Protein Motions Research Articles

Heterogeneous Slowdown of Dynamics in the Condensate of an Intrinsically Disordered Protein.

The high concentration of proteins and other biological macromolecules inside biomolecular condensates leads to dense and confined environments, which can affect the dynamic ensembles and the time scales of the conformational transitions. Here, we use atomistic molecular dynamics (MD) simulations of the intrinsically disordered low complexity domain (LCD) of the human fused in sarcoma (FUS) RNA-binding protein to study how self-crowding inside a condensate affects the dynamic motions of the protein. We found a heterogeneous retardation of the protein dynamics in the condensate with respect to the dilute phase, with large-amplitude motions being strongly slowed by up to 2 orders of magnitude, whereas small-scale motions, such as local backbone fluctuations and side-chain rotations, are less affected. The results support the notion of a liquid-like character of the condensates and show that different protein motions respond differently to the environment.

Development of artificial photosystems based on designed proteins for mechanistic insights into photosynthesis.

This review aims to provide an overview of the progress in protein-based artificial photosystem design and their potential to uncover the underlying principles governing light-harvesting in photosynthesis. While significant advances have been made in this area, a gap persists in reviewing these advances. This review provides a perspective of the field, pinpointing knowledge gaps and unresolved challenges that warrant further inquiry. In particular, it delves into the key considerations when designing photosystems based on the chromophore and protein scaffold characteristics, presents the established strategies for artificial photosystems engineering with their advantages and disadvantages, and underscores the recent breakthroughs in understanding the molecular mechanisms governing light-harvesting, charge separation, and the role of the protein motions in the chromophore's excited state relaxation. By disseminating this knowledge, this article provides a foundational resource for defining the field of bio-hybrid photosystems and aims to inspire the continued exploration of artificial photosystems using protein design.

Inhibitor binding and disruption of coupled motions in MmpL3 protein: Unraveling the mechanism of trehalose monomycolate transport.

Mycobacterial membrane protein Large 3 (MmpL3) of Mycobacterium tuberculosis (Mtb) is crucial for the translocation of trehalose monomycolate (TMM) across the inner bacterial cell membrane, making it a promising target for anti-tuberculosis (TB) drug development. While several structural, microbiological, and in vitro studies have provided significant insights, the precise mechanisms underlying TMM transport by MmpL3 and its inhibition remain incompletely understood at the atomic level. In this study, molecular dynamic (MD) simulations for the apo form and seven inhibitor-bound forms of Mtb MmpL3 were carried out to obtain a thorough comprehension of the protein's dynamics and function. MD simulations revealed that the seven inhibitors in this work stably bind to the central channel of the transmembrane domain and primarily forming hydrogen bonds with ASP251, ASP640, or both residues. Through dynamical cross-correlation matrix and principal component analysis analyses, several types of coupled motions between different domains were observed in the apo state, and distinct conformational states were identified using Markov state model analysis. These coupled motions and varied conformational states likely contribute to the transport of TMM. However, simulations of inhibitor-bound MmpL3 showed an enlargement of the proton channel, potentially disrupting coupled motions. This indicates that inhibitors may impair MmpL3's transport function by directly blocking the proton channel, thereby hindering coordinated domain movements and indirectly affecting TMM translocation.

Utilizing Molecular Dynamics Simulations, Machine Learning, Cryo-EM, and NMR Spectroscopy to Predict and Validate Protein Dynamics.

Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence have revolutionized our understanding of protein dynamics. Nuclear magnetic resonance spectroscopy provides atomic-resolution insights, while molecular dynamics simulations offer detailed trajectories of protein motions. Computational methods applied to X-ray crystallography and cryo-electron microscopy (cryo-EM) have enabled the exploration of protein dynamics, capturing conformational ensembles that were previously unattainable. The integration of machine learning, exemplified by AlphaFold2, has accelerated structure prediction and dynamics analysis. These approaches have revealed the importance of protein dynamics in allosteric regulation, enzyme catalysis, and intrinsically disordered proteins. The shift towards ensemble representations of protein structures and the application of single-molecule techniques have further enhanced our ability to capture the dynamic nature of proteins. Understanding protein dynamics is essential for elucidating biological mechanisms, designing drugs, and developing novel biocatalysts, marking a significant paradigm shift in structural biology and drug discovery.

