Protein Conformational Dynamics Research Articles

Elucidating the interactions of advanced glycation end products with RAGE, employing molecular docking and MD simulation approaches: Implications of potent therapeutic for diabetes and its related complications

Diabetes mellitus is a global health challenge, ranking third among the mortality rates globally. Diabetic-mediated Advanced glycation end products (AGEs) associated with Receptor for Advanced Glycation End-products (RAGE) contribute to chronic diabetes and its complications, inflammatory, cancer, and neurodegenerative disorders. The information behind the binding mechanisms between AGEs-RAGE complexes remains elusive. In the current study, we used advanced computational approaches to reveal the intramolecular interactions of AGEs-RAGE which leads to multiple diseases. We have characterized AGEs-RAGE interactions by protein–ligand docking and molecular dynamic (MD) simulations were further conducted to evaluate the AGEs-RAGE complex stability. Subsequently, several residues emerged as pivotal in AGEs-RAGE complex formation. Further, MD simulation provides valuable insights into structural movements, stability, and conformational dynamics of protein–ligand complexes. Our findings underscore new insights into molecular mechanisms of AGEs-RAGE complex formation in diabetes and its related complications and the ease of the drug discovery process.

Direct lipid interactions control SARS-CoV-2 M protein conformational dynamics and virus assembly.

M is the most abundant structural membrane protein in coronaviruses and is essential for the formation of infectious virus particles. SARS-CoV-2 M adopts two conformations, M short and M long , and regulated transition between states is hypothesized to coordinate viral assembly and budding. However, the factors that regulate M conformation and roles for each state are unknown. Here, we discover a direct M-sphingolipid interaction that controls M conformational dynamics and virus assembly. We show M binds Golgi-enriched anionic lipids including ceramide-1-phosphate (C1P). Molecular dynamics simulations show C1P interaction promotes a long to short transition and energetically stabilizes M short . Cryo-EM structures show C1P specifically binds M short at a conserved site bridging transmembrane and cytoplasmic regions. Disrupting M short -C1P interaction alters M subcellular localization, reduces interaction with Spike and E, and impairs subsequent virus-like particle cell entry. Together, these results show endogenous signaling lipids regulate M structure and support a model in which M short is stabilized in the early endomembrane system to organize other structural proteins prior to viral budding.

Insights into the Structure and Dynamics of Proteins from 19F Solution NMR Spectroscopy.

19F NMR spectroscopy has recently witnessed a resurgence as an attractive analytical tool for the study of the structure and dynamics of biomolecules in vitro and in cells, despite reports of its applications in biomolecular NMR since the 1970s. The high gyromagnetic ratio, large chemical shift dispersion, and complete absence of the spin 1/2 19F nucleus from biomolecules results in background-free, high-resolution 19F NMR spectra. The introduction of 19F probes in a few selected locations in biomolecules reduces spectral crowding despite its increased line width in comparison to typical 1H NMR line widths and allows rapid site-specific measurements from simple 1D spectra alone. The design and synthesis of novel 19F probes with reduced line widths and increased chemical shift sensitivity to the surrounding environment, together with advances in labeling techniques, NMR methodology, and hardware, have overcome several drawbacks of 19F NMR spectroscopy. The increased interest and widespread use of 19F NMR spectroscopy of biomolecules is gradually establishing it as a sensitive and high-resolution probe of biomolecular structure and dynamics, supplementing traditional 13C/15N-based methods. This Review focuses on the advances in 19F solution NMR spectroscopy of proteins in the past 5 years, with an emphasis on novel 19F tags and labeling techniques, NMR experiments to probe protein structure and conformational dynamics in vitro, and in-cell NMR applications.

Genetic Code Expansion for Mechanistic Studies in Ion Channels: An (Un)natural Union of Chemistry and Biology.

