Protein Conformational Dynamics Research Articles

Across atoms to crossing continents: Application of similarity measures to biological location data.

Biological processes involve movements across all measurable scales. Similarity measures can be applied to compare and analyze these movements but differ in how differences in movement are aggregated across space and time. The present study reviews frequently-used similarity measures, such as the Hausdorff distance, Fréchet distance, Dynamic Time Warping, and Longest Common Subsequence, jointly with several measures less used in biological applications (Wasserstein distance, weak Fréchet distance, and Kullback-Leibler divergence), and provides computational tools for each of them that may be used in computational biology. We illustrate the use of the selected similarity measures in diagnosing differences within two extremely contrasting sets of biological data, which, remarkably, may both be relevant for magnetic field perception by migratory birds. Specifically, we assess and discuss cryptochrome protein conformational dynamics and extreme migratory trajectories of songbirds between Alaska and Africa. We highlight how similarity measures contrast regarding computational complexity and discuss those which can be useful in noise elimination or, conversely, are sensitive to spatiotemporal scales.

FLEXR: automated multi-conformer model building using electron-density map sampling.

Protein conformational dynamics that may inform biology often lie dormant in high-resolution electron-density maps. While an estimated ∼18% of side chains in high-resolution models contain alternative conformations, these are underrepresented in current PDB models due to difficulties in manually detecting, building and inspecting alternative conformers. To overcome this challenge, we developed an automated multi-conformer modeling program, FLEXR. Using Ringer-based electron-density sampling, FLEXR builds explicit multi-conformer models for refinement. Thereby, it bridges the gap of detecting hidden alternate states in electron-density maps and including them in structural models for refinement, inspection and deposition. Using a series of high-quality crystal structures (0.8-1.85 Å resolution), we show that the multi-conformer models produced by FLEXR uncover new insights that are missing in models built either manually or using current tools. Specifically, FLEXR models revealed hidden side chains and backbone conformations in ligand-binding sites that may redefine protein-ligand binding mechanisms. Ultimately, the tool facilitates crystallographers with opportunities to include explicit multi-conformer states in their high-resolution crystallographic models. One key advantage is that such models may better reflect interesting higher energy features in electron-density maps that are rarely consulted by the community at large, which can then be productively used for ligand discovery downstream. FLEXR is open source and publicly available on GitHub at https://github.com/TheFischerLab/FLEXR.

Structure-based identification of potential substrate antagonists for isethionate sulfite-lyase enzyme of Bilophila Wadsworthia: Towards novel therapeutic intervention to curb gut-associated illness

Bilophila wadsworthia is one of the prominent sources of hydrogen sulfide (H2S) production in appendices, excessive levels of which can result in a weaker colonic mucus barrier, inflammatory bowel disease, and colorectal cancer. Isethionate sulfite-lyase (IslA) enzyme catalyzes H2S production by cleaving CS bond in isethionate, producing acetaldehyde and sulfite. In this study, we aimed to identify potential substrate antagonists for IsIA using a structure-based drug design. Initially, pharmacophore-based computational screening of the ZINC20 database yielded 66 hits that were subjected to molecular docking targeting the isethionate binding site of IsIA. Based on striking docking scores, nine compounds showed strong interaction with critical IsIA residues (Arg189, Gln193, Glu470, Cys468, and Arg678), drug-like features, appropriate adsorption, metabolism, excretion, and excretion profile with non-toxicity. Molecular dynamics simulations uncovered the significant impact of binding the compounds on protein conformational dynamics. Finally, binding free energies revealed substantial binding affinity (ranging from −35.23 to −53.88 kcal/mol) of compounds (ZINC913876497, ZINC913856647, ZINC914263733, ZINC914137795, ZINC915757996, ZINC914357083, ZINC913934833, ZINC9143362047, and ZINC913854740) for IsIA. The compounds proposed herein through a multi-faceted computational strategy can be experimentally validated as potential substrate antagonists of B. wadsworthia's IsIA for developing new medications to curb gut-associated illness in the future.