The Effect of Spin Relaxation on Magnetic Compass Sensitivity in ErCry4a.

This study explores the impact of thermal motion on the magnetic compass mechanism in migratory birds, focusing on the radical pair mechanism within cryptochrome photoreceptors. The coherence of radical pairs, crucial for magnetic field inference, is curbed by spin relaxation induced by intra-protein motion. Molecular dynamics simulations, density-functional-theory-based calculations, and spin dynamics calculations were employed, utilizing Bloch-Redfield-Wangsness (BRW) relaxation theory, to investigate compass sensitivity. Previous research hypothesized that European robin's cryptochrome 4a (ErCry4a) optimized intra-protein motion to minimize spin relaxation, enhancing magnetic sensing compared to the plant Arabidopsis thaliana's cryptochrome 1 (AtCry1). Different correlation times of the nuclear hyperfine coupling constants in AtCry1 and ErCry4a were indeed found, leading to distinct radical pair recombination yields in the two species, with ErCry4a showing optimized sensitivity. However, this optimization is likely negligible in realistic spin systems with numerous nuclear spins. Beyond insights in magnetic sensing, the study presents a detailed method employing molecular dynamics simulations to assess for spin relaxation effects on chemical reactions with realistically modelled protein motion, relevant for studying radical pair reactions at finite temperature.

Genome-wide analysis of the biophysical properties of chromatin and nuclear proteins in living cells with Hi-D.

To understand the dynamic nature of the genome, the localization and rearrangement of DNA and DNA-binding proteins must be analyzed across the entire nucleus of single living cells. Recently, we developed a computational light microscopy technique, called high-resolution diffusion (Hi-D) mapping, which can accurately detect, classify and map diffusion dynamics and biophysical parameters such as the diffusion constant, the anomalous exponent, drift velocity and model physical diffusion from the data at a high spatial resolution across the genome in living cells. Hi-D combines dense optical flow to detect and track local chromatin and nuclear protein motion genome-wide and Bayesian inference to characterize this local movement at nanoscale resolution. Here we present the Python implementation of Hi-D, with an option for parallelizing the calculations to run on multicore central processing units (CPUs). The functionality of Hi-D is presented to the users via user-friendly documented Python notebooks. Hi-D reduces the analysis time to less than 1 h using a multicore CPU with a single compute node. We also present different applications of Hi-D for live-imaging of DNA, histone H2B and RNA polymerase II sequences acquired with spinning disk confocal and super-resolution structured illumination microscopy.

Supramolecular Assemblies in Active Motor-Filament Systems: Micelles, Bilayers, and Foams

Active matter systems evade the constraints of thermal equilibrium, leading to the emergence of intriguing collective behavior. A paradigmatic example is given by motor-filament mixtures, where the motion of motor proteins drives alignment and sliding interactions between filaments and their self-organization into macroscopic structures. After defining a microscopic model for these systems, we derive continuum equations, exhibiting the formation of active supramolecular assemblies such as micelles, bilayers, and foams. The transition between these structures is driven by a branching instability, which destabilizes the orientational order within the micelles, leading to the growth of bilayers at high microtubule densities. Additionally, we identify a fingering instability, modulating the shape of the micelle interface at high motor densities. We study the role of various mechanisms in these two instabilities, such as contractility, active splay, and anchoring, allowing for generalization beyond the system considered here. Published by the American Physical Society 2024

Structural Characterization of Heat Shock Protein 90β and Molecular Interactions with Geldanamycin and Ritonavir: A Computational Study.

Drug repositioning is an important therapeutic strategy for treating breast cancer. Hsp90β chaperone is an attractive target for inhibiting cell progression. Its structure has a disordered and flexible linker region between the N-terminal and central domains. Geldanamycin was the first Hsp90β inhibitor to interact specifically at the N-terminal site. Owing to the toxicity of geldanamycin, we investigated the repositioning of ritonavir as an Hsp90β inhibitor, taking advantage of its proven efficacy against cancer. In this study, we used molecular modeling techniques to analyze the contribution of the Hsp90β linker region to the flexibility and interaction between the ligands geldanamycin, ritonavir, and Hsp90β. Our findings indicate that the linker region is responsible for the fluctuation and overall protein motion without disturbing the interaction between the inhibitors and the N-terminus. We also found that ritonavir established similar interactions with the substrate ATP triphosphate, filling the same pharmacophore zone.

