Protein Conformational Transitions Research Articles

Biomimetic Protein Structural Transitions Regulate Activation and Inhibition of the Broad-Spectrum Bactericidal Activity of Cationic Nanoparticles

The development of cationic polymers as alternative materials to antibiotics necessitates addressing the challenge of balancing their antimicrobial activity and toxicity. Here we propose a precise switching strategy inspired by biomimetic voltage-gated ion channels, enabling controlled activation and inhibition of cationic antimicrobial functions through protein conformational transitions in diverse physiological environments. Following thermodynamic studies on the specific recognition between mannose end groups on polycations and concanavalin A (ConA), we synthesized a type of ConA-polycation nanoparticle. The nanoparticle was inhibited under neutral conditions, with cationic moieties shielded by ConA's β-sheet. This shielding suppresses their antimicrobial activity, thereby ensuring satisfactory biocompatibility. In mildly acidic environments, however, the transition of a portion of ConA to an α-helix conformation exposed cations at the particle periphery, activating antibacterial functionality. Compared to inhibited nanoparticles, those in the activated state exhibited a 32–256 times reduction in the minimum bactericidal concentration against bacteria and fungi (2−16 μg/mL). In a murine acute pulmonary infection model, intravenous administration of inhibited nanoparticles effectively reduced bacterial counts by 4-log within 12 h. The biomimetic design, regulating cationic antimicrobial functionality through the alteration in protein secondary structure, significantly retards bacterial resistance development, holding great promise for intelligent antimicrobial materials. Statement of significanceCationic antimicrobial polymers exhibit advantages distinct from antibiotics due to their lower propensity for resistance development. However, the presence of cationic moieties also poses a threat to healthy cells and tissues, significantly constraining their potential for clinical applications. To address this challenge, we propose a biomimetic strategy that mimics voltage-gated ion channels to activate the antimicrobial functionality of cations selectively in bacterial environments through the conformational transitions of proteins between β–sheets and α–helices. In healthy tissues, the antimicrobial functionality is inhibited, ensuring satisfactory biocompatibility. Antimicrobial cationic materials capable of intelligent switching between an activated state and an inhibited state in response to environmental changes offer an effective strategy to prevent the development of resistance and mitigate potential side effects.

Sampling a Rare Protein Transition Using Quantum Annealing.

Simulating spontaneous structural rearrangements in macromolecules with classical molecular dynamics is an outstanding challenge. Conventional supercomputers can access time intervals of up to tens of μs, while many key events occur on exponentially longer time scales. Path sampling techniques have the advantage of focusing the computational power on barrier-crossing trajectories, but generating uncorrelated transition paths that explore diverse conformational regions remains a problem. We employ a hybrid path-sampling paradigm that addresses this issue by generating trial transition paths using a quantum annealing (QA) machine. We first employ a classical computer to perform an uncharted exploration of the conformational space. The data set generated in this exploration is then postprocessed using a path integral-based method to yield a coarse-grained network representation of the reactive kinetics. By resorting to a quantum annealer, quantum superposition can be exploited to encode all of the transition pathways in the initial quantum state, thus potentially solving the path exploration problem. Furthermore, each QA cycle yields a completely uncorrelated trial trajectory. We previously validated this scheme on a prototypically simple transition, which could be extensively characterized on a desktop computer. Here, we scale up in complexity and perform an all-atom simulation of a protein conformational transition that occurs on the millisecond time scale, obtaining results that match those of the Anton special-purpose supercomputer. Despite limitations due to the available quantum annealers, our study highlights how realistic biomolecular simulations provide potentially impactful new ground for applying, testing, and advancing quantum technologies.

A Fresh Look at the Normal Mode Analysis of Proteins: Introducing Allosteric Co-Vibrational Modes.

We propose a new way of utilizing normal modes to study protein conformational transitions. Instead of considering individual modes independently, we show that a weighted mixture of low-frequency vibrational modes can reveal dynamic information about the conformational mechanism in more detail than any single mode can. The weights in the mixed mode, termed the allosteric covibrational mode, are determined using a simple model where the conformational transition is viewed as a perturbation of the coupled harmonic oscillator associated with either of the two conformations. We demonstrate our theory in a biologically relevant example of high pharmaceutical interest involving the V617F mutation of Janus 2 tyrosine kinase (JAK2).

