This study presents the initial structural model of L-haloacid dehalogenase (DehLBHS1) from Bacillus megaterium BHS1, an alkalotolerant bacterium known for its ability to degrade halogenated environmental pollutants. The model provides insights into the structural features of DehLBHS1 and expands our understanding of the enzymatic mechanisms involved in the degradation of these hazardous pollutants. Key amino acid residues (Arg40, Phe59, Asn118, Asn176, and Trp178) in DehLBHS1 were identified to play critical roles in catalysis and molecular recognition of haloalkanoic acid, essential for efficient binding and transformation of haloalkanoic acid molecules. DehLBHS1 was modeled using I-TASSER, yielding a best TM-score of 0.986 and an RMSD of 0.53 Å. Validation of the model using PROCHECK revealed that 89.2% of the residues were located in the most favored region, providing confidence in its structural accuracy. Molecular docking simulations showed that the non-simulated DehLBHS1 preferred 2,2DCP over other substrates, forming one hydrogen bond with Arg40 and exhibiting a minimum energy of -2.5 kJ/mol. The simulated DehLBHS1 exhibited a minimum energy of -4.3 kJ/mol and formed four hydrogen bonds with Arg40, Asn176, Asp9, and Tyr11, further confirming the preference for 2,2DCP. Molecular dynamics simulations supported this preference, based on various metrics, including RMSD, RMSF, gyration, hydrogen bonding, and molecular distance. MM-PBSA calculations showed that the DehLBHS1-2,2-DCP complex had a markedly lower binding energy (-21.363 ± 1.26 kcal/mol) than the DehLBHS1-3CP complex (-14.327 ± 1.738 kcal/mol). This finding has important implications for the substrate specificity and catalytic function of DehLBHS1, particularly in the bioremediation of 2,2-DCP in contaminated alkaline environments. These results provide a detailed view of the molecular interactions between the enzyme and its substrate and may aid in the development of more efficient biocatalytic strategies for the degradation of halogenated compounds.Communicated by Ramaswamy H. Sarma.
Genomic surveillance is crucial for tracking emergence and spread of novel variants of pathogens, such as SARS-CoV-2, to inform public health interventions and to enforce control measures. However, in some settings especially in low- and middle- income counties, where sequencing platforms are limited, only certain patients get to be selected for sequencing surveillance. Here, we show that patients with multiple comorbidities potentially harbour SARS-CoV-2 with higher mutation rates and thus deserve more attention for genomic surveillance. The relationship between the patient comorbidities, and type of amino acid mutations was assessed. Correlation analysis showed that there was a significant tendency for mutations to occur within the ORF1a region for patients with higher number of comorbidities. Frequency analysis of the amino acid substitution within ORF1a showed that nsp3 P822L of the PLpro protease was one of the highest occurring mutations. Using molecular dynamics, we simulated that the P822L mutation in PLpro represents a system with lower Root Mean Square Deviation (RMSD) fluctuations, and consistent Radius of gyration (Rg), Solvent Accessible Surface Area (SASA) values-indicate a much stabler protein than the wildtype. The outcome of this study will help determine the relationship between the clinical status of a patient and the mutations of the infecting SARS-CoV-2 virus.
Immobilized lipases were applied to the enzymatic conversion of oils from spent coffee ground into biodiesel. Two lipases were selected for the study because of their conformational behavior analysed by Molecular Dynamics (MD) simulations taking into account that immobilization conditions affect conformational behavior of the lipases and ultimately, their efficiency upon immobilization. The enzymatic synthesis of biodiesel was initially carried out on a model substrate (triolein) in order to select the most promising immobilized biocatalysts. The results indicate that oils can be converted quantitatively within hours. The role of the nature of the immobilization support emerged as a key factor affecting reaction rate, most probably because of partition and mass transfer barriers occurring with hydrophilic solid supports. Finally, oil from spent coffee ground was transformed into biodiesel with yields ranging from 55% to 72%. The synthesis is of particular interest in the perspective of developing sustainable processes for the production of bio-fuels from food wastes and renewable materials. The enzymatic synthesis of biodiesel is carried out under mild conditions, with stoichiometric amounts of substrates (oil and methanol) and the removal of free fatty acids is not required.
