Interactions Of Macromolecules Research Articles

Polyphenol–Macromolecule Interactions by Isothermal Titration Calorimetry

Isothermal titration calorimetry (ITC) is a widely used and valuable technique for studying the binding interactions and the formation and dissociation of molecular complexes. ITC directly measures the energetics associated with the interactions and allows for a precise and complete thermodynamic description of association and binding processes, thereby providing an understanding of the interaction mechanisms. In this review, the role, practical aspects related to the experimental design and setup, advantages, and challenges of using ITC to evaluate polyphenol–macromolecule binding are discussed in detail. The focus is on the possibilities offered by ITC, but at the same time, its limitations are taken into account, especially in the study of complex biological processes and in the subsequent reliable determination of thermodynamic parameters. Polyphenols and proteins typically exhibit exothermic interactions, producing strong signals and distinctive titration curves that can be fitted by one- or two-site binding models; of course, there are exceptions to this. Tannins and tannin fractions usually have a high binding stoichiometry and stronger interactions with proteins than the smaller polyphenols. The driving forces behind these interactions vary, but in many cases, both hydrogen bonding and hydrophobic interactions have been reported. The interactions between polyphenols and polysaccharides or lipid bilayers have been far less studied by ITC in comparison to polyphenol–protein interactions. ITC could be utilized more extensively to study polyphenol–macromolecule interactions, as it is an excellent tool for evaluating the thermodynamic parameters of these interactions, and when used together with other techniques, ITC can also help understand how these interactions affect bioavailability, food applications, and other uses of polyphenols.

Integrative multi-omics analysis of autism spectrum disorder reveals unique microbial macromolecules interactions.

Gut microbiota alterations have been implicated in Autism Spectrum Disorder (ASD), yet the mechanisms linking these changes to ASD pathophysiology remain unclear. This study utilized a multi-omics approach to uncover mechanisms linking gut microbiota to ASD by examining microbial diversity, bacterial metaproteins, associated metabolic pathways and host proteome. The gut microbiota of 30 children with severe ASD and 30 healthy controls was analyzed. Microbial diversity was assessed using 16S rRNA V3 and V4 sequencing. A novel metaproteomics pipeline identified bacterial proteins, while untargeted metabolomics explored altered metabolic pathways. Finally, multi-omics integration was employed to connect macromolecular changes to neurodevelopmental deficits. Children with ASD exhibited significant alterations in gut microbiota, including lower diversity and richness compared to controls. Tyzzerella was uniquely associated with the ASD group. Microbial network analysis revealed rewiring and reduced stability in ASD. Major metaproteins identified were produced by Bifidobacterium and Klebsiella (e.g., xylose isomerase and NADH peroxidase). Metabolomics profiling identified neurotransmitters (e.g., glutamate, DOPAC), lipids, and amino acids capable of crossing the blood-brain barrier, potentially contributing to neurodevelopmental and immune dysregulation. Host proteome analysis revealed altered proteins, including kallikrein (KLK1) and transthyretin (TTR), involved in neuroinflammation and immune regulation. Finally, multi-omics integration supported single-omics findings and reinforced the hypothesis that gut microbiota and their macromolecular products may contribute to ASD-associated symptoms. The integration of multi-omics data provided critical evidence that alteration in gut microbiota and associated macromolecule production may play a role in ASD-related symptoms and co-morbidities. Key bacterial metaproteins and metabolites were identified as potential contributors to neurological and immune dysregulation in ASD, underscoring possible novel targets for therapeutic intervention.

A combined NMR and deep neural network approach for enhancing the spectral resolution of aromatic side chains in proteins.

Nuclear magnetic resonance (NMR) spectroscopy is an important technique for deriving the dynamics and interactions of macromolecules; however, characterizations of aromatic residues in proteins still pose a challenge. Here, we present a deep neural network (DNN), which transforms NMR spectra recorded on simple uniformly 13C-labeled samples to yield high-quality 1H-13C correlation maps of aromatic side chains. Key to the success of the DNN is the design of NMR experiments that produce data with unique features to aid the DNN produce high-resolution spectra. The methodology was validated experimentally on protein samples ranging from 7 to 40 kDa in size, where it accurately reconstructed multidimensional aromatic 1H-13C correlation maps, to facilitate 1H-13C chemical shift assignments and to quantify kinetics. More generally, we believe that the strategy of designing new NMR experiments in combination with customized DNNs represents a substantial advance that will have a major impact on the study of molecules using NMR in the years to come.