Switching Go̅-Martini for Investigating Protein Conformational Transitions and Associated Protein-Lipid Interactions.

Proteins are dynamic biomolecules that can transform between different conformational states when exerting physiological functions, which is difficult to simulate using all-atom methods. Coarse-grained (CG) Go̅-like models are widely used to investigate large-scale conformational transitions, which usually adopt implicit solvent models and therefore cannot explicitly capture the interaction between proteins and surrounding molecules, such as water and lipid molecules. Here, we present a new method, named Switching Go̅-Martini, to simulate large-scale protein conformational transitions between different states, based on the switching Go̅ method and the CG Martini 3 force field. The method is straightforward and efficient, as demonstrated by the benchmarking applications for multiple protein systems, including glutamine binding protein (GlnBP), adenylate kinase (AdK), and β2-adrenergic receptor (β2AR). Moreover, by employing the Switching Go̅-Martini method, we can not only unveil the conformational transition from the E2Pi-PL state to E1 state of the type 4 P-type ATPase (P4-ATPase) flippase ATP8A1-CDC50 but also provide insights into the intricate details of lipid transport.

Exploring Free Energies of Specific Protein Conformations Using the Martini Force Field.

Coarse-grained (CG) level molecular dynamics simulations are routinely used to study various biomolecular processes. The Martini force field is currently the most widely adopted parameter set for such simulations. The functional form of this and several other CG force fields enforces secondary protein structure support by employing a variety of harmonic potentials or restraints that favor the protein's native conformation. We propose a straightforward method to calculate the energetic consequences of transitions between predefined conformational states in systems in which multiple factors can affect protein conformational equilibria. This method is designed for use within the Martini force field and involves imposing conformational transitions by linking a Martini-inherent elastic network to the coupling parameter λ. We demonstrate the applicability of our method using the example of five biomolecular systems that undergo experimentally characterized conformational transitions between well-defined structures (Staphylococcal nuclease, C-terminal segment of surfactant protein B, LAH4 peptide, and β2-adrenergic receptor) as well as between folded and unfolded states (GCN4 leucine zipper protein). The results show that the relative free energy changes associated with protein conformational transitions, which are affected by various factors, such as pH, mutations, solvent, and lipid membrane composition, are correctly reproduced. The proposed method may be a valuable tool for understanding how different conditions and modifications affect conformational equilibria in proteins.

From static to dynamic: Rapid mapping of protein conformational transitions using DeepPath

From static to dynamic: Rapid mapping of protein conformational transitions using DeepPath

Mechanism of action of the low-frequency electromagnetic field on aqueous solutions of biopolymers

This paper presents the mechanism of signal transformation by which a signal from the magnetic component of the low-frequency electromagnetic field with extremely low energy is changed into chemical and biochemical signals which elicit a biological response in aqueous solutions of biopolymers based on nucleic acids and proteins. A theoretical model developed shows that the basis of oxidative DNA damage and conformational transitions of proteins is a universal mechanism associated with a change in the amount of the most long-lived form - hydrogen peroxide in a chemical oscillator of mutual transformations of reactive oxygen species under the influence of low-intensity electromagnetic field exposure. It has been experimentally established that the quantitative content of hydrogen peroxide in solutions of biopolymers resonantly depends on the frequency of applied field. Conformational changes in proteins are accompanied by an increase in the availability and activity of the nucleophilic centers that are potential targets for reactive oxygen species. Complete unfolding and denaturation of the amino acid chain of the protein under the influence of low-frequency electromagnetic field exposure do not occur. It has been shown that enhanced hydrogen peroxide formation at 3 Hz and 50 Hz leads to oxidative modification of nitrogenous bases in DNA.

Cholesterol catalyzes unfolding in membrane-inserted motifs of the pore forming protein cytolysin A