Ensemble docking can be a successful virtual screening technique that addresses the innate conformational heterogeneity of macromolecular drug targets. Yet, lacking a method to identify a subset of conformational states that effectively segregates active and inactive small molecules, ensemble docking may result in the recommendation of a large number of false positives. Here, three knowledge-based methods that construct structural ensembles for virtual screening are presented. Each method selects ensembles by optimizing an objective function calculated using the receiver operating characteristic (ROC) curve: either the area under the ROC curve (AUC) or a ROC enrichment factor (EF). As the number of receptor conformations, N, becomes large, the methods differ in their asymptotic scaling. Given a set of small molecules with known activities and a collection of target conformations, the most resource intense method is guaranteed to find the optimal ensemble but scales as O(2(N)). A recursive approximation to the optimal solution scales as O(N(2)), and a more severe approximation leads to a faster method that scales linearly, O(N). The techniques are generally applicable to any system, and we demonstrate their effectiveness on the androgen nuclear hormone receptor (AR), cyclin-dependent kinase 2 (CDK2), and the peroxisome proliferator-activated receptor δ (PPAR-δ) drug targets. Conformations that consisted of a crystal structure and molecular dynamics simulation cluster centroids were used to form AR and CDK2 ensembles. Multiple available crystal structures were used to form PPAR-δ ensembles. For each target, we show that the three methods perform similarly to one another on both the training and test sets.
Benzimidazole analogs 1-27 were synthesized, characterized by EI-MS and (1)HNMR and their α-glucosidase inhibitory activities were found out experimentally. Compound 25, 19, 10 and 20 have best inhibitory activities with IC50 values 5.30±0.10, 16.10±0.10, 25.36±0.14 and 29.75±0.19 respectively against α-glucosidase. Compound 6 and 12 has no inhibitory activity against α-glucosidase enzyme among the series. Further studies showed that the compounds are not showing any cytotoxicity effect. The docking studies of the compounds as well as the experimental activities of the compounds correlated well. From the molecular docking studies, it was observed that the top ranked conformation of all the compounds fit well in the active site of the homology model of α-glucosidase.
Material designs that use donor and acceptor units are often found in organic optoelectronic devices. Molecular level insight into the interactions between donors and acceptors are crucial for understanding how such interactions can modify the optical properties of the organic optoelectronic materials. In this paper, tris(4-(tert-butyl)phenyl)amine (pTPA) was synthesized as a donor in order to compare with unmodified triphenylamine (TPA) in a donor-acceptor system by having 2,4,6-triphenyl-1,3,5-triazine (TRZ) as an acceptor. Dimerization of donors and acceptors occurred in solvent when the concentration of solute is high. At 0 K, using a polarizable continuum model, the nitrogen atom of TPA is found to stack on top of the center of triazine of TRZ, whereas such alignment is offset in pTPA and TRZ. We attributed such alignment in TPA-TRZ as the result of attractive interactions between partial localization of 2pz electrons at the nitrogen atom of TPA and the π deficiency of triazine in TPA-TRZ. By taking into account random motions of the solvent effect at 300 K in quantum molecular dynamics and classical molecular dynamics simulations to interpret the marked difference in emission spectra between TPA-TRZ and pTPA-TRZ, it was revealed that the attractive interaction between pTPA and TRZ in toluene is weaker than TPA and TRZ. Because of the weaker attractive interaction between pTPA and TRZ in toluene, the dimers adopted numerous ground state conformations resulting in broad emission bands superimposed with multiple small Gaussian peaks. This is in contrast to TPA-TRZ which has only one dominant dimer conformation. This study demonstrates that the strength of intermolecular interactions between donors and acceptors should be taken into consideration in designing supramolecular structures.
One of the techniques to increase oil recovery from hydrocarbon reservoirs is the injection of low salinity water. It is shown that the injection of low salinity water changes the wettability of the rock. However, there are argumentative debates concerning low salinity water effect on changing the wettability of the oil/brine/rock system in the oil reservoirs. In this regard, molecular dynamics simulation (MDS) as a tool to simulate the phenomena at the molecular level has been used for more than a decade. In this study, the Zisman plot (presented by KRUSS Company) was simulated through MDS, and then, contact angle experiments for n-decane interactions on the Bentheimer substrate in the presence of different concentrations of sodium ions were conducted. MDS was then used to simulate experiments and understand the wettability trend based on free-energy calculations. Hereafter, a new model was developed in this study to correlate free energies with contact angles. The developed model predicted the experimental results with high accuracy (R2 ∼ 0.98). A direct relation was observed between free energy and water contact angle. In contrast, an inverse relation was noticed between the ion concentration and the contact angle such that an increase in the ion concentration resulted in a decrease in the contact angle and vice versa. In other terms, increasing brine ionic concentrations in the presence of n-decane is linked to a decrease in free energies and an increase in the wetting state of a sandstone. The comparison between the developed model's predicted contact angles and experimental observations showed a maximum deviation of 14.32%, which is in satisfactory agreement to conclude that MDS can be used as a valuable and economical tool to understand the wettability alteration process.