Synthesis, Characterization, and Application Prospects of Novel Soluble Polysilsesquioxane Bearing Glutarimide Side-Chain Groups.

The requirement for the development of advanced technologies is the need to create new functional thermostable soluble polysilsesquioxanes. Combining the potential of organosilicon chemistry and the chemistry of heterocyclic compounds is a promising direction for the formation of novel organosilicon polymer systems with new properties and new possibilities for their practical application. Using the classical method of hydrolysis and polycondensation of previously unknown trifunctional (trimethoxysilylpropyl)glutarimide in the presence or absence of an acid or base catalyst, a universal approach to the formation of new thermostable soluble polysilsesquioxanes with glutarimide side-chain groups is proposed, which forms the basis for the synthesis of polysilsesquioxane polymers with different functionality. The weight average molecular weight of silsesquioxanes, determined by gel permeation chromatography, is practically independent of the reaction conditions and is 10-12 kDa; at the same time, the molecular weight distribution remains low and amounts to 1.38-1.47. According to thermogravimetric analysis, the resulting polysiloxanes have high thermal stability up to 335 °C. By the dynamic light scattering method, it was established that in an aqueous solution, silsesquioxane macromolecules are in an associated state, forming supramolecular structures due to the intermolecular interaction of individual macromolecules. The average hydrodynamic diameter of the particles was 46 nm. X-ray diffraction analysis showed the amorphous nature of the polymer. Polymer film coatings based on synthesized silsesquioxanes are characterized by 98% transmission in the visible spectrum and resistance to ultraviolet radiation, which is promising for the creation of functional transparent film coatings.

Pretrainable geometric graph neural network for antibody affinity maturation

Increasing the binding affinity of an antibody to its target antigen is a crucial task in antibody therapeutics development. This paper presents a pretrainable geometric graph neural network, GearBind, and explores its potential in in silico affinity maturation. Leveraging multi-relational graph construction, multi-level geometric message passing and contrastive pretraining on mass-scale, unlabeled protein structural data, GearBind outperforms previous state-of-the-art approaches on SKEMPI and an independent test set. A powerful ensemble model based on GearBind is then derived and used to successfully enhance the binding of two antibodies with distinct formats and target antigens. ELISA EC50 values of the designed antibody mutants are decreased by up to 17 fold, and KD values by up to 6.1 fold. These promising results underscore the utility of geometric deep learning and effective pretraining in macromolecule interaction modeling tasks.

Exploring the pathways of drug repurposing and Panax ginseng treatment mechanisms in chronic heart failure: a disease module analysis perspective.

Chronic Heart Failure (CHF) is a significant global public health issue, with high mortality and morbidity rates and associated costs. Disease modules, which are collections of disease-related genes, offer an effective approach to understanding diseases from a biological network perspective. We employed the multi-Steiner tree algorithm within the NeDRex platform to extract CHF disease modules, and subsequently utilized the Trustrank algorithm to rank potential drugs for repurposing. The constructed disease module was then used to investigate the mechanism by which Panax ginseng ameliorates CHF. The active constituents of Panax ginseng were identified through a comprehensive review of the TCMSP database and relevant literature. The Swiss target prediction database was utilized to determine the action targets of these components. These targets were then cross-referenced with the CHF disease module in the STRING database to establish protein-protein interaction (PPI) relationships. Potential action pathways were uncovered through Gene Ontology (GO) and KEGG pathway enrichment analyses on the DAVID platform. Molecular docking, the determination of the interaction of biological macromolecules with their ligands, and visualization were conducted using Autodock Vina, PLIP, and PyMOL, respectively. The findings suggest that drugs such as dasatinib and mitoxantrone, which have low docking scores with key disease proteins and are reported in the literature as effective against CHF, could be promising. Key components of Panax ginseng, including ginsenoside rh4 and ginsenoside rg5, may exert their effects by targeting key proteins such as AKT1, TNF, NFKB1, among others, thereby influencing the PI3K-Akt and calcium signaling pathways. In conclusion, drugs like dasatinib and midostaurin may be suitable for CHF treatment, and Panax ginseng could potentially mitigate the progression of CHF through a multi-component-multi-target-multi-pathway approach. Disease module analysis emerges as an effective strategy for exploring drug repurposing and the mechanisms of traditional Chinese medicine in disease treatment.