Bleaching-resistant, Near-continuous Single-molecule Fluorescence and FRET Based on Fluorogenic and Transient DNA Binding.

Photobleaching of fluorescent probes limits the observation span of typical single-molecule fluorescence measurements and hinders observation of dynamics at long timescales. Here, we present a general strategy to circumvent photobleaching by replenishing fluorescent probes via transient binding of fluorogenic DNAs to complementary DNA strands attached to a target molecule. Our strategy allows observation of near-continuous single-molecule fluorescence for more than an hour, a timescale two orders of magnitude longer than the typical photobleaching time of single fluorophores under our conditions. Using two orthogonal sequences, we show that our method is adaptable to Förster Resonance Energy Transfer (FRET) and that can be used to study the conformational dynamics of dynamic structures, such as DNA Holliday junctions, for extended periods. By adjusting the temporal resolution and observation span, our approach enables capturing the conformational dynamics of proteins and nucleic acids over a wide range of timescales.

Effective Molecular Dynamics from Neural Network-Based Structure Prediction Models.

Recent breakthroughs in neural network-based structure prediction methods, such as AlphaFold2 and RoseTTAFold, have dramatically improved the quality of computational protein structure prediction. These models also provide statistical confidence scores that can estimate uncertainties in the predicted structures, but it remains unclear to what extent these scores are related to the intrinsic conformational dynamics of proteins. Here, we compare AlphaFold2 prediction scores with explicit large-scale molecular dynamics simulations of 28 one- and two-domain proteins with varying degrees of flexibility. We demonstrate a strong correlation between the statistical prediction scores and the explicit motion derived from extensive atomistic molecular dynamics simulations and further derive an elastic network model based on the statistical scores of AlphFold2 (AF-ENM), which we benchmark in combination with coarse-grained molecular dynamics simulations. We show that our AF-ENM method reproduces the global protein dynamics with improved accuracy, providing a powerful way to derive effective molecular dynamics using neural network-based structure prediction models.

Torsion angles to map and visualize the conformational space of a protein.

Present understanding of protein structure dynamics trails behind that of static structures. A torsion-angle-based approach, called the representation of protein entities, derives an interpretable conformational space that correlates with data collection temperature, resolution, and reaction coordinate. For more complex systems, atomic coordinates fail to separate functional conformational states, which are still preserved by torsion angle-derived space. This indicates that torsion angles are often a more sensitive and biologically relevant descriptor for protein conformational dynamics than atomic coordinates.

Online Fully Automated System for Hydrogen/Deuterium-Exchange Mass Spectrometry with Millisecond Time Resolution.

Amide hydrogen/deuterium-exchange mass spectrometry (HDX-MS) is a powerful tool for analyzing the conformational dynamics of proteins in a solution. Current conventional methods have a measurement limit starting from several seconds and are solely reliant on the speed of manual pipetting or a liquid handling robot. Weakly protected regions of polypeptides, such as in short peptides, exposed loops and intrinsically disordered the protein exchange on the millisecond timescale. Typical HDX methods often cannot resolve the structural dynamics and stability in these cases. Numerous academic laboratories have demonstrated the considerable utility of acquiring HDX-MS data in the sub-second regimes. Here, we describe the development of a fully automated HDX-MS apparatus to resolve amide exchange on the millisecond timescale. Like conventional systems, this instrument boasts automated sample injection with software selection of labeling times, online flow mixing and quenching, while being fully integrated with a liquid chromatography-MS system for existing standard "bottom-up" workflows. HDX-MS's rapid exchange kinetics of several peptides demonstrate the repeatability, reproducibility, back-exchange, and mixing kinetics achieved with the system. Comparably, peptide coverage of 96.4% with 273 peptides was achieved, supporting the equivalence of the system to standard robotics. Additionally, time windows of 50 ms-300 s allowed full kinetic transitions to be observed for many amide groups; especially important are short time points (50-150 ms) for regions that are likely highly dynamic and solvent- exposed. We demonstrate that information on structural dynamics and stability can be measured for stretches of weakly stable polypeptides in small peptides and in local regions of a large enzyme, glycogen phosphorylase.