The sigma-E transcription factor (σETF) can be found in most of the bacteria cells including Bacillus thuringiensis. However, the cellular regulatory mechanisms of these transcription factors in the mass production of δ-endotoxins during sporulation stage are yet to be revealed. In addition, the recognition of DNA towards σETF DNA binding motifs that led to the transcription activities is also being poorly studied. Therefore, this work studied the possible DNA binding motifs of σETF by utilising in silico approaches. The structure of σETF was first built via three different computational methods. A cognate DNA sequence was then docked to the predicted σETF DNA-binding motifs. The binding free energy calculated using molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) for triplicate 50 ns simulation of σETF-DNA complex revealed favourable binding energy of DNA to σETF (average ∆Gbind = -34.57 kcal/mol) mainly driven by non-polar interactions. This study revealed that σETF LYS131, ARG133, PHE138, TRP146, ARG222, LYS225 and ARG226 are most likely the key residues upon the binding and recognition of DNA prior to transcription actives. Since determination of genome-regulating protein which recognises specific DNA sequence is important to discriminate between the proteins preferences for different genes, this study might provide some understanding on the possible σETF-DNA recognition prior to transcription initiated for the δ-endotoxins production.
While the economy is rapidly expanding in most emerging countries, issues coupled with a higher population has created foreseeable tension among food, water, and energy. It is crucial for more sustainable valorization of resources, for instance, nanocellulose, to address the core challenges in environmental sustainability. As the complexity of the system evolved, the timescale of project development has increased exponentially. However, research on the design and operation of integrated nanomaterials, along with energy supply, monitoring, and control infrastructure, has seriously lagged. The development cost of new materials can be significantly reduced by utilizing molecular simulation technology in the design of nanostructured materials. To realize its potential, nanocellulose, an amphiphilic biopolymer with the presence of rich -OH and -CH structural groups, was investigated via molecular dynamics simulation to reveal its full potential as Pickering emulsion stabilizer at the molecular level. This work has successfully quantified the Pickering stabilization mechanism profiles by nanocellulose, and the phenomenon could be visualized in three stages, namely the initial homogenous phase, rapid formation of micelles and coalescence, and lastly the thermodynamic equilibrium of the system. It was also observed that the high bead order was always coupled with a high volume of phase separation activities, through a coarse-grained model within 20,000 time steps. The outcome of this work would be helpful to provide an important perspective for the future design and development of nanocellulose-based emulsion products, which cater for food, cosmeceutical, and pharmaceutical industries.
Alkaline-stable lipases are highly valuable biocatalysts that catalyze reactions under highly basic conditions. Herein, computational predictions of lipase from Acinetobacter haemolyticus and its mutant, Mut-LipKV1 was performed to identify functionally relevant mutations that enhance pH performance under increasing basicity. Mut-LipKV1 was constructed by in silico site directed mutagenesis of several outer loop acidic residues, aspartic acid (Asp) into basic ones, lysine (Lys) at positions 51, 122 and 247, followed by simulation under extreme pH conditions (pH 8.0-pH 12.0). The energy minimized Mut-LipKV1 model exhibited good quality as shown by PROCHECK, ERRAT and Verify3D data that corresponded to 79.2, 88.82 and 89.42% in comparison to 75.2, 86.15, and 95.19% in the wild-type. Electrostatic surface potentials and charge distributions of the Mut-LipKV1 model was more stable and better adapted to conditions of elevated pHs (pH 8.0 - 10.0). Mut-LipKV1 exhibited a mixture of neutral and positive surface charge distribution compared to the predominantly negative charge in the wild-type lipase at pH 8.0. Data of molecular dynamics simulations also supported the increased alkaline-stability of Mut-LipKV1, wherein the lipase was more stable at a higher pH 9.0 (RMSD = ∼0.3 nm, RMSF = ∼0.05-0.2 nm), over the optimal pH 8.0 of the wild-type lipase (RMSD = 0.3 nm, RMSF = 0.05-0.20 nm). Thus, the adaptive strategy of replacing surface aspartic acid to lysine in lipase was successful in yielding a more alkaline-stable Mut-LipKV1 under elevated basic conditions.Communicated by Ramaswamy H. Sarma.