Ion channels play central roles in biology and human health by catalyzing the transmembrane flow of electrical charge. These proteins are ideal targets for genetic code expansion (GCE) methods because it is feasible to measure ion channel activity from miniscule amounts of protein and to analyze the resulting data via rigorous, established biophysical methods. In an ideal scenario, the encoding of synthetic, noncanonical amino acids via GCE allows the experimenter to ask questions inaccessible to traditional methods. For this reason, GCE has been successfully applied to a variety of ligand- and voltage-gated channels wherein extensive structural, functional, and pharmacological data exist. Here, we provide a comprehensive summary of GCE as applied to ion channels. We begin with an overview of the methods used to encode noncanonical amino acids in channels and then describe mechanistic studies wherein GCE was used for photochemistry (cross-linking; caged amino acids) and atomic mutagenesis (isosteric manipulation of charge and aromaticity; backbone mutation). Lastly, we cover recent advances in the encoding of fluorescent amino acids for the real-time study of protein conformational dynamics.

Quantification of CH and NH/π-Stacking Interactions in Cells Using Nuclear Magnetic Resonance Spectroscopy.

π-Stacking, a type of noncovalent interactions involving aromatic residues, plays an important role in protein folding and function. In this work, an attempt has been made to measure CH/π and NH/π stacking interactions in a protein in Escherichia coli cells using a combined double-mutant cycle and nuclear magnetic resonance spectroscopy method. The results show that the CH/π and NH/π stacking interactions are generally weaker in cells than those in the buffer. The transient intermolecular noncovalent interactions between the protein and the complex cellular environment may compete with and thus weaken the stacking interactions in the protein. The weakening of stacking interactions can enhance the local conformational opening of proteins in E. coli cells. This is evident from the faster rates of amide hydrogen/deuterium exchange observed in cells than in the buffer, for residues that undergo local conformational opening. This study highlights the influence of the cellular environment on π-stacking and the conformational dynamics of proteins.

The Unusual Functional Role of Protein Flexibility in Photosynthetic Light Harvesting: Protein Dynamics Studied Using Neutron Scattering

In addition to investigations of the three-dimensional protein structure, information on the dynamical properties of proteins is indispensable for an understanding of protein function in general. Correlations between protein dynamics and function are typically anticipated when both molecular mobility and function are concurrently affected under specific temperatures or hydration conditions. In contrast, excitation energy transfer within the major photosynthetic light-harvesting complex II (LHC II) presents an atypical case, as it remains fully operational even at cryogenic temperatures, primarily depending on the interactions between electronic states and involving harmonic protein vibrations only. This review summarizes recent work on vibrational and conformational protein dynamics of LHC II and directly relates these findings to its light-harvesting function. In addition, we give a comprehensive introduction into the use of neutron spectroscopy and molecular dynamics simulations to investigate the protein dynamics of photosynthetic protein complexes in solution, which is information complementary to that obtained by protein crystallography.

Hydrogen-Bonding and Hydrophobic Interaction Networks as Structural Determinants of Microbial Rhodopsin Function.

Microbial pump rhodopsins are highly versatile light-driven membrane proteins that couple protein conformational dynamics with ion translocation across the cell membranes. Understanding how microbial pump rhodopsins use specific amino acid residues at key functional sites to control ion selectivity and ion pumping direction is of general interest for membrane transporters, and could guide site-directed mutagenesis for optogenetics applications. To enable direct comparisons between proteins with different sequences we implement, for the first time, a unique numbering scheme for the microbial pump rhodopsin residues, NS-mrho. We use NS-mrho to show that distinct microbial pump rhodopsins typically have hydrogen-bond networks that are less conserved than anticipated from the amino acid residue conservation, whereas their hydrophobic interaction networks are largely conserved. To illustrate the role of the hydrogen-bond networks as structural elements that determine the functionality of microbial pump rhodopsins, we performed experiments, atomic-level simulations, and hydrogen bond network analyses on GR, the outward proton pump from Gloeobacter violaceus, and KR2, the outward sodium pump from Krokinobacter eikastus. The experiments indicate that multiple mutations that recover KR2 amino acid residues in GR not only fail to convert it into a sodium pump, but completely inactivate GR by abolishing photoisomerization of the retinal chromophore. This observation could be attributed to the drastically altered hydrogen-bond interaction network identified with simulations and network analyses. Taken together, our findings suggest that functional specificity could be encoded in the collective hydrogen-bond network of microbial pump rhodopsins.