Plasma membrane-induced protein folding and conformational transitions play a central role in cellular homeostasis. Several transmembrane proteins are folded in the complex lipid milieu to acquire a specific structure and function. Bacterial pore forming toxins (PFTs) are proteins expressed by a large class of pathogenic bacteria that exploit the plasma membrane environment to efficiently undergo secondary structure changes, oligomerize, and form transmembrane pores. Unregulated pore formation causes ion imbalance, leading to cell death and infection. Determining the free energy landscape of these membrane-driven-driven transitions remains a challenging problem. Although cholesterol recognition is required for lytic activity of several proteins in the PFT family of toxins, the regulatory role of cholesterol for the α-PFT, cytolysin A expressed by Escherichia coli remains unexplained. In a recent free energy computation, we showed that the β tongue, a critical membrane-inserted motif of the ClyA toxin, has an on-pathway partially unfolded intermediate that refolds into the helix-turn-helix motif of the pore state. To understand the molecular role played by cholesterol, we carry out string-method-based computations in membranes devoid of cholesterol, which reveals an increase of ∼30 times in the free energy barrier for the loss of β sheet secondary structure when compared with membranes containing cholesterol. Specifically, the tyrosine-cholesterol interaction was found to be critical to creating the unfolded intermediate. Cholesterol also increases the packing and hydrophobicity of the bilayer, resulting in enhanced interactions of the bound protein before complete membrane insertion. Our study illustrates that cholesterol is critical to catalyzing and stabilizing the membrane-inserted unfolded state of the β tongue motif of ClyA, opening up fresh insights into cholesterol-assisted unfolding of membrane proteins.

Observation of Protein Unfolding during pH Ramp Evoked by Lipase-Catalyzed Ester Hydrolysis.

Studies of protein folding often involve offline experimental methods such as titrating protein samples with denaturants or equilibrating them in the presence of denaturants. Here, we demonstrate an online analytical approach in which the protein structure is perturbed by a pH ramp evoked by immobilized lipase-catalyzed ester hydrolysis. Changes in the tertiary structure of the protein in response to a pH ramp (from approximately 6.3 to 2.8) are monitored using electrospray ionization mass spectrometry and spectrofluorometry. Interestingly, we discovered a side reaction of ammonium and formate leading to the production of cyanide that occurred during the ionization process. We also found that only certain protein analytes were bound to the formed cyanide species. Nevertheless, this problem was readily overcome by carefully selecting a specific ester substrate. Overall, the alterations in the charge-state distribution and fluorescence intensity─caused by the lipase-induced pH ramp─reveal conformational transitions in different proteins. In line with previous reports, the acid-induced denaturation of holo-myoglobin occurs through a two-step mechanism, which is supported by identification of protein-unfolding intermediates and the loss of noncovalent protein ligand (heme). The results─obtained using the developed catalytic method─are also consistent with the results of equilibrium-based experiments, while sample preparation steps are substantially reduced. The proposed approach simplifies the identification of the pH range that has the greatest impact on the protein structure. Thus, it has the potential to be a useful tool for studying protein conformational transitions in the course of pH changes.

High fidelity DNA strand-separation is the major specificity determinant in DNA methyltransferase CcrM's catalytic mechanism.

Strand-separation is emerging as a novel DNA recognition mechanism but the underlying mechanisms and quantitative contribution of strand-separation to fidelity remain obscure. The bacterial DNA adenine methyltransferase, CcrM, recognizes 5'GANTC'3 sequences through a DNA strand-separation mechanism with unusually high selectivity. To explore this novel recognition mechanism, we incorporated Pyrrolo-dC into cognate and noncognate DNA to monitor the kinetics of strand-separation and used tryptophan fluorescence to follow protein conformational changes. Both signals are biphasic and global fitting showed that the faster phase of DNA strand-separation was coincident with the protein conformational transition. Non-cognate sequences did not display strand-separation and methylation was reduced>300-fold, providing evidence that strand-separation is a major determinant of selectivity. Analysis of an R350A mutant showed that the enzyme conformational step can occur without strand-separation, so the two events are uncoupled. A stabilizing role for the methyl-donor (SAM) is proposed; the cofactor interacts with a critical loop which is inserted between the DNA strands, thereby stabilizing the strand-separated conformation. The results presented here are broadly applicable to the study of other N6-adenine methyltransferases that contain the structural features implicated in strand-separation, which are found widely dispersed across many bacterial phyla, including human and animal pathogens, and some Eukaryotes.

Topology Effects of Poly(2-ethyl-2-oxazoline) Brushes with Various Architectures for Antifouling Behavior under Shear Flow.