We have further developed the two-brains hypothesis as a form of complementarity (or complementary relationship) of endogenously induced weak magnetic fields in the electromagnetic brain. The locally induced magnetic field between electron magnetic dipole moments of delocalized electron clouds in neuronal domains is complementary to the exogenous electromagnetic waves created by the oscillating molecular dipoles in the electro-ionic brain. In this paper, we mathematically model the operation of the electromagnetic grid, especially in regard to the functional role of atomic orbitals of dipole-bound delocalized electrons. A quantum molecular dynamic approach under quantum equilibrium conditions is taken to illustrate phase differences between quasi-free electrons tethered to an oscillating molecular core. We use a simplified version of the many-body problem to analytically solve the macro-quantum wave equation (equivalent to the Kohn-Sham equation). The resultant solution for the mechanical angular momentum can be used to approximate the molecular orbital of the dipole-bound delocalized electrons. In addition to non-adiabatic motion of the molecular core, 'guidance waves' may contribute to the delocalized macro-quantum wave functions in generating nonlocal phase correlations. The intrinsic magnetic properties of the origins of the endogenous electromagnetic field are considered to be a nested hierarchy of electromagnetic fields that may also include electromagnetic patterns in three-dimensional space. The coupling between the two-brains may involve an 'anticipatory affect' based on the conceptualization of anticipation as potentiality, arising either from the macro-quantum potential energy or from the electrostatic effects of residual charges in the quantum and classical subsystems of the two-brains that occurs through partitioning of the potential energy of the combined quantum molecular dynamic system.
Literature has shown that oil palm leaves (OPL) can be transformed into nanocellulose (NC) by fungal lignocellulosic enzymes, particularly those produced by the Trichoderma species. However, mechanism of β-glucosidase and xylanase selectivity to degrade lignin, hemicellulose and cellulose in OPL for NC production remains relatively vague. The study aimed to comprehend this aspect by an in silico approach of molecular docking, molecular dynamics (MD) simulation and Molecular-mechanics Poisson-Boltzmann surface area (MM-PBSA) analysis, to compare interactions between the β-glucosidase- and xylanase from Trichoderma asperellum UC1 in complex with each substrate. Molecular docking of the enzyme-substrate complex showed residues Glu165-Asp226-Glu423 and Arg155-Glu210-Ser160 being the likely catalytic residues of β-glucosidase and xylanase, respectively. The binding affinity of β-glucosidase for the substrates are as follows: cellulose (-8.1 kcal mol-1) > lignin (-7.9 kcal mol-1) > hemicellulose (-7.8 kcal mol-1), whereas, xylanase showed a corresponding preference for; hemicellulose (-6.7 kcal mol-1) > cellulose (-5.8 kcal mol-1) > lignin (-5.7 kcal mol-1). Selectivity of both enzymes was reiterated by MD simulations where interactions between β-glucosidase-cellulose and xylanase-hemicellulose were the strongest. Notably low free-binding energy (ΔGbind) of β-glucosidase and xylanase in complex with cellulose (-207.23 +/- 47.13 kJ/mol) and hemicellulose (-131.48 +/- 24.57 kJ/mol) were observed, respectively. The findings thus successfully identified the cellulose component selectivity of the polymer-acting β-glucosidase and xylanase of T. asperellum UC1.Communicated by Ramaswamy H. Sarma.
Protein function depends greatly on its structure. Based on this principle, it is vital to study the
protein structure in order to understand its function. This study attempts to build the predicted
model of lipase gene in Rhodococcus sp. NAM81 using homology modelling method. The
predicted structure was then used to investigate the function of protein through several
bioinformatic tools. The DNA sequence of lipase gene was obtained from the Rhodococcus sp.
