Molecular Dynamics Simulation Analysis Research Articles

Improvement of thermostability by increasing rigidity in the finger regions and flexibility in the catalytic pocket area of Pseudoalteromonas porphyrae κ-carrageenase.

Poor thermostability reduces the industrial application value of κ-carrageenase. In this study, the PoPMuSiC algorithm combined with site-directed mutagenesis was applied to improve the thermostability of the alkaline κ-carrageenase from Pseudoalteromonas porphyrae. The mutant E154A with improved thermal stability was successfully obtained using this strategy after screening seven rationally designed mutants. Compared with the wild-type κ-carrageenase (WT), E154A improved the activity by 29.4% and the residual activity by 51.6% after treatment at 50°C for 30min. The melting temperature (Tm) values determined by circular dichroism were 66.4°C and 64.6°C for E154A and WT, respectively. Molecular dynamics simulation analysis of κ-carrageenase showed that the flexibility decreased within the finger regions (including F1, F2, F3, F5 and F6) and the flexibility improved in the catalytic pocket area of the mutant E154A. The catalytic tunnel dynamic simulation analysis revealed that E154A led to enlarged catalytic tunnel volume and increased rigidity of the enzyme-substrate complex. The increasing rigidity within the finger regions and more flexible catalytic pocket of P. porphyrae κ-carrageenase might be a significant factor for improvement of the thermostability of the mutant κ-carrageenase E154A. The proposed rational design strategy could be applied to improve the enzyme kinetic stability of other industrial enzymes. Moreover, the hydrolysates of κ-carrageenan digested by the mutant E154A demonstrated increased scavenging activities against hydroxyl (OH) radicals and 2,2'-azinobis(3-ethylbenzothiazoline)-6-sulfonic acid (ABTS) radicals compared with the undigested κ-carrageenan.

Tardigrade secretory proteins protect biological structures from desiccation

Tardigrades, microscopic animals that survive a broad range of environmental stresses, express a unique set of proteins termed tardigrade-specific intrinsically disordered proteins (TDPs). TDPs are often expressed at high levels in tardigrades upon desiccation, and appear to mediate stress adaptation. Here, we focus on the proteins belonging to the secreted family of tardigrade proteins termed secretory-abundant heat soluble (“SAHS”) proteins, and investigate their ability to protect diverse biological structures. Recombinantly expressed SAHS proteins prevent desiccated liposomes from fusion, and enhance desiccation tolerance of E. coli and Rhizobium tropici upon extracellular application. Molecular dynamics simulation and comparative structural analysis suggest a model by which SAHS proteins may undergo a structural transition upon desiccation, in which removal of water and solutes from a large internal cavity in SAHS proteins destabilizes the beta-sheet structure. These results highlight the potential application of SAHS proteins as stabilizing molecules for preservation of cells.

Current analytical methods and applications used in the insight of serum proteins interactions with various food additives, pesticides, and contaminants

In recent years, many societies have expressed increasing apprehension regarding the potential negative impacts of food additives, pesticides, and environmental contaminants on human health. Environmental or occupational exposure to these compounds can cause significant adverse effects on human health by causing temporary or permanent changes in the immune system. There is supporting evidence linking pesticides/food ingredients/contaminants-induced immune alterations to the prevalence of diseases associated with changes in immune responses. Hence, it is essential to comprehensively understand the key mechanisms contributing to immune dysregulation induced by these substances, including direct immunotoxicity, endocrine disruption, and antigenicity. The impact of pesticides/food ingredients and contaminants on the human body ranges from mild to severe, depending on their affinity for blood components. These compounds form complexes with blood serum proteins, influencing their metabolism, transport, absorption, and overall toxicity. Numerous studies in the literature have explored the interactions between serum proteins and various molecules, including pesticides, drugs, and food dyes. These investigations employed a range of techniques, including spectroscopy, electrochemical and chromatographic methods as well as molecular modeling and molecular dynamics simulations analyses. This recent review, spanning from 2020 to the present, has been employed to investigate the binding characteristics, mechanisms, and attributes of different food additives, pesticides, and contaminants with serum proteins by using various techniques such as steady-state fluorescence, circular dichroism and ultra-violet spectroscopies, and computational docking methods. The review provides insights into these compounds’ positions and affinities to proteins and possible effects on human health through detailed research studies.