In-silico screening of missense nsSNPs in Delta-opioid receptor protein and their restoring tendency on MCRT interaction; focusing on dynamic nature

Delta-opioid receptor protein (OPRD1) is one of the potential targets for treating pain. The presently available opioid agonists are known to cause unnecessary side effects. To discover a novel opioid agonist, our research group has synthesized a chimeric peptide MCRT and proved its potential activity through in vivo analysis. Non-synonymous SNPs (nsSNPs) missense mutations affect the functionality and stability of proteins leading to diseases. The current research was focused on understanding the role of MCRT in restoring the binding tendency of OPRD1 nsSNPs missense mutations on dynamic nature in comparison with Deltorphin-II and morphiceptin. The deleterious effects of nsSNPs were analyzed using various bioinformatics tools for predicting structural, functional, and oncogenic influence. The shortlisted nine nsSNPs were predicted for allergic reactions, domain changes, post-translation modification, multiple sequence alignment, secondary structure, molecular dynamic simulation (MDS), and peptide docking influence. Further, the docked complex of three shortlisted deleterious nsSNPs was analyzed using an MDS study, and the highly deleterious shortlisted nsSNP A149T was further analyzed for higher trajectory analysis. MCRT restored the binding tendency influence caused by nsSNPs on the dynamics of stability, functionality, binding affinity, secondary structure, residues connection, motion, and folding of OPRD1 protein.

Molecular modeling and simulation approaches to characterize potential molecular targets for burdock inulin to instigate protection against autoimmune diseases.

In the current study, we utilized molecular modeling and simulation approaches to define putative potential molecular targets for Burdock Inulin, including inflammatory proteins such as iNOS, COX-2, TNF-alpha, IL-6, and IL-1β. Molecular docking results revealed potential interactions and good binding affinity for these targets; however, IL-1β, COX-2, and iNOS were identified as the best targets for Inulin. Molecular simulation-based stability assessment demonstrated that inulin could primarily target iNOS and may also supplementarily target COX-2 and IL-1β during DSS-induced colitis to reduce the role of these inflammatory mechanisms. Furthermore, residual flexibility, hydrogen bonding, and structural packing were reported with uniform trajectories, showing no significant perturbation throughout the simulation. The protein motions within the simulation trajectories were clustered using principal component analysis (PCA). The IL-1β-Inulin complex, approximately 70% of the total motion was attributed to the first three eigenvectors, while the remaining motion was contributed by the remaining eigenvectors. In contrast, for the COX2-Inulin complex, 75% of the total motion was attributed to the eigenvectors. Furthermore, in the iNOS-Inulin complex, the first three eigenvectors contributed to 60% of the total motion. Furthermore, the iNOS-Inulin complex contributed 60% to the total motion through the first three eigenvectors. To explore thermodynamically favorable changes upon mutation, motion mode analysis was carried out. The Free Energy Landscape (FEL) results demonstrated that the IL-1β-Inulin achieved a single conformation with the lowest energy, while COX2-Inulin and iNOS-Inulin exhibited two lowest-energy conformations each. IL-1β-Inulin and COX2-Inulin displayed total binding free energies of - 27.76kcal/mol and - 37.78kcal/mol, respectively, while iNOS-Inulin demonstrated the best binding free energy results at - 45.89kcal/mol. This indicates a stronger pharmacological potential of iNOS than the other two complexes. Thus, further experiments are needed to use inulin to target iNOS and reduce DSS-induced colitis and other autoimmune diseases.