Novel Insights into the Catalytic Mechanism of Collagenolysis by Zn(II)-Dependent Matrix Metalloproteinase-1.

Collagen hydrolysis, catalyzed by Zn(II)-dependent matrix metalloproteinases (MMPs), is a critical physiological process. Despite previous computational investigations into the catalytic mechanisms of MMP-mediated collagenolysis, a significant knowledge gap in understanding remains regarding the influence of conformational sampling and entropic contributions at physiological temperature on enzymatic collagenolysis. In our comprehensive multilevel computational study, employing quantum mechanics/molecular mechanics (QM/MM) metadynamics (MetD) simulations, we aimed to bridge this gap and provide valuable insights into the catalytic mechanism of MMP-1. Specifically, we compared the full enzyme-substrate complex in solution, clusters in solution, and gas-phase to elucidate insights into MMP-1-catalyzed collagenolysis. Our findings reveal significant differences in the catalytic mechanism when considering thermal effects and the dynamic evolution of the system, contrasting with conventional static potential energy surface QM/MM reaction path studies. Notably, we observed a significant stabilization of the critical tetrahedral intermediate, attributed to contributions from conformational flexibility and entropy. Moreover, we found that protonation of the scissile bond nitrogen occurs via proton transfer from a Zn(II)-coordinated hydroxide rather than from a solvent water molecule. Following C-N bond cleavage, the C-terminus remains coordinated to the catalytic Zn(II), while the N-terminus forms a hydrogen bond with a solvent water molecule. Subsequently, the release of the C-terminus is facilitated by the coordination of a water molecule. Our study underscores the pivotal role of protein conformational dynamics at physiological temperature in stabilizing the transition state of the rate-limiting step and key intermediates, compared to the corresponding reaction in solution. These fundamental insights into the mechanism of collagen degradation provide valuable guidance for the development of MMP-1-specific inhibitors.

Parsing Dynamics of Protein Backbone NH and Side-Chain Methyl Groups using Molecular Dynamics Simulations.

Experimental NMR spectroscopy and theoretical molecular dynamics (MD) simulations provide complementary insights into protein conformational dynamics and hence into biological function. The present work describes an extensive set of backbone NH and side-chain methyl group generalized order parameters for the Escherichia coli ribonuclease HI (RNH) enzyme derived from 2-μs microsecond MD simulations using the OPLS4 and AMBER-FF19SB force fields. The simulated generalized order parameters are compared with values derived from NMR 15N and 13CH2D spin relaxation measurements. The squares of the generalized order parameters, S2 for the N-H bond vector and Saxis2 for the methyl group symmetry axis, characterize the equilibrium distribution of vector orientations in a molecular frame of reference. Optimal agreement between simulated and experimental results was obtained by averaging S2 or Saxis2 calculated by dividing the simulated trajectories into 50 ns blocks (∼five times the rotational diffusion correlation time for RNH). With this procedure, the median absolute deviations (MAD) between experimental and simulated values of S2 and Saxis2 are 0.030 (NH) and 0.061 (CH3) for OPLS4 and 0.041 (NH) and 0.078 (CH3) for AMBER-FF19SB. The MAD between OPLS4 and AMBER-FF19SB are 0.021 (NH) and 0.072 (CH3). The generalized order parameters for the methyl group symmetry axis can be decomposed into contributions from backbone fluctuations, between-rotamer dihedral angle transitions, and within-rotamer dihedral angle fluctuations. Analysis of the simulation trajectories shows that (i) backbone and side chain conformational fluctuations exhibit little correlation and that (ii) fluctuations within rotamers are limited and highly uniform with values that depend on the number of dihedral angles considered. Low values of Saxis2, indicative of enhanced side-chain flexibility, result from between-rotamer transitions that can be enhanced by increased local backbone flexibility.