Novel drug discovery: Advancing Alzheimer's therapy through machine learning and network pharmacology

Alzheimer's disease (AD), marked by tau tangles and amyloid-beta plaques, leads to cognitive decline. Despite extensive research, its complex etiology remains elusive, necessitating new treatments. This study utilized machine learning (ML) to analyze compounds with neuroprotective potential. This approach exposed the disease's complexity and identified important proteins, namely MTOR and BCL2, as central to the pathogenic network of AD. MTOR regulates neuronal autophagy and survival, whereas BCL2 regulates apoptosis, both of which are disrupted in AD. The identified compounds, including Armepavine, Oprea1_264702,1-cyclopropyl-7-fluoro-8-methoxy-4-oxoquinoline-3-carboxylic acid,(2S)-4′-Hydroxy-5,7,3′-trimethoxyflavan,Oprea1_130514,Sativanone,5-hydroxy-7,8-dimethoxyflavanone,7,4′-Dihydroxy-8,3′-dimethoxyflavanone,N,1-dicyclopropyl-6,Difluoro-Methoxy-Gatifloxacin,6,8-difluoro-1-(2-fluoroethyl),1-ethyl-6-fluoro-7-(4-methylpiperidin-1-yl),Avicenol C, demonstrated potential modulatory effects on these proteins. The potential for synergistic effects of these drugs in treating AD has been revealed via network pharmacology. By targeting numerous proteins at once, these chemicals may provide a more comprehensive therapeutic approach, addressing many aspects of AD's complex pathophysiology. A Molecular docking, dynamic simulation, and Principle Component Analysis have confirmed these drugs' efficacy by establishing substantial binding affinities and interactions with important proteins such as MTOR and BCL2. This evidence implies that various compounds may interact within the AD pathological framework, providing a sophisticated and multifaceted therapy strategy. In conclusion, our study establishes a solid foundation for the use of these drugs in AD therapy. Thus current study highlights the possibility of multi-targeted, synergistic therapeutic approaches in addressing the complex pathophysiology of AD by integrating machine learning, network pharmacology, and molecular docking simulations. This holistic technique not only advances drug development but also opens up new avenues for developing more effective treatments for this difficult and widespread disease.

Molecular Docking and Dynamic Simulation Analysis of Natural Polyphenols for Identifying Potential PTP1B Inhibitors for Type 2 Diabetes

Molecular Docking and Dynamic Simulation Analysis of Natural Polyphenols for Identifying Potential PTP1B Inhibitors for Type 2 Diabetes

In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene

Single nucleotide polymorphisms (SNPs) are one of the most common determinants and potential biomarkers of human disease pathogenesis. SNPs could alter amino acid residues, leading to the loss of structural and functional integrity of the encoded protein. In humans, members of the minichromosome maintenance (MCM) family play a vital role in cell proliferation and have a significant impact on tumorigenesis. Among the MCM members, the molecular mechanism of how missense SNPs of minichromosome maintenance complex component 6 (MCM6) contribute to DNA replication and tumor pathogenesis is underexplored and needs to be elucidated. Hence, a series of sequence and structure-based computational tools were utilized to determine how mutations affect the corresponding MCM6 protein. From the dbSNP database, among 15,009 SNPs in the MCM6 gene, 642 missense SNPs (4.28%), 291 synonymous SNPs (1.94%), and 12,500 intron SNPs (83.28%) were observed. Out of the 642 missense SNPs, 33 were found to be deleterious during the SIFT analysis. Among these, 11 missense SNPs (I123S, R207C, R222C, L449F, V456M, D463G, H556Y, R602H, R633W, R658C, and P815T) were found as deleterious, probably damaging, affective and disease-associated. Then, I123S, R207C, R222C, V456M, D463G, R602H, R633W, and R658C missense SNPs were found to be highly harmful. Six missense SNPs (I123S, R207C, V456M, D463G, R602H, and R633W) had the potential to destabilize the corresponding protein as predicted by DynaMut2. Interestingly, five high-risk mutations (I123S, V456M, D463G, R602H, and R633W) were distributed in two domains (PF00493 and PF14551). During molecular dynamics simulations analysis, consistent fluctuation in RMSD and RMSF values, high Rg and hydrogen bonds in mutant proteins compared to wild-type revealed that these mutations might alter the protein structure and stability of the corresponding protein. Hence, the results from the analyses guide the exploration of the mechanism by which these missense SNPs of the MCM6 gene alter the structural integrity and functional properties of the protein, which could guide the identification of ways to minimize the harmful effects of these mutations in humans.

