Decoding Protein Dynamics in Cells Using Chemical Cross-Linking and Hierarchical Analysis.

Protein dynamics play a crucial role in their diverse functions. The intracellular environment significantly influences protein dynamics, particularly for intrinsically disordered proteins (IDPs). To comprehensively capture structural information from various proteins within cells and characterize protein dynamics, chemical cross‐linking mass spectrometry was employed. In this study, we introduce a hierarchical decoding strategy that enables the investigation of protein dynamics in vivo. Computational analysis based on distance restraints derived from cross‐links is used to infer protein dynamics in cells. To facilitate this analysis, we leverage the prior structure obtained from AlphaFold2. By employing this strategy, we can characterize the full‐length structure of multi‐domain proteins taking into account their distinct dynamic features. Furthermore, by combining restraint sampling with an unbiased sampling and evaluation approach, we can provide a comprehensive description of the intrinsic motion of IDPs. Consequently, the hierarchical strategy we propose holds significant potential in advancing our understanding of the molecular mechanisms that undelie protein functions in cells.

Incoherent quasielastic neutron scattering (iQENS) is a fascinating technique for investigating the internal dynamics of protein. However, low flux of neutron beam, low signal to noise ratio of QENS spectrometers and unavailability of well-established analyzing method have been obstacles for studying internal dynamics under physiological condition (in solution). The recent progress of neutron source and spectrometer provide the fine iQENS profile with high statistics and as well the progress of computational technique enable us to quantitatively reveal the internal dynamic from the obtained iQENS profile. The internal dynamics of two proteins, globular domain protein (GDP) and intrinsically disordered protein (IDP) in solution, were measured with the state-of-the art QENS spectrometer and then revealed with the newly developed analyzing method. It was clarified that the average relaxation rate of IDP was larger than that of GDP and the fraction of mobile H atoms of IDP was also much higher than that of GDP. Combined with the structural analysis and the calculation of solvent accessible surface area of amino acid residue, it was concluded that the internal dynamics were related to the highly solvent exposed amino acid residues depending upon protein’s structure.

Deciphering Protein Dynamics from NMR Data Using Explicit Structure Sampling and Selection

AlphaFold 2 (AF2) has placed Molecular Biology in a new era where we can visualize, analyze and interpret the structures and functions of all proteins solely from their primary sequences. We performed AF2 structure predictions for various protein systems, including globular proteins, a multi-domain protein, an intrinsically disordered protein (IDP), a randomized protein, two larger proteins (> 1000 AA), a heterodimer and a homodimer protein complex. Our results show that along with the three dimensional (3D) structures, AF2 also decodes protein sequences into residue flexibilities via both the predicted local distance difference test (pLDDT) scores of the models, and the predicted aligned error (PAE) maps. We show that PAE maps from AF2 are correlated with the distance variation (DV) matrices from molecular dynamics (MD) simulations, which reveals that the PAE maps can predict the dynamical nature of protein residues. Here, we introduce the AF2-scores, which are simply derived from pLDDT scores and are in the range of [0, 1]. We found that for most protein models, including large proteins and protein complexes, the AF2-scores are highly correlated with the root mean square fluctuations (RMSF) calculated from MD simulations. However, for an IDP and a randomized protein, the AF2-scores do not correlate with the RMSF from MD, especially for the IDP. Our results indicate that the protein structures predicted by AF2 also convey information of the residue flexibility, i.e., protein dynamics.

Molecular dynamics in proteins animate and play a vital role for biologically relevant processes of these biomacromolecules. Quasielastic incoherent neutron scattering (QENS) is a well-suited experimental method to study protein dynamics from the picosecond to several nanoseconds and in the Ångström length-scale. In QENS experiments of protein solutions hydrogens act as reporters for the motions of methyl groups or amino acids to which they are bound. Neutron Spin-Echo spectroscopy (NSE) offers the highest energy resolution in the field of neutron spectroscopy and allows the study of slow collective motions in proteins up to several hundred nanoseconds and in the nanometer length-scale. In the following manuscript I will review recent studies that stress the relevance of molecular dynamics for protein folding and for conformational transitions of intrinsically disordered proteins (IDPs). During the folding collapse the protein is exploring its accessible conformational space via molecular motions. A large flexibility of partially folded and unfolded proteins, therefore, is mandatory for rapid protein folding. IDPs are a special case as they are largely unstructured under physiological conditions. A large flexibility is a characteristic property of IDPs as it allows, for example, the interaction with various binding partners or the rapid response to different conditions.