Polymer brushes with different topological architectures exhibit unparalleled interfacial and physicochemical properties and are being widely utilized in antifouling applications. However, there is an absence of a thorough understanding of the antifouling process of dynamic flow mediated by the topological structure of polymer brushes. Here, it is highlighted how the interface parameters related to biofouling in flowing carrier fluid are tuned by topologically different architectures. The mechanism by which three brushes with various topological structures (cyclic, looped, and linear brushes) encounter biological media was revealed by relating protein adhesion with nanomechanics and protein conformational transitions on poly(2-ethyl-2-oxazoline) (PEtOx) brushes. In contrast to the classically linear analogue, the cyclic PEtOx brushes confered an enhanced steric barrier and excellent lubrication at the critical density region. The impenetrable and smoother layer prevented the approach and shortened the residence time for protein on the surface, providing optimal antifouling properties at low shear rates. The looped brushes also significantly inhibited protein adhesion under prolonged high shear rates due to their unshakable conformational characteristics. These findings detailed a new evaluation framework behind polymer brushes of topology-driven biofouling repulsion under flow conditions and pointed the way toward a promising approach for the effectiveness of biomaterial design.

Molecular Dynamics Simulations of the Proteins Regulating Synaptic Vesicle Fusion

Neuronal transmitters are packaged in synaptic vesicles (SVs) and released by the fusion of SVs with the presynaptic membrane (PM). An inflow of Ca2+ into the nerve terminal triggers fusion, and the SV-associated protein Synaptotagmin 1 (Syt1) serves as a Ca2+ sensor. In preparation for fusion, SVs become attached to the PM by the SNARE protein complex, a coiled-coil bundle that exerts the force overcoming SV-PM repulsion. A cytosolic protein Complexin (Cpx) attaches to the SNARE complex and differentially regulates the evoked and spontaneous release components. It is still debated how the dynamic interactions of Syt1, SNARE proteins and Cpx lead to fusion. This problem is confounded by heterogeneity in the conformational states of the prefusion protein-lipid complex and by the lack of tools to experimentally monitor the rapid conformational transitions of the complex, which occur at a sub-millisecond scale. However, these complications can be overcome employing molecular dynamics (MDs), a computational approach that enables simulating interactions and conformational transitions of proteins and lipids. This review discusses the use of molecular dynamics for the investigation of the pre-fusion protein-lipid complex. We discuss the dynamics of the SNARE complex between lipid bilayers, as well as the interactions of Syt1 with lipids and SNARE proteins, and Cpx regulating the assembly of the SNARE complex.

Enhancement of surimi gel properties through the synergetic effect of fucoidan and oligochitosan

For the first time, two common marine-derived dietary fibres (MDFs), fucoidan (FU) and oligochitosan (OCS), were introduced as textural and nutritional enhancers in hairtail surimi gels. The MDFs could assist with inhabiting the endogenous proteolytic enzyme activity, unfolding the myosin to expose more reactive domains, inducing favorable protein conformational transition, and thus, promoting gelation. The highly hydrophilic MDFs rich in –OH groups can bind water molecules via strong hydrogen bonds, facilitating water redistribution within the gel network. Driven by the enhanced chemical forces, a stable protein-FU-OCS gel is obtained, which improves the hardness by almost 100% and the water holding capacity from 86.25% to 92.25%. Collectively, this study demonstrates that MDFs are a group of effective additives to improve gel characteristics and nutritional profiles of surimi-based seafood products. The proposed MDF-protein interaction model would guide the application of MDFs as novel additives in the food industry.

Machine learning guided sampling of protein transition pathways.

Capturing a protein conformational transition pathway is an important yet difficult task in biophysics. For example, X-ray-crystallography/cryo-EM techniques have captured open/closed states or inward/outward-facing conformations of many ion-channels/transporters; yet, it remains a challenge to experimentally capture transitioning pathways between these ground states due to their rather short-spanned nature. Multiple advanced techniques based on molecular dynamics (MD) simulations have provided great insights to fill such gaps by predicting hypothetical transition states and pathways. Such MD-based techniques, including both long equilibrium simulations and enhanced sampling ones, have provided insights to better understand how putative transition state conformations and pathways would look like. However, MD-based techniques generally take a long time; therefore, it would be of great utility to sample putative transition states along putative transition pathways more efficiently. We present a machine learning model, developed using variational autoencoder (VAE), with the goal of sampling the transition pathway between different protein's conformational states. Using VAE, which takes in protein raw trajectory coordinates generated by equilibrium MD simulations as input, the model is able to reconstruct a structurally close output. Such a VAE can therefore reduce the high-dimensional protein description in the full space into a meaningful low-dimensional representation. In this low-dimensional space, we can interpolate between the two states of interest. The interpolated pathway represents a putative transition-pathway in the higher-dimensional space, learned by VAE. After reconstruction of the sampled transition pathway into the full protein space, secondary structures, RMSDs, and other quality-control properties are used and compared with the functional mechanism of the protein. The reconstructed putative transition pathway can be used in further MD simulations. This machine learning guided MD approach will accelerate studying the full transition pathways of protein conformations by seeding good starting points generated by VAE for iterative MD simulations.