Characterization of the interaction between the tumour suppressor p53 and heme and its role in the protein conformational dynamics studied by various spectroscopic techniques and hydrogen/deuterium exchange coupled with mass spectrometry

The tumour suppressor p53 regulates the expression of a myriad of proteins that are important for numerous cellular processes, including apoptosis, cell cycle arrest, DNA repair, metabolism, and even autophagy and ferroptosis. Aside from DNA, p53 can interact with many types of partners including proteins and small organic molecules. The ability of p53 to interact with heme has been reported so far. In this study, we used various spectroscopic studies to conduct a thorough biophysical characterization of the interaction between p53 and heme concerning the oxidation, spin, coordination, and ligand state of heme iron. We found that the p53 oligomeric state and zinc biding ability are preserved upon the interaction with heme. Moreover, we described the effect of heme binding on the conformational dynamics of p53 by hydrogen/deuterium exchange coupled with mass spectrometry. Specifically, the conformational flexibility of p53 is significantly increased upon interaction with heme, while its affinity to a specific DNA sequence is reduced by heme. The inhibitory effect of DNA binding by heme is partially reversible. We discuss the potential heme binding sites in p53 with respect to the observed conformational dynamics changes and perturbed DNA-binding ability of p53 upon interaction with heme.

Heterogeneous and Allosteric Role of Surface Hydration for Protein-Ligand Binding.

Atomistic-level understanding of surface hydration mediating protein-protein interactions and ligand binding has been a challenge due to the dynamic nature of water molecules near the surface. We develop a computational method to evaluate the solvation free energy based on the density map of the first hydration shell constructed from all-atom molecular dynamics simulation and use it to examine the binding of two intrinsically disordered ligands to their target protein domain. One ligand is from the human protein, and the other is from the 1918 Spanish flu virus. We find that the viral ligand incurs a 6.9 kcal/mol lower desolvation penalty upon binding to the target, which is consistent with its stronger binding affinity. The difference arises from the spatially fragmented and nonuniform water density profiles of the first hydration shell. In particular, residues that are distal from the ligand-binding site contribute to a varying extent to the desolvation penalty, among which the "entropy hotspot" residues contribute significantly. Thus, ligand binding alters hydration on remote sites in addition to affecting the binding interface. The nonlocal effect disappears when the conformational motion of the protein is suppressed. The present results elucidate the interplay between protein conformational dynamics and surface hydration. Our approach of measuring the solvation free energy based on the water density of the first hydration shell is tolerant of the conformational fluctuation of protein, and we expect it to be applicable to investigating a broad range of biomolecular interfaces.

Probing protein structural dynamics at the single-molecule level by nanopore tweezers.

Proteins are dynamic entities that sample multiple conformations over a range of time scales. Understanding how proteins work requires a full description of their conformational dynamics over time. Nuclear magnetic resonance (NMR) spectroscopy can measure protein dynamics at multiple time scales, however, application is laborious and limited to relatively small proteins that can be stably prepared at high concentrations. Conformational heterogeneity, such as multiple weakly populated conformational states, is challenging to resolve from ensemble methods such as NMR due to averaging effects. Integrative approaches and single-molecule techniques can be advantageous for revealing transient protein dynamics and functional heterogeneities. Nanopore tweezers have emerged as a powerful, single-molecule analytical tool to monitor the protein's conformational dynamics. Nanopore tweezers confine a single protein within the pore lumen and measure ionic current changes induced by the protein analyte's motion. Here we will present several studies of ClyA nanopore tweezers to showcase their utility in resolving ligand interaction modes, screening allosteric drugs and investigating intrinsically disordered protein interactions.

Characterizing protein conformational ensembles and dynamics with 2D IR spectroscopy.