Constrained hidden Markov models reveal further Hsp90 protein states

Time series of conformational dynamics in proteins are usually evaluated with hidden Markov models (HMMs). This approach works well if the number of states and their connectivity is known. However, for the multi-domain protein Hsp90, a standard HMM analysis with optimization of the BIC (Bayesian information criterion) cannot explain long-lived states well. Therefore, here we employ constrained HMMs, which neglect transitions between states by including assumptions. Gradually tuning a model with justified and focused changes allows us to improve its effectiveness and the score of the BIC. This became possible by analyzing time traces with several thousand observable transitions and, therefore, superb statistics. In this scheme, we also monitor the residences in the states reconstructed by the model, aiming to find exponentially distributed dwell times. We show how introducing new states can achieve these statistics but also point out limitations, e.g. for substantial similarity of two states connected to a common neighbor. One of the states displays the lowest free energy and could be the idle open ‘waiting state’, in which Hsp90 waits for the binding of nucleotides, cochaperones, or clients.

Intrinsic Conformational Dynamics of Glycine and Alanine in Polarizable Molecular Dynamics Force Fields: Comparison to Spectroscopic Data.

Molecular dynamics (MD) is a great tool for elucidating conformational dynamics of proteins and peptides in water at the atomistic level that often surpasses the level of detail available experimentally. Structure predictions, however, are limited by the accuracy of the underlying MD force field. This limitation is particularly stark in the case of intrinsically disordered peptides and proteins, which are characterized by solvent-accessible and disordered peptide regions and domains. Recent studies show that most additive MD force fields, including CHARMM36m, do not reproduce the intrinsic conformational distributions of guest amino acid residues x in cationic GxG peptides in water in line with experimental data. Positing that a lack of polarizability in additive MD force fields may be the culprit for the reported discrepancies, we here examine the conformational dynamics of guest glycine and alanine residues in cationic GxG peptides in water using two polarizable MD force fields, CHARMM Drude and AMOEBA. Our results indicate that while AMOEBA captures the experimental data better than CHARMM Drude, neither of the two polarizable force fields offers an improvement of the Ramachandran distributions of glycine and alanine residues in cationic GGG and GAG peptides, respectively, over CHARMM36m.

Deuterium spin relaxation of fractionally deuterated ribonuclease H using paired 475 and 950MHz NMR spectrometers.

Deuterium (2H) spin relaxation of 13CH2D methyl groups has been widely applied to investigate picosecond-to-nanosecond conformational dynamics in proteins by solution-state NMR spectroscopy. The B0 dependence of the 2H spin relaxation rates is represented by a linear relationship between the spectral density function at three discrete frequencies J(0), J(ωD) and J(2ωD). In this study, the linear relation between 2H relaxation rates at B0 fields separated by a factor of two and the interpolation of rates at intermediate frequencies are combined for a more robust approach for spectral density mapping. The general usefulness of the approach is demonstrated on a fractionally deuterated (55%) and alternate 13C-12C labeled sample of E. coli RNase H. Deuterium relaxation rate constants (R1, R1ρ, RQ, RAP) were measured for 57 well-resolved 13CH2D moieties in RNase H at 1H frequencies of 475MHz, 500MHz, 900MHz, and 950MHz. The spectral density mapping of the 475/950MHz data combination was performed independently and jointly to validate the expected relationship between data recorded at B0 fields separated by a factor of two. The final analysis was performed by jointly analyzing 475/950MHz rates with 700MHz rates interpolated from 500/900MHz data to yield six J(ωD) values for each methyl peak. The J(ω) profile for each peak was fit to the original (τM, Sf2, τf) or extended model-free function (τM, Sf2, Ss2, τf, τs) to obtain optimized dynamic parameters.

