for the rotary motion of the central shaft as a rigid body, which generally incurs nonzero total angular momentum and nonzero total external torque. The power profile of the geometric somersault implies a preliminary mechanism for elastic power transmission. The results of this study may be of fundamental interest in twisting and rotary motions of biomolecules.

Selective Manipulation of Molecules by Electrostatic Force and Detection of Single Molecules in Aqueous Solution

Manipulation of biomolecules in aqueous solution has been a critical issue for the development of many biosensing techniques and biomedical devices. Electrostatic force is an effective method for increasing both sensitivity and selectivity of various biosensing techniques. In this study, we employed surface-enhanced Raman spectroscopy (SERS) as an in situ label-free method to monitor the motion of biomolecules driven by this manipulation technique. We present the results of a combined experimental and simulation study to demonstrate that electrostatic force could enhance SERS detection of molecules in aqueous solutions with respect to sensitivity and selectivity. In regards to sensitivity, we successfully observed the signature of single molecule addition to individual SERS hot spots, in the form of the stepwise increase of Raman signal with time. With regard to selectivity, we obtained discernible SERS signature of selected families of molecules from a mixture of other molecular families of higher concen...