Interplay of structural preorganization and conformational sampling in UDP-glucuronic acid 4-epimerase catalysis

Understanding enzyme catalysis as connected to protein motions is a major challenge. Here, based on temperature kinetic studies combined with isotope effect measurements, we obtain energetic description of C-H activation in NAD-dependent UDP-glucuronic acid C4 epimerase. Approach from the ensemble-averaged ground state (GS) to the transition state-like reactive conformation (TSRC) involves, alongside uptake of heat (ΔH‡\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\Delta {{{{{\\rm{H}}}}}}}^{{{\\ddagger}} }$$\\end{document} = 54 kJ mol−1), significant loss in entropy (−TΔS‡\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$-T{\\Delta {{{{{\\rm{S}}}}}}}^{{{\\ddagger}} }$$\\end{document} = 20 kJ mol−1; 298 K) and negative activation heat capacity (ΔCp‡\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\Delta {{{{{\\rm{C}}}}}}}_{{{{{{\\rm{p}}}}}}}^{{{\\ddagger}} }$$\\end{document} = −0.64 kJ mol−1 K−1). Thermodynamic changes suggest the requirement for restricting configurational freedom at the GS to populate the TSRC. Enzyme variants affecting the electrostatic GS preorganization reveal active-site interactions important for precise TSRC sampling and H-transfer. Collectively, our study captures thermodynamic effects associated with TSRC sampling and establishes rigid positioning for C-H activation in an enzyme active site that requires conformational flexibility in fulfillment of its natural epimerase function.

Hydrophobic Clusters Regulate Surface Hydration Dynamics of Bacillus subtilis Lipase A.

The surface hydration diffusivity of Bacillus subtilis Lipase A (BSLA) has been characterized by low-field Overhauser dynamic nuclear polarization (ODNP) relaxometry using a series of spin-labeled constructs. Sites for spin-label incorporation were previously designed via an atomistic computational approach that screened for surface exposure, reflective of the surface hydration comparable to other proteins studied by this method, as well as minimal impact on protein function, dynamics, and structure of BSLA by excluding any surface site that participated in greater than 30% occupancy of a hydrogen bonding network within BSLA. Experimental ODNP relaxometry coupling factor results verify the overall surface hydration behavior for these BSLA spin-labeled sites similar to other globular proteins. Here, by plotting the ODNP parameters of relative diffusive water versus the relative bound water, we introduce an effective "phase-space" analysis, which provides a facile visual comparison of the ODNP parameters of various biomolecular systems studied to date. We find notable differences when comparing BSLA to other systems, as well as when comparing different clusters on the surface of BSLA. Specifically, we find a grouping of sites that correspond to the spin-label surface location within the two main hydrophobic core clusters of the branched aliphatic amino acids isoleucine, leucine, and valine cores observed in the BSLA crystal structure. The results imply that hydrophobic clustering may dictate local surface hydration properties, perhaps through modulation of protein conformations and samplings of the unfolded states, providing insights into how the dynamics of the hydration shell is coupled to protein motion and fluctuations.

Functional protein dynamics in a crystal.

Proteins are molecular machines and to understand how they work, we need to understand how they move. New pump-probe time-resolved X-ray diffraction methods open up ways to initiate and observe protein motions with atomistic detail in crystals on biologically relevant timescales. However, practical limitations of these experiments demands parallel development of effective molecular dynamics approaches to accelerate progress and extract meaning. Here, we establish robust and accurate methods for simulating dynamics in protein crystals, a nontrivial process requiring careful attention to equilibration, environmental composition, and choice of force fields. With more than seven milliseconds of sampling of a single chain, we identify critical factors controlling agreement between simulation and experiments and show that simulated motions recapitulate ligand-induced conformational changes. This work enables a virtuous cycle between simulation and experiments for visualizing and understanding the basic functional motions of proteins.

Metastability of Protein Solution Structures in the Absence of a Solvent: Rugged Energy Landscape and Glass-like Behavior.