Fast Water Desalination with a Graphene-MoS2 Nanoporous Heterostructure.

Energy-efficient water desalination is the key to tackle the challenges with drought and water scarcity that affect 1.2 billion people. The material and type of membrane in reverse osmosis water desalination are the key factors in their efficiency. In this work, we explored the potential of a graphene-MoS2 heterostructure membrane for water desalination, focusing on bilayer membranes and their advantages over monolayer counterparts. Through extensive molecular dynamics simulation and statistical analysis, the bilayer MoS2-graphene was investigated and compared to the monolayer of graphene and MoS2. By optimizing the heterostructure membrane, improved water flux was achieved while maintaining a high ion rejection rate. Furthermore, the study delves into the physical mechanisms underlying the superior performance of heterostructure nanopores, comparing them with circular bilayer and monolayer pores. Factors investigated include water structure, hydration shell near the membrane surface, water density, energy barrier using the potential of mean force, and porosity within the nanopore. Our findings contribute to the understanding of heterostructure membranes and their potential in enhancing the water desalination efficiency, providing valuable insights for future membrane design and optimization.

Allosteric Modulation of Thrombin by Thrombomodulin: Insights from Logistic Regression and Statistical Analysis of Molecular Dynamics Simulations

Allosteric Modulation of Thrombin by Thrombomodulin: Insights from Logistic Regression and Statistical Analysis of Molecular Dynamics Simulations

Exploring different classification-dependent QSAR modelling strategies for HDAC3 inhibitors in search of meaningful structural contributors.

Histone deacetylase 3 (HDAC3), a Zn2+-dependent class I HDACs, contributes to numerous disorders such as neurodegenerative disorders, diabetes, cardiovascular disease, kidney disease and several types of cancers. Therefore, the development of novel and selective HDAC3 inhibitors might be promising to combat such diseases. Here, different classification-based molecular modelling studies such as Bayesian classification, recursive partitioning (RP), SARpy and linear discriminant analysis (LDA) were conducted on a set of HDAC3 inhibitors to pinpoint essential structural requirements contributing to HDAC3 inhibition followed by molecular docking study and molecular dynamics (MD) simulation analyses. The current study revealed the importance of hydroxamate function for Zn2+ chelation as well as hydrogen bonding interaction with Tyr298 residue. The importance of hydroxamate function for higher HDAC3 inhibition was noticed in the case of Bayesian classification, recursive partitioning and SARpy models. Also, the importance of substituted thiazole ring was revealed, whereas the presence of linear alkyl groups with carboxylic acid function, any type of ester function, benzodiazepine moiety and methoxy group in the molecular structure can be detrimental to HDAC3 inhibition. Therefore, this study can aid in the design and discovery of effective novel HDAC3 inhibitors in the future.

Enhancing MD simulations: ASGARD's automated analysis for GROMACS.