NAM81 genome scaffold. Blastx analysis showed 100% identity to the target enzyme andthe
appropriate template for homology modelling was determined using Blastp analysis. The 3D
protein structure was built using two homology modelling software, EsyPred3D and Swiss
Model Server. Both structures built obtained LGScore of greater than 4, which means they are
extremely good models according to ProQ validation criteria. Both structures also satisfied the
Ramachandran plot structure validation analysis. The predicted structures were 100% matched
with each other when superimposed with DaliLite pairwise. This shows that both structure
validation servers agreed on the same model. Structure analysis using ProFunc had found seven
motifs and active sites that indicate similar function of this protein with other known proteins.
Thus, this study has successfully produced a good 3D protein structure for the target enzyme.
A new series of novel triclosan (2,4,4'-trichloro-2'-hydroxydiphenylether) analogues were designed, synthesized, and screened for their in vitro antimycobacterial and antibacterial activities. Most of the compounds showed significant activity against Mycobacterium tuberculosis H37Rv strain with minimum inhibitory concentration (MIC) values in 20-40 μM range in GAST/Fe medium when compared with triclosan (43 μM) in the first week of assay, and after additional incubation, seven compounds, that is, 2a, 2c, 2g, 2h, 2i, 2j, and 2m, exhibited MIC values at the concentration of 20-40 μM. The compounds also showed more significant activity against Bacillus subtilis and Staphylococcus aureus. The synthesized compounds showed druggable properties, and the predicted ADME (absorption, distribution, metabolism, and excretion) properties were within the acceptable limits. The in silico studies predicted better interactions of compounds with target protein residues and a higher dock score in comparison with triclosan. Molecular dynamics simulation study of the most active compound 2i was performed in order to further explore the stability of the protein-ligand complex and the protein-ligand interaction in detail.
This study aimed to investigate the transport mechanisms of ions during forward-osmosis-driven (FO-driven) dewatering of microalgae using molecular dynamics (MD) simulations. The dynamical and structural properties of ions in FO systems of varying NaCl or MgCl2 draw solution (DS) concentrations were calculated and correlated. Results indicate that FO systems with higher DS concentration caused ions to have lower hydration numbers and higher coordination numbers leading to lower diffusion coefficients. The higher hydration number of Mg2+ ions resulted in significantly lower ionic permeability as compared to Na+ ions at all concentrations (p = 0.002). The simulations also revealed that higher DS concentrations led to higher accumulation of ions in the membrane. This study provides insights on the proper selection of DS for FO systems.
Wax appearance temperature (WAT), defined as the temperature at which the first solid paraffin crystal appears in a crude oil, is one of the key flow assurance indicators in the oil industry. Although there are several commonly-used experimental techniques to determine WAT, none provides unambiguous molecular-level information to characterize the phase transition between the homogeneous fluid and the underlying solid phase. Molecular Dynamics (MD) simulations employing the statistical associating fluid theory (SAFT) force field are used to interrogate the incipient solidification states of models for long-chain alkanes cooled from a melt to an arrested state. We monitor the phase change of pure long chain n-alkanes: tetracosane (C24H50) and triacontane (C30H62), and an 8-component surrogate n-alkane mixture (C12-C33) built upon the compositional information of a waxy crude. Comparison to Diffusion Ordered Spectroscopy Nuclear Magnetic Resonance (DOSY NMR) results allows the assessment of the limitations of the coarse-grained models proposed. We show that upon approach to freezing, the heavier components restrict their motion first while the lighter ones retain their mobility and help fluidize the mixture. We further demonstrate that upon sub-cooling of long n-alkane fluids and mixtures, a discontinuity arises in the slope of the self-diffusion coefficient with decreasing temperature, which can be employed as a marker for the appearance of an arrested state commensurate with conventional WAT measurements.
The manifestation of class D β-lactamases in the community raises significant concern as they can hydrolyze carbapenem antibiotics. Hence, it is exceptionally alluring to design novel inhibitors. Structure-based virtual screening using docking programs and molecular dynamics simulations was employed to identify two novel non-β-lactam compounds that possess the ability to block different OXA variants. Furthermore, the presence of a nonpolar aliphatic amino acid, valine, near the active site serine, was identified in all OXA variants that can be accounted to block the catalytic activity of OXA enzymes.