Single molecule magnetic tweezers for unfolding dynamics of Acyl-CoA binding protein

There are significant differences in mechanical stability and unfolding dynamics among proteins with different structural compositions. Compared with proteins with β-sheets and subjected to shearing forces, proteins that are composed entirely of α-helices often undergo rapid unfolding under low stretching forces, thus requiring quantitative studies by using experimental tools that can precisely control forces on a pico-Newton scale. Magnetic tweezers with intrinsic force-control capability and great stability for long-time continuous measurement are suitable to measure force-induced conformation transitions of protein subjected to low forces of several pico-Newton. Acyl-CoA binding protein (ACBP) is a model protein used to study the folding/unfolding kinetics of complete α-helices protein. It is composed of 86 amino acid residues, forming a helical bundle of four α-helices. When its N- and C-terminal are stretched, the first and last α-helix are subjected to shear force in parallel. Previous biochemical studies showed that ACBP folding and unfolding in a two-state manner. In this paper, we use magnetic tweezers to stretch ACBP from its N- and C-end and obtain the distribution of the unfolding force at different loading rates ranging from 0.25 pN/s to 4 pN/s. The most probable unfolding forces are all less than 10 pN, which confirms that ACBP is not mechanically stable. At a constant loading rate, the unfolding force distribution and the most probable unfolding force as a function of loading rate have well-defined analytical formulas based on Bell’s model. Therefore, the experimental results of unfolding force can be fitted directly to obtain the important kinetic parameter of unfolding distance which is defined as the difference in extension between the native state and the transition state. Data analysis shows that ACBP has an extraordinarily long unfolding distance of 7.8 nm. Steered molecular dynamics simulations of ACBP stretching gives the transition state with N-terminal α-helix fully unfolded and C-terminal α-helix partially unfolded, which is consistent with the long unfolding distance obtained in the experiment on magnetic tweezers. According to the simulation results, the unfolding of α-helices is less cooperative than that of β-sheet structures. This characteristic makes α-helix proteins sensitive to mechanical forces, rendering them suitable as force sensors in cells. This study shows that single-molecule stretching experiment combined with molecular dynamics simulations is a reliable method to reveal the molecular mechanism of protein conformationtransitions under stretching forces.

Monitoring In Vitro Extracellular Matrix Protein Conformations in the Presence of Biomimetic Bone-Regeneration Scaffolds Using Functionalized Gold-Edge-Coated Triangular Silver Nanoparticles.

In the cellular environment, high noise levels, such as fluctuations in biochemical reactions, protein variability, molecular diffusion, cell-to-cell contact, and pH, can both mediate and interfere with cellular functions. In this work, gold edge-coated triangular silver nanoparticles (AuTSNP) were validated as a promising new tool to indicate protein conformational transitions in cultured cells and to monitor essential protein activity in the presence of an optimized bone biomimetic chitosan-based scaffold whose rational design mimics the ECM as a natural scaffold. A chitosan-based scaffold formulation with hydroxyapatite (CS/HAp) was selected due to its promising features for orthopedic applications, including combined high mechanical strength biocompatibility and biodegradability. Functionalized AuTSNP-based tests with the model ECM protein, fibronectin (Fn), illustrate that the protein interactions can be clearly sensed over time through the local surface plasmon resonance (LSPR) technique. This demonstrates that AuTNSP are a powerful tool to detect protein conformational activity in the presence of biomimetic bone tissue regeneration scaffolds within a cellular environment that comprises a diversity of molecular cues.

The effect of heating method on the gel structures and properties of surimi prepared from Bombay duck (Harpadon nehereus).