Advances in protein two-dimensional infrared spectroscopy and computational spectroscopy of amide I vibrations have provided a way to characterize the conformational variation and disorder in protein structure. These techniques use isotope-edited amide I spectra in combination with spectra computed from Markov state models built from molecular dynamics simulations to infer variation in local configuration and to refine ensembles for peptides and proteins. This talk will describe these tools drawing on examples from studies of insulin monomer and dimer structure and the dynamic interactions in the monomer-dimer equilibrium.

Integration of smFRET and molecular dynamics to characterize conformational dynamics of the spike protein of wild-type SARS-CoV-2 and its variants.

Since the rise of the COVID-19 pandemic, researchers have pushed for development of efficient therapeutics and vaccines to assist in preventing the severity of its viral effects. A major target has been the trimeric SARS-CoV-2 spike protein. There has been various experimental and computational efforts to characterize the structural dynamics of this protein at different stages of its mechanisms. Among these methods are single molecule fluorescence resonance energy transfer (smFRET) experiments as well as molecular dynamics (MD) simulations. The purpose of our current work here is to combine the existing data from smFRET experiments and MD simulations to provide a more complete picture of prefusion SARS-CoV-2 spike protein conformational dynamics. We have particularly examined the conformational dynamics of several variants of this protein in a comparative manner. Specifically, we have examined multiple computational methods based on “implicit screening” approach within different approximations to predict dye-dye distance and FRET efficiency distributions to provide reliable interpretations for both smFRET experimental data and MD simulation data of various spike protein variants including the wild-type, the alpha, beta, gamma, delta, and omega variants as well as the engineered spike protein used in the Moderna vaccine. This work sheds light on the structural heterogeneity of the spike protein in different variants of SARS-CoV-2.

A generic rotamer model to explain the temperature dependence of BSA protein fluorescence

AbstractProtein fluorescence signals essential information about the conformational dynamics of proteins. Different types of intrinsic fluorophores reflect different protein local or global structural changes. Bovine Serum Albumin (BSA) is a transport protein that contains two intrinsic fluorophores: Tryptophan134 (Trp134) and Tryptophan213 (Trp213). This protein displays an interesting temperature dependence of the tryptophan fluorescence. However, the molecular mechanism of the temperature dependence is still unclear. In this work, we propose a generic rotamer model to explain this phenomenon. The model assumes the presence of rotamer‐specific fluorescence lifetimes. The fluorescence temperature dependence is caused by the population shifts between different rotamers due to thermal effects. As a proof of concept, we show that the tryptophan's two fluorescence lifetimes (𝜏1 = 0.4–0.5 ns and 𝜏2 = 2‐4 ns) are sufficient to qualitatively explain the fluorescence intensity change at different temperatures, both in buffer solution (water) and in the protein. To computationally verify our rotamer hypothesis, we use an all‐atom molecular dynamics simulation to study the effects of temperature on the two tryptophans' rotamer dynamics. The simulations show that Trp134 is more sensitive to temperature, consistent with experimental observations. Overall, the results support that the temperature dependence of fluorescence in the protein BSA is due to local conformational changes at the residue level. This work sheds light on the relationship between tryptophan's rotamer dynamics and its ability to fluorescence.

Protein Conformational Dynamics Underlie Selective Recognition of Thermophilic over Mesophilic Enzyme I by a Substrate Analogue.

Substrate selectivity is an important preventive measure to decrease the possibility of cross interactions between enzymes and metabolites that share structural similarities. In addition, understanding the mechanisms that determine selectivity towards a particular substrate increases the knowledge base for designing specific inhibitors for target enzymes. Here, we combine NMR, molecular dynamics (MD) simulations, and protein engineering to investigate how two substrate analogues, allylicphosphonate (cPEP) and sulfoenolpyruvate (SEP), recognize the mesophilic (eEIC) and thermophilic (tEIC) homologues of the receptor domain of bacterial Enzyme I, which has been proposed as a target for antimicrobial research. Chemical Shift Perturbation (CSP) experiments show that cPEP and SEP recognize tEIC over the mesophilic homologue. Combined Principal Component Analysis of half-microsecond-long MD simulations reveals that incomplete quenching of a breathing motion in the eEIC-ligand complex destabilizes the interaction and makes the investigated substrate analogues selective toward the thermophilic enzyme. Our results indicate that residual protein motions need to be considered carefully when optimizing small molecule inhibitors of EI. In general, our work demonstrates that protein conformational dynamics can be exploited in the rational design and optimization of inhibitors with subfamily selectivity.