Native dynamics and allosteric responses in PTP1B probed by high-resolution HDX-MS.

Protein tyrosine phosphatase 1B (PTP1B) is a validated therapeutic target for obesity, diabetes, and certain types of cancer. In particular, allosteric inhibitors hold potential for therapeutic use, but an incomplete understanding of conformational dynamics and allostery in this protein has hindered their development. Here, we interrogate solution dynamics and allosteric responses in PTP1B using high-resolution hydrogen-deuterium exchange mass spectrometry (HDX-MS), an emerging and powerful biophysical technique. Using HDX-MS, we obtain a detailed map of backbone amide exchange that serves as a proxy for the solution dynamics of apo PTP1B, revealing several flexible loops interspersed among more constrained and rigid regions within the protein structure, as well as local regions that exchange faster than expected from their secondary structure and solvent accessibility. We demonstrate that our HDX rate data obtained in solution adds value to estimates of conformational heterogeneity derived from a pseudo-ensemble constructed from ~200 crystal structures of PTP1B. Furthermore, we report HDX-MS maps for PTP1B with active-site versus allosteric small-molecule inhibitors. These maps suggest distinct and widespread effects on protein dynamics relative to the apo form, including changes in locations distal (>35 Å) from the respective ligand binding sites. These results illuminate that allosteric inhibitors of PTP1B can induce unexpected changes in dynamics that extend beyond the previously understood allosteric network. Together, our data suggest a model of BB3 allostery in PTP1B that combines conformational restriction of active-site residues with compensatory liberation of distal residues that aid in entropic balancing. Overall, our work showcases the potential of HDX-MS for elucidating aspects of protein conformational dynamics and allosteric effects of small-molecule ligands and highlights the potential of integrating HDX-MS alongside other complementary methods, such as room-temperature X-ray crystallography, NMR spectroscopy, and molecular dynamics simulations, to guide the development of new therapeutics.

Linear and Nonlinear Dielectric Response of Intrinsically Disordered Proteins.

Linear and nonlinear dielectric responses of solutions of intrinsically disordered proteins (IDPs) were analyzed by combining molecular dynamics simulations with formal theories. A large increment of the linear dielectric function over that of the solvent is found and related to large dipole moments of IDPs. The nonlinear dielectric effect (NDE) of the IDP far exceeds that of the bulk electrolyte, offering a route to interrogate protein conformational and rotational statistics and dynamics. Conformational flexibility of the IDP makes the dipole moment statistics consistent with the gamma/log-normal distributions and contributes to the NDE through the dipole moment's non-Gaussian parameter. The intrinsic non-Gaussian parameter of the dipole moment combines with the protein osmotic compressibility in the nonlinear dielectric susceptibility when dipolar correlations are screened by the electrolyte. The NDE is dominated by dipolar correlations when electrolyte screening is reduced.

Raman spectroscopy in the study of amyloid formation and phase separation.

Neurodegenerative diseases, such as Alzheimer's and Parkinson's, share a common pathological feature of amyloid structure accumulation. However, the structure-function relationship between these well-ordered, β-sheet-rich, filamentous protein deposits and disease etiology remains to be defined. Recently, an emerging hypothesis has linked phase separation, a process involved in the formation of protein condensates, to amyloid formation, suggesting that liquid protein droplets serve as loci for amyloid initiation. To elucidate how these processes contribute to disease progression, tools that can directly report on protein secondary structural changes are needed. Here, we review recent studies that have demonstrated Raman spectroscopy as a powerful vibrational technique for interrogating amyloid structures; one that offers sensitivity from the global secondary structural level to specific residues. This probe-free technique is further enhanced via coupling to a microscope, which affords structural data with spatial resolution, known as Raman spectral imaging (RSI). In vitro and in cellulo applications of RSI are discussed, highlighting studies of protein droplet aging, cellular internalization of fibrils, and Raman imaging of intracellular water. Collectively, utilization of the myriad Raman spectroscopic methods will contribute to a deeper understanding of protein conformational dynamics in the complex cellular milieu and offer potential clinical diagnostic capabilities for protein misfolding and aggregation processes in disease states.