Native ion mobility/mass spectrometry is well-poised to structurally screen proteomes but characterizes protein structures in the absence of a solvent. This raises long-standing unanswered questions about the biological significance of protein structures identified through ion mobility/mass spectrometry. Using newly developed computational and experimental ion mobility/ion mobility/mass spectrometry methods, we investigate the unfolding of the protein ubiquitin in a solvent-free environment. Our data suggest that the folded, solvent-free ubiquitin observed by ion mobility/mass spectrometry exists in a largely native fold with an intact β-grasp motif and α-helix. The ensemble of folded, solvent-free ubiquitin ions can be partitioned into kinetically stable subpopulations that appear to correspond to the structural heterogeneity of ubiquitin in solution. Time-resolved ion mobility/ion mobility/mass spectrometry measurements show that folded, solvent-free ubiquitin exhibits a strongly stretched-exponential time dependence, which simulations trace to a rugged energy landscape with kinetic traps. Unfolding rate constants are estimated to be approximately 800 to 20,000 times smaller than in the presence of water, effectively quenching the unfolding process on the time scale of typical ion mobility/mass spectrometry measurements. Our proposed unfolding pathway of solvent-free ubiquitin shares substantial characteristics with that established for the presence of solvent, including a polarized transition state with significant native content in the N-terminal β-hairpin and α-helix. Our experimental and computational data suggest that (1) the energy landscape governing the motions of folded, solvent-free proteins is rugged in analogy to that of glassy systems; (2) large-scale protein motions may at least partially be determined by the amino acid sequence of a polypeptide chain; and (3) solvent facilitates, rather than controls, protein motions.

Allosteric activation unveils protein-mass modulation of ATP phosphoribosyltransferase product release

Heavy-isotope substitution into enzymes slows down bond vibrations and may alter transition-state barrier crossing probability if this is coupled to fast protein motions. ATP phosphoribosyltransferase from Acinetobacter baumannii is a multi-protein complex where the regulatory protein HisZ allosterically enhances catalysis by the catalytic protein HisGS. This is accompanied by a shift in rate-limiting step from chemistry to product release. Here we report that isotope-labelling of HisGS has no effect on the nonactivated reaction, which involves negative activation heat capacity, while HisZ-activated HisGS catalytic rate decreases in a strictly mass-dependent fashion across five different HisGS masses, at low temperatures. Surprisingly, the effect is not linked to the chemical step, but to fast motions governing product release in the activated enzyme. Disruption of a specific enzyme-product interaction abolishes the isotope effects. Results highlight how altered protein mass perturbs allosterically modulated thermal motions relevant to the catalytic cycle beyond the chemical step.

Mechanistic insights into the conformational changes and alterations in residual communications due to the mutations in the pncA Gene of Mycobacterium tuberculosis: A computational perspective for effective therapeutic solutions

Due to its emerging resistance to first-line anti-TB medications, tuberculosis (TB) is one of the most contagious illness in the world. According to reports, the effectiveness of treating TB is severely impacted by drug resistance, notably resistance caused by mutations in the pncA gene-encoded pyrazinamidase (PZase) to the front-line drug pyrazinamide (PZA). The present study focused on investigating the resistance mechanism caused by the mutations D12N, T47A, and H137R to better understand the structural and molecular events responsible for the resistance acquired by the pncA gene of Mycobacterium tuberculosis (MTB) at the structural level. Bioinformatics analysis predicted that all three mutations were deleterious and located near the active centre of the pncA, affecting its functional activity. Furthermore, molecular dynamics simulation (MDS) results established that mutations significantly reduced the structural stability and caused the rearrangement of FE2+ in the active centre of pncA. Moreover, essential dynamics analysis, including principal component analysis (PCA) and free energy landscape (FEL), concluded variations in the protein motion and decreased conformational space in the mutants. Additionally, the mutations potentially impacted the network topologies and altered the residual communications in the network. The complex simulation study results established the significant movement of the flap region from the active centre of mutant complexes, further supporting the flap region’s significance in developing resistance to the PZA drug. This study advances our knowledge of the primary cause of the mechanism of PZA resistance and the structural dynamics of pncA mutants, which will help us to design new and potent chemical scaffolds to treat drug-resistant TB (DR-TB).

Changes in an enzyme ensemble during catalysis observed by high-resolution XFEL crystallography.

Enzymes populate ensembles of structures necessary for catalysis that are difficult to experimentally characterize. We use time-resolved mix-and-inject serial crystallography at an x-ray free electron laser to observe catalysis in a designed mutant isocyanide hydratase (ICH) enzyme that enhances sampling of important minor conformations. The active site exists in a mixture of conformations, and formation of the thioimidate intermediate selects for catalytically competent substates. The influence of cysteine ionization on the ICH ensemble is validated by determining structures of the enzyme at multiple pH values. Large molecular dynamics simulations in crystallo and time-resolved electron density maps show that Asp17 ionizes during catalysis and causes conformational changes that propagate across the dimer, permitting water to enter the active site for intermediate hydrolysis. ICH exhibits a tight coupling between ionization of active site residues and catalysis-activated protein motions, exemplifying a mechanism of electrostatic control of enzyme dynamics.