Efficient protein conformation dynamics characterization enabled by mobility-mass spectrometry

Protein structure dynamics in solution and from solution to gas phase are important but challenging topics. Great efforts and advances have been made especially since the wide application of ion mobility mass spectrometry (IM-MS), by which protein collision cross section (CCS) in gas phase could be measured. Due to the lack of efficient experimental methods, protein structures in protein databank are typically referred as their structures in solution. Although conventional structural biology techniques provide high-resolution protein structures, complicated and stringent processes also limit their applicability under different solvent conditions, thus preventing the capture of protein dynamics in solution. Enabled by the combination of mobility capillary electrophoresis (MCE) and IM-MS, an efficient experimental protocol was developed to characterize protein conformation dynamics in solution and from solution to gas phase. As a first attempt, key factors that affecting protein conformations were distinguished and evaluated separately, including pH, temperature, softness of ionization process, presence and specific location of disulfide bonds. Although similar extent of unfolding could be observed for different proteins, in-depth analysis reveals that pH decrease from 7.0 to 3.0 dominates the unfolding of proteins without disulfide bonds in conventional ESI-MS experiments; while harshness of the ionization process dominates the unfolding of proteins with disulfide bonds. Second, disulfide bonds show capability of preserving protein conformations in acidic solution environments. However, by monitoring protein conformation dynamics and comparing results from different proteins, it is also found that their capability is position dependent. Surprisingly, disulfide bonds did not show the capability of preserving protein conformations during ionization processes.

Exploring the role of preferential solvation in the stability of globular proteins through the study of ovalbumin interaction with organic additives

<abstract> <p>The impact of denaturing and stabilizing osmolytes on protein conformational dynamics has been extensively explored due to the significant contribution of protein solvation to the stability, function, malfunction and regulation of globular proteins. We studied the effect of two nonspecific organic molecules, urea, which is a conventional denaturant, and dimethyl sulfoxide (DMSO), which is a multilateral organic solvent, on the stability and conformational dynamics of a non-inhibitory serpin, ovalbumin (OVA). A differential scanning microcalorimetry (DSC) experimental series conducted in the phosphate buffer solutions containing 0–30% of additives revealed the destabilizing impact of both urea and DMSO in a mild acidic media, manifested in the gradual decrease of thermal unfolding enthalpy and transition temperature. These findings differ from the results observed in our study of the mild alkaline DMSO buffered solutions of OVA, where the moderate stabilization of OVA was observed in presence of 5–10% of DMSO. However, the overall OVA interaction patterns with urea and DMSO are consistent with our previous findings on the stability and conformational flexibility of another model globular protein, α-chymotrypsin, in similar medium conditions. The obtained results could be explained by preferential solvation patterns. Positive preferential solvation of protein by urea in urea/water mixtures mainly weakens the hydrophobic interactions of the protein globule and eventually leads to the disruption of the tertiary structure within the whole range of urea concentrations. Alternatively, under certain experimental conditions in DMSO/water mixtures, positive preferential solvation by water molecules can be observed. We assume that the switch to the positive preferential solvation by DMSO, which is shown to have a soft maximum around 20–30% DMSO, could be shifted towards lower additive concentrations due to the intrinsic capability of ovalbumin OVA to convert into a heat-stable, yet flexible set of conformations that have increased the surface hydrophobicity, characteristic to molten-globule-like states.</p> </abstract>

Single-molecule FRET for virology: 20 years of insight into protein structure and dynamics.