Medicinal plants as rich sources of bioactive compounds are now being explored for drug development against COVID-19. 19 medicinal plants known to exhibit antiviral and anti-inflammatory effects were manually curated, procuring a library of 521 metabolites; this was virtually screened against NSP9, including some other viral and host targets and were evaluated for polypharmacological indications. Leads were identified via rigorous scoring thresholds and ADMET filtering. MM-GBSA calculation was deployed to select NSP9-Lead complexes and the complexes were evaluated for their stability and protein-ligand communication via MD simulation. We identified 5 phytochemical leads for NSP9, 23 for Furin, 18 for ORF3a, and 19 for IL-6. Ochnaflavone and Licoflavone B, obtained from Lonicera japonica (Japanese Honeysuckle) and Glycyrrhiza glabra (Licorice), respectively, were identified to have the highest potential polypharmacological properties for the aforementioned targets and may act on multiple pathways simultaneously to inhibit viral entry, replication, and disease progression. Additionally, MD simulation supports the robust stability of Ochnaflavone and Licoflavone B against NSP9 at the active sites via hydrophobic interactions, H-bonding, and H-bonding facilitated by water. This study promotes the initiation of further experimental analysis of natural product-based anti-COVID-19 therapeutics.
Increased scientific interest has led to the rise in biotechnological uses of halophilic and halotolerant microbes for hypersaline wastewater bioremediation. Hence, this study performed molecular docking, molecular dynamic (MD) simulations, and validation by Molecular Mechanic Poisson-Boltzmann Surface Area (MM-PBSA) calculations on the DehH2 from Bacillus thuringiensis H2. We aimed to identify the interactions of DehH2 with substrates haloacids, haloacetates, and chlorpyrifos under extreme salinity (35% NaCl). MD simulations revealed that DehH2 preferentially degraded haloacids and haloacetates (-6.3 to -4.7 kcal/mol) by forming three or four hydrogen bonds to the catalytic triad, Asp125, Arg201, and Lys202. Conversely, chlorpyrifos was the least preferred substrate in both MD simulations and MM-PBSA calculations. MD simulation results ranked the DehH2-L-2CP complex (RMSD □0.125-0.23 nm) as the most stable while the least was the DehH2-chlorpyrifos complex (RMSD 0.32 nm; RMSF 0.0 - 0.29). The order of stability was as follows: DehH2-L-2CP > DehH2-MCA > DehH2-D-2CP > DehH2-3CP > DehH2-2,2-DCP > DehH2-2,3-DCP > DehH2-TCA > DehH2-chlorpyrifos. The MM-PBSA calculations further affirmed the DehH2-L-2CP complex's highest stability with the lowest binding energy of -45.14 kcal/mol, followed closely by DehH2-MCA (-41.21 kcal/mol), DehH2-D-2CP (-31.59 kcal/mol), DehH2-3CP (-30.75 kcal/mol), DehH2-2,2- DCP (-29.72 kcal/mol), DehH2-2,3-DCP (-22.20 kcal/mol) and DehH2-TCA (-18.46 kcal/mol). The positive binding energy of the DehH2-chlorpyrifos complex (+180.57 kcal/mol) proved the enzyme's non-preference for the substrate. The results ultimately illustrated the unique specificity of the DehH2 to degrade the above-said pollutants under a hypersaline condition.Communicated by Ramaswamy H. Sarma.
The fundamental colloidal properties of pristine graphene flakes remain incompletely understood, with conflicting reports about their chemical character, hindering potential applications that could exploit the extraordinary electronic, thermal, and mechanical properties of graphene. Here, the true amphipathic nature of pristine graphene flakes is demonstrated through wet-chemistry testing, optical microscopy, electron microscopy, and density functional theory, molecular dynamics, and Monte Carlo calculations, and it is shown how this fact paves the way for the formation of ultrastable water/oil emulsions. In contrast to commonly used graphene oxide flakes, pristine graphene flakes possess well-defined hydrophobic and hydrophilic regions: the basal plane and edges, respectively, the interplay of which allows small flakes to be utilized as stabilizers with an amphipathic strength that depends on the edge-to-surface ratio. The interactions between flakes can be also controlled by varying the oil-to-water ratio. In addition, it is predicted that graphene flakes can be efficiently used as a new-generation stabilizer that is active under high pressure, high temperature, and in saline solutions, greatly enhancing the efficiency and functionality of applications based on this material.