Molecular Dynamics (MD) simulations are essential in analyzing the physical movement of molecules, with GROMACS being a widely recognized open-source package for this purpose. However, conducting analyses individually in GROMACS can take excessive time and effort. Addressing this challenge, we introduce ASGARD, an innovative workflow designed to streamline and automate the analysis of MD simulation of protein or protein-ligand complex. Unlike the traditional, manual approach, ASGARD enables researchers to generate comprehensive analyses with a single command line, significantly accelerating the research process and avoiding the laborious task of manual report generation. This tool automatically performs a range of analyses post-simulation, including system stability and flexibility assessments through RMSD Fluctuation and Distribution calculations. It further provides dynamic analysis using SASA, DSSP method graphs, and various interaction analyses. A key feature of ASGARD is its user-friendly design; it requires no additional installations or dependencies, making it highly accessible for researchers. In conclusion, ASGARD simplifies the MD simulation analysis process and substantially enhances efficiency and productivity in molecular research by providing an integrated, one-command analysis solution.Communicated by Ramaswamy H. Sarma.

Enhanced pyroptosis induction with pore-forming gene delivery for osteosarcoma microenvironment reshaping

Osteosarcoma is the most common malignant bone tumor without efficient management for improving 5-year event-free survival. Immunotherapy is also limited due to its highly immunosuppressive tumor microenvironment (TME). Pore-forming gasdermins (GSDMs)-mediated pyroptosis has gained increasing concern in reshaping TME, however, the expressions and relationships of GSDMs with osteosarcoma remain unclear. Herein, gasdermin E (GSDME) expression is found to be positively correlated with the prognosis and immune infiltration of osteosarcoma patients, and low GSDME expression was observed. A vector termed as LPAD contains abundant hydroxyl groups for hydrating layer formation was then prepared to deliver the GSDME gene to upregulate protein expression in osteosarcoma for efficient TME reshaping via enhanced pyroptosis induction. Atomistic molecular dynamics simulations analysis proved that the hydroxyl groups increased LPAD hydration abilities by enhancing coulombic interaction. The upregulated GSDME expression together with cleaved caspase-3 provided impressive pyroptosis induction. The pyroptosis further initiated proinflammatory cytokines release, increased immune cell infiltration, activated adaptive immune responses and create a favorable immunogenic hot TME. The study not only confirms the role of GSDME in the immune infiltration and prognosis of osteosarcoma, but also provides a promising strategy for the inhibition of osteosarcoma by pore-forming GSDME gene delivery induced enhanced pyroptosis to reshape the TME of osteosarcoma.

Structure-Based Virtual Screening Identifying Novel FOXM1 Inhibitors as the Lead Compounds for Glioblastoma.

Glioblastoma multiforme (GBM) is a highly heterogeneous brain tumor with limited treatment options and a poor prognosis. Cancer stem cells (CSCs) have emerged as a critical factor in GBM resistance and management, contributing to tumor growth, heterogeneity, and immunosuppression. The transcription factor FOXM1 has been identified as a key player in the progression, spread, and therapy resistance of various cancers, including GBM. In this research, the objective was to perform structure-based in silico screening with the aim of identifying natural compounds proficient in targeting the DNA-binding domain (DBD) of the FOXM1 protein. In this study, in silico tools were employed for screening a hundred naturally occurring compounds capable of targeting the FOXM1 protein. Through molecular docking analysis and pharmacokinetic profiling, five compounds were found to be promising candidates for extensive interaction with the FOXM1 protein. Further, these compounds were validated for the stability of the FOXM1-natural compound complex using molecular dynamics (MD) simulations. Four compounds, such as Withaferin A, Bryophyllin A, Silybin B, Sanguinarine and Troglitazone (control compound), emerged as promising candidates with substantial interactions with FOXM1, suggesting their potential as a protein inhibitor based on molecular docking investigations. After MD simulation analysis, the FOXM1- Bryophyllin A complex was found to maintain the highest stability, and the other three ligands had moderate but comparable binding affinities over a period of 100 ns. This study provides valuable insights into four promising FOXM1 inhibitors that have the ability to induce senescence in GBM stem cells. These findings contribute to the development of structure-based designing strategies for FOXM1 inhibitors and innovative therapeutic approaches for the treatment of Glioblastoma.

Allosteric Regulation and Inhibition of Coronavirus 3CLpro Revealed by HDX-MS.