Polyethylene Glycol Impacts Conformation and Dynamics of Escherichia coli Prolyl-tRNA Synthetase Via Crowding and Confinement Effects.

Polyethylene glycol (PEG) is a flexible, nontoxic polymer commonly used in biological and medical research, and it is generally regarded as biologically inert. PEG molecules of variable sizes are also used as crowding agents to mimic intracellular environments. A recent study with PEG crowders revealed decreased catalytic activity of Escherichia coli prolyl-tRNA synthetase (Ec ProRS), where the smaller molecular weight PEGs had the maximum impact. The molecular mechanism of the crowding effects of PEGs is not clearly understood. PEG may impact protein conformation and dynamics, thus its function. In the present study, the effects of PEG molecules of various molecular weights and concentrations on the conformation and dynamics of Ec ProRS were investigated using a combined experimental and computational approach including intrinsic tryptophan fluorescence spectroscopy, atomic force microscopy, and atomistic molecular dynamic simulations. Results of the present study suggest that lower molecular weight PEGs in the dilute regime have modest effects on the conformational dynamics of Ec ProRS but impact the catalytic function primarily via the excluded volume effect; they form large clusters blocking the active site pocket. In contrast, the larger molecular weight PEGs in dilute to semidilute regimes have a significant impact on the protein's conformational dynamics; they wrap on the protein surface through noncovalent interactions. Thus, lower-molecular-weight PEG molecules impact protein dynamics and function via crowding effects, whereas larger PEGs induce confinement effects. These results have implications for the development of inhibitors for protein targets in a crowded cellular environment.

Can Protein Structure Prediction Methods Capture Alternative Conformations of Membrane Transporters?

Understanding the conformational dynamics of proteins, such as the inward-facing (IF) and outward-facing (OF) transition observed in transporters, is vital for elucidating their functional mechanisms. Despite significant advances in protein structure prediction (PSP) over the past three decades, most efforts have been focused on single-state prediction, leaving multistate or alternative conformation prediction (ACP) relatively unexplored. This discrepancy has led to the development of highly accurate PSP methods such as AlphaFold, yet their capabilities for ACP remain limited. To investigate the performance of current PSP methods in ACP, we curated a data set, named IOMemP, consisting of 32 experimentally determined high-resolution IF and OF structures of 16 membrane proteins with substantial conformational changes. We benchmarked 12 representative PSP methods, along with two recent multistate methods based on AlphaFold, against this data set. Our findings reveal a remarkably consistent preference for specific states across various PSP methods. We elucidated how coevolution information in MSAs influences state preference. Moreover, we showed that AlphaFold, when excluding coevolution information, estimated similar energies between the experimental IF and OF conformations, indicating that the energy model learned by AlphaFold is not biased toward any particular state. Our IOMemP data set and benchmark results are anticipated to advance the development of robust ACP methods.

Ligand-induced protein transition state stabilization switches the binding pathway from conformational selection to induced fit

Protein-ligand complex formation is fundamental to biological function. A central question is whether proteins spontaneously adopt binding-competent conformations to which ligands bind conformational selection (CS) or whether ligands induce the binding-competent conformation induced fit (IF). Here, we resolve the CS and IF binding pathways by characterizing protein conformational dynamics over a wide range of ligand concentrations using NMR relaxation dispersion. We determined the relative flux through the two pathways using a four-state binding model that includes both CS and IF. Experiments conducted without ligand show that galectin-3 exchanges between the ground-state conformation and a high-energy conformation similar to the ligand-bound conformation, demonstrating that CS is a plausible pathway. Near-identical crystal structures of the apo and ligand-bound states suggest that the high-energy conformation in solution corresponds to the apo crystal structure. Stepwise additions of the ligand lactose induce progressive changes in the relaxation dispersions that we fit collectively to the four-state model, yielding all microscopic rate constants and binding affinities. The ligand affinity is higher for the bound-like conformation than for the ground state, as expected for CS. Nonetheless, the IF pathway contributes greater than 70% of the total flux even at low ligand concentrations. The higher flux through the IF pathway is explained by considerably higher rates of exchange between the two protein conformations in the ligand-associated state. Thus, the ligand acts to decrease the activation barrier between protein conformations in a manner reciprocal to enzymatic transition-state stabilization of reactions involving ligand transformation.