Although viral protein structure and replication mechanisms have been explored extensively with X-ray crystallography, cryo-electron microscopy, and population imaging studies, these methods are often not able to distinguish dynamic conformational changes in real time. Single-molecule fluorescence resonance energy transfer (smFRET) offers unique insights into interactions and states that may be missed in ensemble studies, such as nucleic acid or protein structure, and conformational transitions during folding, receptor-ligand interactions, and fusion. We discuss the application of smFRET to the study of viral protein conformational dynamics, with a particular focus on viral glycoprotein dynamics, viral helicases, proteins involved in HIV reverse transcription, and the influenza RNA polymerase. smFRET experiments have played a crucial role in deciphering conformational changes in these processes, emphasising the importance of smFRET as a tool to help elucidate the life cycle of viral pathogens and identify key anti-viral targets.

ARCHE-NOAH: NMR supersequence with five different CEST experiments for studying protein conformational dynamics.

An NMR NOAH-supersequence is presented consisting of five CEST experiments for studying protein backbone and side-chain dynamics by 15N-CEST, carbonyl-13CO-CEST, aromatic-13Car-CEST, 13Cα-CEST, and methyl-13Cmet-CEST. The new sequence acquires the data for these experiments in a fraction of the time required for the individual experiments, saving over four days of NMR time per sample.

High Pressure CPMG and CEST Reveal That Cavity Position Dictates Distinct Dynamic Disorder in the PP32 Repeat Protein.

Given the central role of conformational dynamics in protein function, it is essential to characterize the time scales and structures associated with these transitions. High pressure (HP) perturbation favors transitions to excited states because they typically occupy a smaller molar volume, thus facilitating characterization of conformational dynamics. Repeat proteins, with their straightforward architecture, provide good models for probing the sequence dependence of protein conformational dynamics. Investigations of chemical exchange by 15N CPMG relaxation dispersion analysis revealed that introduction of a cavity via substitution of isoleucine 7 by alanine in the N-terminal capping motif of the pp32 leucine-rich repeat protein leads to pressure-dependent conformational exchange detected on the 500 μs-2 ms CPMG time scale. Exchange amplitude decreased from the N- to C-terminus, revealing a gradient of conformational exchange across the protein. In contrast, introduction of a cavity in the central core of pp32 via the L60A mutation led to pressure-induced exchange on a slower (>2 ms) time scale detected by 15N-CEST analysis. Excited state 15N chemical shifts indicated that in the excited state detected by HP CEST, the N-terminal region is mostly unfolded, while the core retains native-like structure. These HP chemical exchange measurements reveal that cavity position dictates exchange on distinct time scales, highlighting the subtle, yet central role of sequence in determining protein conformational dynamics.

Measuring Structural Changes in Cytochrome c under Crowded Conditions Using In Vitro and In Silico Approaches.

It is known from in vitro studies that macromolecular crowding in the cell effects protein structure, stability and function; but predictive studies are relatively unexplored. There are few reports where the effect of various crowder mixtures has been exploited to discern their combined effect on the structural stability of proteins. These studies are more significant because their effect can mimicked with in vivo conditions, where the environment is heterogeneous. Effects of two crowders, polyethylene glycol (PEG 400 Da), and its monomer ethylene glycol (EG) alone and in mixture on the structural stability of cytochrome c (cyt c) were determined using various spectroscopic and bioinformatics tools. The main conclusions of our study are (i) the monomer EG has a kosmotropic effect on the protein (stabilizes the protein), and has no significant effect on the tertiary structure; (ii) PEG 400 destabilizes the structure as well as the stability of the protein; and (iii) EG counteracts the destabilizing effect of PEG 400. From this investigation, it seems evident that proteins may fold or unfold in the crowded environment of the cell where various interactions assist them to maintain their structure for their functions. Bioinformatics approaches were also used to support all of the in vitro observations. Cyt c is functional protein; if the structure of the protein is modulated due to change in the environment its nature of function will also change. Our research addresses the question by modulating the environment around the protein, and the macromolecule (protein) conformation dynamics and interaction study via in vitro and in silico approaches which indirectly compares with that of the environment in-cellular milieu, which is highly crowded.