Chemical and Physical Architecture of Macromolecular Gels for Fracturing Fluid Applications in the Oil and Gas Industry; Current Status, Challenges, and Prospects.

Hydraulic fracturing is vital in recovering hydrocarbons from oil and gas reservoirs. It involves injecting a fluid under high pressure into reservoir rock. A significant part of fracturing fluids is the addition of polymers that become gels or gel-like under reservoir conditions. Polymers are employed as viscosifiers and friction reducers to provide proppants in fracturing fluids as a transport medium. There are numerous systems for fracturing fluids based on macromolecules. The employment of natural and man-made linear polymers, and also, to a lesser extent, synthetic hyperbranched polymers, as additives in fracturing fluids in the past one to two decades has shown great promise in enhancing the stability of fracturing fluids under various challenging reservoir conditions. Modern innovations demonstrate the importance of developing chemical structures and properties to improve performance. Key challenges include maintaining viscosity under reservoir conditions and achieving suitable shear-thinning behavior. The physical architecture of macromolecules and novel crosslinking processes are essential in addressing these issues. The effect of macromolecule interactions on reservoir conditions is very critical in regard to efficient fluid qualities and successful fracturing operations. In future, there is the potential for ongoing studies to produce specialized macromolecular solutions for increased efficiency and sustainability in oil and gas applications.

Nucleolin lactylation contributes to intrahepatic cholangiocarcinoma pathogenesis via RNA splicing regulation of MADD

Intrahepatic cholangiocarcinoma (iCCA) is a fatal malignancy of the biliary system. The lack of a detailed understanding of oncogenic signaling or global gene expression alterations has impeded clinical iCCA diagnosis and therapy. The role of protein lactylation, a newly unraveled post-translational modification that orchestrates gene expression, remains largely elusive in the pathogenesis of iCCA. Proteomics analysis of clinical iCCA specimens and adjacent tissues was performed to screen for proteins aberrantly lactylated in iCCA. Mass spectrometry, macromolecule interaction and cell behavioral studies were employed to identify the specific lactylation sites on the candidate protein(s) and to decipher the downstream mechanisms responsible for iCCA development, which were subsequently validated using a xenograft tumor model and clinical samples. Nucleolin (NCL), the most abundant RNA-binding protein in the nucleolus, was identified as a functional lactylation target that correlates with iCCA occurrence and progression. NCL was lactylated predominantly at lysine 477 by the acyltransferase P300 in response to a hyperactivity of glycolysis, and promoted the proliferation and invasion of iCCA cells. Mechanistically, lactylated NCL bound to the primary transcript of MAP kinase-activating death domain protein (MADD) and led to efficient translation of MADD by circumventing alternative splicing that generates a premature termination codon. NCL lactylation, MADD translation and subsequent ERK activation promoted xenograft tumor growth and were associated with overall survival in patients with iCCA. NCL is lactylated to upregulate MADD through an RNA splicing-dependent mechanism, which potentiates iCCA pathogenesis via the MAPK pathway. Our findings reveal a novel link between metabolic reprogramming and canonical tumor-initiating events, and uncover biomarkers that can potentially be used for prognostic evaluation or targeted treatment of iCCA. Intrahepatic cholangiocarcinoma (iCCA) is a highly aggressive liver malignancy with largely uncharacterized pathogenetic mechanisms. Herein, we demonstrated that glycolysis promotes P300-catalyzed lactylation of nucleolin, which upregulates MAP kinase-activating death domain protein (MADD) through precise mRNA splicing and activates ERK signaling to drive iCCA development. These findings unravel a novel link between metabolic rewiring and canonical oncogenic pathways, and reveal new biomarkers for prognostic assessment and targeting of clinical iCCA.