This study investigates the effects of heating method, setting time, and setting temperature on the gel properties, water holding capacity (WHC), molecular forces, protein composition, protein conformation, and water transition of Bombay duck (BD) surimi gel. The obtained results demonstrate that the best gel properties are obtained by two-step heating at 30°C for 120 min while the hardness was 10.418 N and the breaking force was 4.52 N. Gel softening occurs at setting temperatures greater than 40°C due to the effect of endogenous enzymes in destroying the protein structure and increasing the hydrophobic and disulfide interactions. Low-field nuclear magnetic resonance spectra confirm that high two-step setting temperatures induce gel softening and the destruction of the surimi gel structure, as evidenced by the increased water migration at these temperatures. Of all protein conformations in the gel, the β-sheet structure, decreases from 38.40% at 30°C to 11.75% at 60°C when the setting time is 60 min, is the most susceptible to gel softening. Overall, the data reported herein provide a scientific basis for the development of new BD surimi products on an industrial level.

Effects of magnetic nanoscale combined radio frequency or microwave thawing on conformation of sea bass myosin heavy chain: a molecular dynamics study.

The consumption of frozen foods inevitably involves a thawing process. Protein conformation changes during a short thawing process and the quantification of their effects remains challenging. Molecular dynamics simulations can be used to evaluate the conformational changes of protein occurring in food processing. In the present study, four different thawing methods were used [i.e. magnetic nanometer combined with microwave thawing (MT-Mag), magnetic nanometer combined with radio frequency thawing (RT-Mag), radio frequency thawing (RT) and microwave thawing (MT)] to change the conformation of myosin heavy chain (MHC). The results obtained showed that, compared with the fresh sample, the hydrogen bond number and radius of gyration of the RT-Mag and RT groups were less decreased. Visual molecular dynamics STRIDE analysis showed that the content of the α helix was relatively high in the RT-Mag and MT-Mag groups. These simulation results indicate that RT-Mag can be used as an effective method for promoting the thawing process of fish and better stabilizing the protein structure. These conclusions provide a theoretical realization for understanding the protein conformational transition during the thawing process and the realization of quantification and also provide guidance for choosing better thawing conditions without loss of nutritional properties. © 2022 Society of Chemical Industry.

Direct Observation of Single-Protein Transition State Passage by Nanopore Ionic Current Jumps.

Conformational transitions of proteins are governed by chemical kinetics, often toggled by passage through an activated state separating two conformational ensembles. The passage time of a protein through the activated state can be too fast to be detected by single-molecule experiments without the aid of viscogenic agents. Here, we use high-bandwidth nanopore measurements to resolve microsecond-duration transitions that occur between conformational states of individual protein molecules partly blocking pore current. We measure the transition state passage time between folded and unfolded states of a two-state λ6-85 mutant and between metastable intermediates and the unfolded state of the multistate folder cytochrome c. Consistent with the principle of microscopic reversibility, the transition state passage time is the same for the forward and backward reactions. A passage time distribution whose tail is broader than a single exponential observed in cytochrome c suggests a multidimensional energy landscape for this protein.

Effects of oil-modified crosslinked/acetylated starches on silver carp surimi gel: Texture properties, water mobility, microstructure, and related mechanisms

This study investigated the texture properties, water mobility and microstructure of surimi gel added with crosslinked tapioca starch (CTS) and acetylated tapioca starch (ATS), and their counterparts modified with oil (Oil-CTS and Oil-ATS, respectively). Both Oil-CTS and Oil-ATS could improve the breaking force, deformation and elasticity of surimi gel, especially Oil-CTS. Additionally, oil-modified starches could increase the water-holding capacity of surimi gels and prompt the transformation of free water to bound water, resulting in the decrease of water mobility. The difference between oil-modified starches and their counterparts in gel-enhancing effect is due to the swelling ability and different microstructure of surimi/starch gels. Namely, oil-modified starches prompted the formation of a more homogeneous and compact gel network, endowing the surimi/Oil-CTS gel with tiny pores due to its restricted swelling property, while others were opposite. Raman spectral results further unveiled that the addition of oil-modified starches promoted the protein conformational transition from α-helix to β-sheet and β-turn, as well as a decrease of ionic bonds and an increase of hydrogen bonds and hydrophobic interactions of surimi gel, which were beneficial to form firm and compact gel structure. The overall results indicated the new oil-modified starches (especially Oil-CTS) have great potential to improve the quality of surimi-based products.