Activation and friction in enzymatic loop opening and closing dynamics

Protein loop dynamics have recently been recognized as central to enzymatic activity, specificity and stability. However, the factors controlling loop opening and closing kinetics have remained elusive. Here, we combine molecular dynamics simulations with string-method determination of complex reaction coordinates to elucidate the molecular mechanism and rate-limiting step for WPD-loop dynamics in the PTP1B enzyme. While protein conformational dynamics is often represented as diffusive motion hindered by solvent viscosity and internal friction, we demonstrate that loop opening and closing is activated. It is governed by torsional rearrangement around a single loop peptide group and by significant friction caused by backbone adjustments, which can dynamically trap the loop. Considering both torsional barrier and time-dependent friction, our calculated rate constants exhibit very good agreement with experimental measurements, reproducing the change in loop opening kinetics between proteins. Furthermore, we demonstrate the applicability of our results to other enzymatic loops, including the M20 DHFR loop, thereby offering prospects for loop engineering potentially leading to enhanced designs.

Sakuranetin ameliorates streptozotocin-induced diabetes in rodents by inhibiting caspase-3 activity, modulating hematological parameters, and suppressing inflammatory cytokines: a molecular docking and dynamics study

Diabetes affects people of all ages, regardless of gender and background. To date, there is no evidence for the effect of sakuranetin against the streptozotocin (STZ)-induced diabetes paradigm. The research was directed to evaluate the antidiabetic activity of sakuranetin in the STZ model invoking the diabetes-induced disease paradigm. STZ (I.P. 60 mg/kg) is directed to induce type 2 diabetes in experimental rats. Recent research pursued to regulate the anti-diabetic ability of sakuranetin at both 10 and 20 mg/kg in STZ-induced rats. Furthermore, molecular docking research was implemented to evaluate sakuranetin requisite attraction to inflammatory indicators. Various anti-diabetic [(glucose, hemoglobin A1c (HbA1c), and insulin)], lipid profile [triglycerides (TG), total cholesterol (TC), and high-density lipoproteins (HDL)], hematological parameters [Hemoglobin (HGB), packed cell volume (PCV), red blood cells (RBC), mean corpuscular volume (MCV), platelet (PLT), and white blood cells (WBC), pro-inflammatory cytokines [tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6)], antioxidant level [catalase (CAT), superoxide dismutase (SOD), glutathione (GSH)], lipid oxidation, and caspase-3 were evaluated. Furthermore, molecular docking and dynamics were performed for TNF-α (2AZ5), IL-6 (1ALU), IL-1β (6Y8M), Caspase-3 (1NME) and serum insulin (4IBM) target ligands. Sakuranetin treatment at both doses restored the biochemical parameters i.e. blood glucose, insulin, HbA1c, lipid profile, hematological parameters, pro-inflammatory markers, antioxidant levels, lipid oxidation, and caspase-3 in the context of diabetic rats. It also showed favorable binding affinity on inflammatory markers. Sakuranetin binds to proteins 2AZ5, 1ALU, 6Y8M, 1NME, and 4IBM at −7.489, −6.381, −6.742, −7.202, and −8.166 Kcal/mol, respectively. All of the findings from the molecular dynamics simulations points toward a considerable change in the conformational dynamics of protein upon binding with sakuranetin. The potential use of sakuranetin as an alternative diabetes medication will aid future research as a potent anti-diabetic agent. Communicated by Ramaswamy H. Sarma