The role of SUMO specific peptidase 3 in secondary inflammation of ischemic stroke in mice

Ischemic stroke is the main cause of death and disability, and microglia play a crucial role in the pathophysiology of hypoxic ischemic brain injury. We found that SENP3 is highly expressed in the early stages of ischemic stroke in both in vivo and in vitro mouse models, and may be related to the deSUMOylation of the key kinase MKK7 in the TLR4/p-JNK signaling pathway. Knocking down SENP3 can inhibit the deSUMOylation of MKK7, thereby inhibiting the activation of the TLR4/p-JNK signaling pathway in an in vitro stroke model. Proteomic analysis showed that SENP3 undergoes phosphorylation at the T429 site after ischemic stroke. Computer simulation predictions show a significant enhancement of the interaction between pT429-SENP3 and MKK7, which has been confirmed through experiments on the interaction of biological macromolecules (SPR). The mitochondrial metabolic abnormalities caused by energy abnormalities in the early stages of stroke provide a good explanation for the phosphorylation of SENP3. Therefore, we used the mitochondrial complex inhibitor TTFA to reverse demonstrate that the phosphorylation of SENP3 comes from the large amount of adenosine triphosphate produced by mitochondrial abnormal metabolism caused by early oxygen glucose deficiency. Finally, proteomic analysis indicates that a significant amount of oxidative phosphorylation does occur in the early stages of stroke. In summary, targeted regulation of SENP3 phosphorylation to affect the deSUMOylation of MKK7 may inhibit secondary inflammation in ischemic stroke.

Studying Macromolecular Interactions of Cellular Machines by the Combined Use of Analytical Ultracentrifugation, Light Scattering, and Fluorescence Spectroscopy Methods.

Cellular machines formed by the interaction and assembly of macromolecules are essential in many processes of the living cell. These assemblies involve homo- and hetero-associations, including protein-protein, protein-DNA, protein-RNA, and protein-polysaccharide associations, most of which are reversible. This chapter describes the use of analytical ultracentrifugation, light scattering, and fluorescence-based methods, well-established biophysical techniques, to characterize interactions leading to the formation of macromolecular complexes and their modulation in response to specific or unspecific factors. We also illustrate, with several examples taken from studies on bacterial processes, the advantages of the combined use of subsets of these techniques as orthogonal analytical methods to analyze protein oligomerization and polymerization, interactions with ligands, hetero-associations involving membrane proteins, and protein-nucleic acid complexes.

New anthracene-based Oxime-Palladium complexes loaded on albumin nanoparticles, in vitro cytotoxicity, mathematical release mechanism studies and biological macromolecules interaction investigation

In this research work, two new palladium complexes [trans-Pd(C15H10NOCH3)2]Cl2 (1) and [cis- Pd(C15H10NOCH3)(PPh3)2Cl]Cl (2) were synthesized using an alkoxyme ligand named isophethalaldoxime. Then structure characterization has been done by FT-IR and different NMR (1H, 13C and 31P) spectroscopy. Then, their interactions with biological macromolecules including deoxyribonucleic acid and bovine serum albumin were studied using various spectroscopic methods such as UV–Vis absorption, fluorescence emission spectroscopy and circular dichroism. The results showed the binding of the prepared complexes to the deoxyribonucleic acid via grooves and different binding sites of bovine serum albumin. Fluorescence emission data showed that the mechanism of extinction of albumin emission by these compounds is static. Competitive titration was performed on albumin with eosin-Y, ibuprofen and digoxin as site markers I, II and III. The antitumor activity and toxicity of these compounds were evaluated on cancer cell lines A549 (leukemia) and K562 by in-vitro cytotoxicity test. The IC50 values showed the good activity of these complexes in inhibiting cancer cells. In the last section, the release mechanism of synthesized complexes from albumin nanoparticles (BNPs) was investigated and theoretical calculations were performed that showed Korsmeyer-Peppas mechanism for complex (1) and Quadratic mechanism for complex (2).

Engineered molecular sensors for quantifying cell surface crowding

Cells mediate interactions with the extracellular environment through a crowded assembly of transmembrane proteins, glycoproteins and glycolipids on their plasma membrane. The extent to which surface crowding modulates the biophysical interactions of ligands, receptors, and other macromolecules is poorly understood due to the lack of methods to quantify surface crowding on native cell membranes. In this work, we demonstrate that physical crowding on reconstituted membranes and live cell surfaces attenuates the effective binding affinity of macromolecules such as IgG antibodies in a surface crowding-dependent manner. We combine experiment and simulation to design a crowding sensor based on this principle that provides a quantitative readout of cell surface crowding. Our measurements reveal that surface crowding decreases IgG antibody binding by 2 to 20 fold in live cells compared to a bare membrane surface. Our sensors show that sialic acid, a negatively charged monosaccharide, contributes disproportionately to red blood cell surface crowding via electrostatic repulsion, despite occupying only ~1% of the total cell membrane by mass. We also observe significant differences in surface crowding for different cell types and find that expression of single oncogenes can both increase and decrease crowding, suggesting that surface crowding may be an indicator of both cell type and state. Our high-throughput, single-cell measurement of cell surface crowding may be combined with functional assays to enable further biophysical dissection of the cell surfaceome.