Crowded, Cell-like Environment Induces Shape Changes In Aspherical Protein

Prediction of the Effects of the Val66Met Polymorphism on the Conformational Ensemble of an Intrinsically Disordered Protein, Brain-Derived Neurotrophic Factor

During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here we review the links between disordered proteins and the associated networks, and describe the consequences of local, mesoscopic and global network disorder on changes in protein structure and dynamics. We introduce a new classification of protein networks into 'cumulus-type', i.e., those similar to puffy (white) clouds, and 'stratus-type', i.e., those similar to flat, dense (dark) low-lying clouds, and relate these network types to protein disorder dynamics and to differences in energy transmission processes. In the first class, there is limited overlap between the modules, which implies higher rigidity of the individual units; there the conformational changes can be described by an 'energy transfer' mechanism. In the second class, the topology presents a compact structure with significant overlap between the modules; there the conformational changes can be described by 'multi-trajectories'; that is, multiple highly populated pathways. We further propose that disordered protein regions evolved to help other protein segments reach 'rarely visited' but functionally-related states. We also show the role of disorder in 'spatial games' of amino acids; highlight the effects of intrinsically disordered proteins (IDPs) on cellular networks and list some possible studies linking protein disorder and protein structure networks.

Capturing the Cooperativity of Backbone Hydrogen Bonding with Polarizable Force Fields

Dynamical structures of intrinsically disordered proteins (IDPs) and multi-domain proteins that include large ID regions between the domains are unable to be determined by such conventional methods as X-ray crystallography and electron microscopy. Small-angle X-ray scattering (SAXS) is suitable to determine low-resolution structures of proteins and protein complexes in solution, but the structural data on protein dynamics are averaged over the structural ensemble in protein solution. To overcome this problem, we have developed a novel method, named MD-SAXS, of the combined use of SAXS and molecular dynamics (MD) simulation to analyze protein dynamics in solution of multi-subunit protein complexes and multi-domain proteins toward the structural characterization of IDPs. Here we show validity of the method through the structural characterization of restriction Endonuclease EcoO109I.

Theoretical perspectives on nonnative interactions and intrinsic disorder in protein folding and binding

Chapter 19 - The evolution and exploration of intrinsically disordered and phase-separated protein states

It is well-established that dynamics are central to protein function; their importance is implicitly acknowledged in the principles of the Monod, Wyman and Changeux model of binding cooperativity, which was originally proposed in 1965. Nowadays the concept of protein dynamics is formulated in terms of the energy landscape theory, which can be used to understand protein folding and conformational changes in proteins. Because protein dynamics are so important, a key to understanding protein function at the molecular level is to design experiments that allow their quantitative analysis. Nuclear magnetic resonance (NMR) spectroscopy is uniquely suited for this purpose because major advances in theory, hardware, and experimental methods have made it possible to characterize protein dynamics at an unprecedented level of detail. Unique features of NMR include the ability to quantify dynamics (i) under equilibrium conditions without external perturbations, (ii) using many probes simultaneously, and (iii) over large time intervals. Here we review NMR techniques for quantifying protein dynamics on fast (ps-ns), slow (μs-ms), and very slow (s-min) time scales. These techniques are discussed with reference to some major discoveries in protein science that have been made possible by NMR spectroscopy.

Intrinsic dynamics of proteins are known to play important roles in their function. In particular, collective dynamics of a protein, which are defined by the protein’s overall architecture, are important in promoting the active site conformation that favors substrate binding and effective catalysis. The primary sequence of a protein, which determines its three-dimensional structure, encodes unique dynamics. The intrinsic dynamics of a protein actually link protein structure to its function. In the present study, coarse-grained normal mode analysis was performed to examine the intrinsic dynamic patterns of 24 different enzymes involved in primary metabolic pathways. We observed that each metabolic enzyme exhibits unique patterns of motions, which are conserved across multiple species and functionally relevant. Dynamic cross-correlation matrices (DCCMs) are visibly identical for a given enzyme family but significantly different from DCCMs of other protein families, reinforcing that proteins with sim...

Intrinsically disordered proteins (IDPs) have long been a challenge to structural biologists due to their lack of stable secondary structure elements. Hydrogen-Deuterium Exchange (HDX) measured at rapid time scales is uniquely suited to detect structures and hydrogen bonding networks that are briefly populated, allowing for the characterization of transient conformers in native ensembles. Coupling of HDX to mass spectrometry offers several key advantages, including high sensitivity, low sample consumption and no restriction on protein size. This technique has advanced greatly in the last several decades, including the ability to monitor HDX labeling times on the millisecond time scale. In addition, by incorporating the HDX workflow onto a microfluidic platform housing an acidic protease microreactor, we are able to localize dynamic properties at the peptide level. In this study, Time-Resolved ElectroSpray Ionization Mass Spectrometry (TRESI-MS) coupled to HDX was used to provide a detailed picture of residual structure in the tau protein, as well as the conformational shifts induced upon hyperphosphorylation.