Coronavirus (CoV) infections have caused contagious and fatal respiratory diseases in humans worldwide. CoV 3-chymotrypsin-like proteases (3CLpro or Mpro) play an important role in viral maturation, and maintenance of their dimeric conformation is crucial for viral activity. Therefore, allosterically regulated dimerization of 3CLpro can be employed as a drug development target. Here, we investigated the allosteric regulatory mechanism of 3CLpro dimerization by using hydrogen/deuterium exchange coupled with mass spectrometry (HDX-MS) technology. We found that the FLAG tag directly coupled to the N-finger of 3CLpro significantly increased HDX kinetics at the dimer interface, and 3CLpro transformed from a dimer to a monomer. The 3CLpro mutants of SARS-CoV-2, which are monomeric, also exhibited increased deuterium exchange. Binding of the allosteric inhibitor Gastrodenol to most betacoronavirus 3CLpros led to increased allosteric deuterium exchange, resulting in the monomeric conformation of the CoV 3CLpro upon binding. Molecular dynamics (MD) simulation analysis further indicated the molecular mechanism of action of Gastrodenol on CoV 3CLpro: binding of Gastrodenol to SARS-CoV-2 3CLpro destroyed the hydrogen bond in the dimer interface. These results suggest that Gastrodenol may be a potential broad-spectrum anti-betacoronavirus drug.

Experimental measurement and molecular dynamics simulation analysis of thermal aging performance in composite solid propellants

As a complex mixed system, the aging mechanism of high-energy composite materials involves the aging of each component itself, interactions between components, and transformation of microstructural and thermodynamic properties. The study of a single component or performance parameter has great limitations for elaborating the cognitive complexity of aging processes, making it difficult to reveal the underlying principles of physicochemical property transformation. Thus, it can only be applied as an empirical summary. In view of this, this study comprehensively utilized numerical analysis and experimental detection to explore the evolution of micromolecular conformation and changes in macro aging performance from four aspects of composite systems, including binder aging, plasticizer migration, bond interface debonding, and mechanical property transformation. There was good consistency observed between molecular simulation and thermal aging experiments, indicating that there was basically no post curing process for HTPB propellants using TDI as the curing agent. In the early stage of aging, scission chain was the main process and, in the later stage of aging, oxidation crosslinking the main process. Oxidative crosslinking increased the mean square radius of gyration and glass transition temperature of the binder system, reduced the peak value of radial distribution function, and revealed the reason for the change of propellant hardness and CC and CO double bond content. However, chain degradation increased the number of polar groups, enhanced intermolecular polarity, reduced the solubility parameter, and increased the free volume fraction of the mixed system and the dioctyl sebacate diffusion coefficient. This resulted in an increase in the tangent value of the HTPB propellant loss angle from 0.43 to 0.44° and a decrease in the glass transition temperature from 203.3 to 202.0 K. The binding energy at the interfaces of AP/HTPB and Al/HTPB increased first and then decreased, which was consistent with SEM images of bonding interfaces. The joint effect of binding energy and mechanical properties of the binder system promoted the transformation of the stress-strain curve of aging propellant.

Semi-rational design of nitroarene dioxygenase for catalytic ability toward 2,4-dichloronitrobenzene.