Identification of the Thermal Activation Network in Human 15-Lipoxygenase-2: Divergence from Plant Orthologs and Its Relationship to Hydrogen Tunneling Activation Barriers.

The oxidation of polyunsaturated fatty acids by lipoxygenases (LOXs) is initiated by a C-H cleavage step in which the hydrogen atom is transferred quantum mechanically (i.e., via tunneling). In these reactions, protein thermal motions facilitate the conversion of ground-state enzyme-substrate complexes to tunneling-ready configurations and are thus important for transferring energy from the solvent to the active site for the activation of catalysis. In this report, we employed temperature-dependent hydrogen-deuterium exchange mass spectrometry (TDHDX-MS) to identify catalytically linked, thermally activated peptides in a representative animal LOX, human epithelial 15-LOX-2. TDHDX-MS of wild-type 15-LOX-2 was compared to two active site mutations that retain structural stability but have increased activation energies (Ea) of catalysis. The Ea value of one variant, V427L, is implicated to arise from suboptimal substrate positioning by increased active-site side chain rotamer dynamics, as determined by X-ray crystallography and ensemble refinement. The resolved thermal network from the comparative Eas of TDHDX-MS between wild-type and V426A is localized along the front face of the 15-LOX-2 catalytic domain. The network contains a clustering of isoleucine, leucine, and valine side chains within the helical peptides. This thermal network of 15-LOX-2 is different in location, area, and backbone structure compared to a model plant lipoxygenase from soybean that exhibits a low Ea value of catalysis compared to the human ortholog. The presented data provide insights into the divergence of thermally activated protein motions in plant and animal LOXs and their relationships to the enthalpic barriers for facilitating hydrogen tunneling.

Simultaneous Recording of Remote Domain Dynamics in Membrane Proteins Using the Double-Labeled DXB/DXT Technique.

Protein dynamics play important roles in biological functions, which accompany allosteric structure changes. Diffracted X-ray blinking (DXB) uses monochromatic X-rays and nanocrystal probes. The intramolecular motion of target proteins is analyzed from the intensity changes in detector signals at the diffraction rings. In contrast, diffracted X-ray tracking (DXT) elucidates molecular dynamics by analyzing the trajectories of Laue spots. In this study, we have developed a dual-labeling technique for DXB and DXT, allowing the simultaneous observation of motions at different domains in proteins. We identified zinc oxide (ZnO) crystals as promising candidates for the second labeling probes due to their excellent diffraction patterns, high chemical stability, and favorable binding properties with proteins. The diffraction spots from the ZnO crystals are sufficiently separated from those of gold, enabling independent motion analysis at different domains. Dual-labeling DXB was employed for the motion analysis of the 5-HT2A receptor in living cells. Simultaneous motion recording of the N-terminus and the second extracellular loop demonstrated ligand-induced motion suppression at both domains. The dual-labeling DXT technique demonstrated a capsaicin-induced peak shift in the two-dimensional motion maps at the N-terminus of the TRPV1 protein, but the peak shift was not obvious in the C-terminus. The capsaicin-induced motion modulation was recovered by the addition of the competitive inhibitor AMG9810.

Prediction of order parameters based on protein NMR structure ensemble and machine learning.

The fast motions of proteins at the picosecond to nanosecond timescale, known as fast dynamics, are closely related to protein conformational entropy and rearrangement, which in turn affect catalysis, ligand binding and protein allosteric effects. The most used NMR approach to study fast protein dynamics is the model free method, which uses order parameter S2 to describe the amplitude of the internal motion of local group. However, to obtain order parameter through NMR experiments is quite complex and lengthy. In this paper, we present a machine learning approach for predicting backbone 1H-15N order parameters based on protein NMR structure ensemble. A random forest model is used to learn the relationship between order parameters and structural features. Our method achieves high accuracy in predicting backbone 1H-15N order parameters for a test dataset of 10 proteins, with a Pearson correlation coefficient of 0.817 and a root-mean-square error of 0.131.