Macromolecular Modification Strategies for Biomaterial Surface: Challenges in Fundamental Research and Applications

Over the past few decades, macromolecular surface modification technologies have rapidly evolved as a key driver of biomaterial innovation. The successful application of these technologies relies on the fundamental knowledge on the interaction of macromolecules with biomaterial surfaces; among them, protein and cell-surface interaction is one of the central issues. Besides, innovations in macromolecular surface initiation and characterization methods have also played a key role. Despite the progress, it is an inescapable fact that many excellent macromolecular modification techniques remain at the laboratory stage. In particular, some of these techniques are disconnected from the standards and requirements of practical applications. On top of that, the characterization of surfaces remains difficult so that the full mastery of macromolecules information on surfaces is still pending. In this Perspective, we share with classic examples of macromolecules and biomaterials surface research to summarize some instructive conclusions and real challenges in fundamental research and application of macromolecular modification strategies for biomaterial surfaces.

Ion-Specific Water–Macromolecule Interactions at the Air/Aqueous Interface: An Insight into Hofmeister Effect

The specificity of ions in inducing conformational changes in macromolecules is introduced as the Hofmeister series; however, the detailed underlying mechanism is not comprehensible yet. We utilized surface-specific sum frequency generation (SFG) vibrational spectroscopy to explore the Hofmeister effect at the air/polyvinylpyrrolidone (PVP)/water interface. The spectral signature observed from the ssp polarization scheme reveals ion-specific ordering of water molecules following the Hofmeister series attributed to the ion-macromolecule interactions. Along with this, the presence of ions does not reflect any significant influence on the structure of the PVP macromolecule. However, the ppp-SFG spectra in the CH-stretch region reveal the impact of ions on the orientation angle of vinyl chain CH2-groups, which follows the Hofmeister series: SO42- > Cl- > NO3- > Br- > ClO4- > SCN-. The minimal orientation angle of CH2-groups indicates significant reordering in PVP vinyl chains in the presence of chaotropic anions ClO4-, and SCN-. The observation is attributed to the ion-specific water-macromolecule interactions at the air/aqueous interface. It is compelling to observe the signature of spectral blue shifts in the OH-stretch region in the ppp configuration in the presence of chaotropic anions. The origin of spectral blue shifts has been ascribed to the existence of weaker interactions between the interfacial water molecules and the backbone CH- and CH2-moieties of the PVP macromolecules. The ion-specific modulation in water-macromolecule interactions is endorsed by the relative propensity of anion's adsorption toward the air/aqueous interface. The experimental findings highlight the existence and cooperative participation of ion-specific water-macromolecule interactions in the mechanism of the Hofmeister effect, along with the illustrious ion-water and ion-macromolecule interactions.

High-throughput single-molecule localization microscopy: Potential clinical applications.

High-throughput single-molecule localization microscopy: Potential clinical applications.

Multiscale modeling of complex fluids under SAOS and LAOS using a combined FENE transient network model

The multiscale modeling of complex fluids under small and large amplitude oscillatory shear flow using non-linear kinetic and transient network models is presented. The kinetics of microstates is analogous to chemical kinetics, which defines the physical macromolecule interaction in a Newtonian fluid, and the concentration of microstates defines a variable maximum length of extension for each microstate. The effect of important parameters like viscosity ratio, chain length, viscoelasticity, kinetic rate constants, for different initial entanglement scenarios (entangled, disentangled and aleatory) are analyzed. The Lissajous curves for the shear stress and the first normal stress difference versus the instantaneous strain or strain-rate are shown. The self-intersection of the Lissajous curves or secondary loops is shown to depend on the kinetic rate constants, the maximum extension length, and the elasticity.