Rieske non-heme dioxygenase family enzymes play an important role in the aerobic biodegradation of nitroaromatic pollutants, but no active dioxygenases are available in nature for initial reactions in the degradation of many refractory pollutants like 2,4-dichloronitrobenzene (24DCNB). Here, we report the engineering of hotspots in 2,3-dichloronitrobenzene dioxygenase from Diaphorobacter sp. strain JS3051, achieved through molecular dynamic simulation analysis and site-directed mutagenesis, with the aim of enhancing its catalytic activity toward 24DCNB. The computationally predicted activity scores were largely consistent with the detected activities in wet experiments. Among them, the two most beneficial mutations (E204M and M248I) were obtained, and the combined mutant reached up to a 62-fold increase in activity toward 24DCNB, generating a single product, 3,5-dichlorocatechol, which is a naturally occurring compound. In silico analysis confirmed that residue 204 affected the substrate preference for meta-substituted nitroarenes, while residue 248 may influence substrate preference by interaction with residue 295. Overall, this study provides a framework for manipulating nitroarene dioxygenases using computational methods to address various nitroarene contamination problems.IMPORTANCEAs a result of human activities, various nitroaromatic pollutants continue to enter the biosphere with poor degradability, and dioxygenation is an important kickoff step to remove toxic nitro-groups and convert them into degradable products. The biodegradation of many nitroarenes has been reported over the decades; however, many others still lack corresponding enzymes to initiate their degradation. Although rieske non-heme dioxygenase family enzymes play extraordinarily important roles in the aerobic biodegradation of various nitroaromatic pollutants, prediction of their substrate specificity is difficult. This work greatly improved the catalytic activity of dioxygenase against 2,4-dichloronitrobenzene by computer-aided semi-rational design, paving a new way for the evolution strategy of nitroarene dioxygenase. This study highlights the potential for using enzyme structure-function information with computational pre-screening methods to rapidly tailor the catalytic functions of enzymes toward poorly biodegradable contaminants.

Computational design, docking, and molecular dynamics simulation study of RNA helicase inhibitors of dengue virus.

RNA viruses are complex pathogens in terms of their genetic makeup, mutation frequency, and transmission modes. They contain the RNA helicase enzyme, which plays a crucial role in the viral genome replication process. This work aims to develop and screen a potential molecule that could function as a dengue virus (DENV) RNA helicase inhibitor. The present study was performed by taking 26 potential derivatives of gedunin phytochemicals from the PubChem database as ligands. The binding study of the compounds were analyzed by in silico docking method considering DENV RNA helicase enzyme as the receptor. After a thorough analysis of the docking scores, toxicity, and physicochemical properties, compound tetrahydrogedunin was obtained as the best. Based on tetrahydrogedunin molecular structure, 100 drug-like molecules were designed using the Data Warrior tool. After the screening process for drug-likeness and ADMET properties, the derivative number 42 was considered as the promising. Further comparative docking of derivative 42 and a standard inhibitor molecule ST-610 with DENV RNA helicase enzyme showed binding affinity as -10.0 kcal/mol and -9.6 kcal/mol, respectively. The favorable interaction between DENV RNA helicase and derivative 42 was further validated by 50 nanoseconds molecular dynamics simulation and MM-GBSA analysis. Since the antiviral activity of derivative 42 has not been reported till date, the compound was predicted as a novel therapeutic molecule that can act against the dengue virus (DENV) RNA helicase enzyme.

Theoretical insights into the formation of oxygen activation sites with the affection of protein microenvironment in Flavin-Dependent monooxygenases MsuD

Flavin-dependent monooxygenases are very famous for their capability to catalyze the oxidation of various substrates using oxygen and reduced flavin mononucleotide (FMNH-) or reduced flavin adenine dinucleotide (FADH-). When investigating the catalytic mechanism of flavin-dependent monooxygenase systems, a fundamental problem remains unsolved is that the O2 binding scheme within the reaction cavity is unclear. By applying molecular dynamics simulations, MDpocket simulations, residue mutation molecular dynamics simulation and energy decomposition analyses, this work identified the O2 binding pockets and discovered a possible oxygen migration channel within MsuD enzyme. Molecular dynamics simulations after residue mutation proved that residues Asn104 plays an important role in maintaining the O2 position within the reaction cavity. By analyzing the interaction between O2 and the surrounding protein microenvironment, we demonstrated that N5 is a more favored reaction site and speculated a reasonable O2 activation process. This work recovers the formation of oxygen activation sites in MsuD enzyme, which is of great significance to further investigations of the catalytic reaction mechanism. This work provides a feasible method to study the O2 binding in proteins and the role of the protein microenvironment around the reaction cavity.