Synergistic Antitumor Potency of a Self-Assembling Cyclodextrin Nanoplex for the Co-Delivery of 5-Fluorouracil and Interleukin-2 in the Treatment of Colorectal Cancer

Chemotherapy is the most used method after surgery in the treatment of colon cancer. Cancer cells escape the recognition mechanism of immune system cells to survive and develop chemoresistance. Therefore, the use of immunotherapy in combination with chemotherapy can increase the effectiveness of the treatment. Nanoparticles have been used clinically to increase the accumulation of therapeutics in target tissues and reduce toxicity. In this paper, nanoplexes were formed via cationic cyclodextrin polymer, 5-Fluorouracil, and Interleukin-2 based on the opposite charge interaction of macromolecules without undergoing any structural changes or losing the biological activity of Interleukin-2. Anticancer activities of nanoplexes were determined in two-dimensional and three-dimensional cell culture setups. The dual drug-loaded cyclodextrin nanoplexes diffused deeper into the spheroids and accelerated apoptosis when compared with 5-FU solutions. In the colorectal tumor-bearing animal model, survival rate, antitumor activity, metastasis, and immune response parameters were assessed using a cyclodextrin derivative, which was found to be safe based on the ALT/AST levels in healthy mice. Histomorphometric analysis showed that the groups treated with the nanoplex formulation had significantly fewer initial tumors and lung foci when compared with the control. The dual drug-loaded nanoplex could be a promising drug delivery technique in the immunochemotherapy of colorectal cancer.

Solvent/non-solvent-based approach in MAPLE deposition of EVA coatings

A new approach to target preparation was applied for MAPLE deposition of poly(ethylene-co-vinyl acetate) (EVA) coatings. By adding a non-solvent (acetone) to EVA-chloroform solution, an almost threefold increase in the deposition efficiency was achieved and semicrystalline coatings with a modified surface morphology and high preservation of chemical structure were obtained. The chemical structure of the coatings was determined using IR and XPS techniques, the morphology and topography were characterized by AFM, SEM, XRD and profilometry. It is postulated that the addition of a non-solvent to the solvent mixture improves the spatial conformation of high molecular weight polymer chains, leading to lower entanglement and lower tendency to form larger clusters that have a detrimental effect on the coating morphology and composition. This hypothesis is supported by analysis of the rheological properties of the solutions. A change in the spatial conformation and physical interactions of EVA macromolecules was evaluated by viscosity and dynamic light scattering (DLS) measurements. The approach proposed can be applied to all oligomeric and polymeric materials to diminish the viscosity and entanglement of molecules to increase the deposition efficiency and represents an important step in the scaling-up of the MAPLE process.

Molecular and Macromolecular Interactions of Carbon-Based Nanostructures

The interactions of molecules and macromolecules with carbon nanostructures such as carbon dots, carbon nanotubes, graphene, graphene oxide, and fullerenes, have been stimulating the interest of the researchers working on the preparation, functionalization, properties and applications of carbon-based nanomaterials [...].

STABILITY OF OMEGA-3 COMPOUNDS COMPLEX WITH PPAR-γ RECEPTOR AS AN ANTI-OBESITY USING MOLECULAR DYNAMIC SIMULATION

Objective: Obesity is a major contributor to comorbid diseases based on low grade chronic inflammation. Omega-3 fatty acids have a role in inflammation so it is thought to prevent obesity. This study was conducted to analyze the stability of omega-3 fatty acids with the PPAR-γ receptor using molecular dynamic simulation to investigate the relationship of macromolecule interactions to biologically relevant as an obesity comorbid.
 Methods: The methods consisted of ligand acquisition, molecular dynamic simulation, and analysis of dynamic molecular results using Gromacs 2016.3 software and the results of the MD analysis were carried out by simulating time with VMD software and graphing the results of MD data analysis using Microsoft Excel.
 Results: The result showed that docosahexaenoic acid (DHA), docosapentaenoic acid (DPA), and heneicosapentaenoic acid (HPA) have good stability. Average RMSD values of DHA, DPA, and HPA were 0.347 Å, 0.464 Å, and 0.706 Å with similar pattern of fluctuation across the region. DHA forms a hydrogen bond to Tyr347 and Leu343. Meanwhile, DPA binds to Asn52 and HPA bind to Arg213. DHA, DPA, and HPA have an average SASA of 233.91 nm2, 231.47 nm2, and 225.52 nm2, respectively. DHA has the lowest total binding energy (-129.914 kJ/mol) compared to DPA (-102.018 kJ/mol) and HPA (-115.992 kJ/mol).
 Conclusion: Based on the molecular dynamics simulation approach, omega-3 compounds, DHA, DPA, and HPA showed that DHA has good stability compared to DPA and HPA. DHA, DPA, and HPA can be used as lead drugs to bind to PPAR-γ receptors to prevent and treat obesity.