Enhancing the effectiveness of Polymyxin E with a Fisetin Nanoemulsion against a Colistin-resistant Salmonella typhimurium infection

BackgroundPolymyxin E is widely recognized as a last resort for treating multidrug-resistant gram-negative bacteria. Unfortunately, the effectiveness of polymyxin E is significantly reduced when treating life-threatening bacterial infections due to plasmid-mediated polymyxin E resistance. The synergistic effect of applying a polymyxin E adjuvant is a promising strategy for overcoming the growing threat of antibiotic-resistant pathogens. PurposeTo evaluate the synergistic effect of fisetin and polymyxin E on S. typhimurium infections in vivo and further elucidate the underlying mechanism of this effect. MethodsThe effect of combining fisetin and polymyxin E to treat mobilized colistin resistance-1-positive (MCR-1-positive) gram-negative bacteria in vitro was examined using various methods, such as checkerboard assays, growth curves and time‒kill curves. To elucidate the mechanism by which fisetin affects MCR-1, we employed ultraviolet (UV) absorption spectroscopy, thin layer chromatography (TLC), and western blot analysis to investigate its effect at the protein level. Subsequently, molecular dynamics simulations (MDS) and metabolomics analysis were utilized to determine the site of interaction between fisetin and MCR-1 as well as the potential pathways and mechanisms involved. A new nanoemulsion of fisetin was produced using high-pressure homogenization, and its stability was tested. Finally, two animal models of S. typhimurium HYM2 infection were established to evaluate the synergistic effect of polymyxin E and fisetin in vivo. ResultsOur study revealed that fisetin exhibited a synergistic effect when combined with polymyxin E against MCR-1-positive S. typhimurium. The TLC results demonstrated that fisetin could inhibit the phosphoethanolamine (PEA) transfer of the MCR-1 protein, thereby restoring the activity of polymyxin E in strains against MCR-1. The MDS analysis indicated robust and immediate binding between fisetin and the MCR-1 protein, with both hydrophobic and polar effects playing significant roles in determining the binding energy of the former. Metabolomic studies demonstrated that the addition of fisetin significantly modulated bacterial metabolites. Moreover, it effectively inhibited the activity of ABC transporters in bacteria, thereby mitigating bacterial drug resistance and enhancing the therapeutic efficacy of polymyxin E. Furthermore, in mouse and chick models of infection, intragastric administration of the fisetin nanoemulsion together with polymyxin E resulted in significant therapeutic benefits, including increased survival rates, reduced bacterial colonization, and decreased levels of inflammatory factors. ConclusionFisetin, an MCR-1 inhibitor and a promising synergistic partner of polymyxin E, has significant potential for clinical application in the treatment of S. typhimurium infections, particularly those resulting extensively from drug-resistant MCR-1-positive strains.

In-silico Identification of Dexamethasone-similar Compounds Against SARS-Cov-2 Spike Protein: A Drug Repurposing Approach

Abstract: To identify potential drug candidates for the treatment of COVID-19 using a computational method. The recent pandemic of COVID-19 is observed as not less than a natural calamity of humankind and raised serious concerns for its immediate management. The continued spread of coronavirus disease across the globe poses a significant threat to human health. Out of this, the application of Dexamethasone has been correlated with reduced mortality in COVID-19 cases. This study sheds new light on the pharmacological potential of Dexamethasone and similar compounds in mitigating SARSCoV2 infection. : In this study, we explored Dexamethasone-similar compounds, which can modulate the binding of SARS-CoV-2 spike protein to the host and TH17 programming in the host using a computer-aided drug repurposing method. The docking studies indicate that Desoximetasone can bind to the spike proteins of SARS-CoV-2, which are crucial for viral attachment and entry into host cells. By competing with these spike proteins, Desoximetasone may interfere with the virus's ability to attach to and enter host cells, potentially inhibiting viral replication and spread. The results from molecular dynamic simulation analysis further support this notion by demonstrating that Desoximetasone has a strong interaction with the binding sites of the spike protein. Experimental validation through in vitro studies and clinical trials is needed to evaluate its potential as a treatment option for COVID-19. Together, these findings revealed the underlying mechanism of how Desoximetasone can influence the fate of the virus in the host and advocated its anti-viral potential.

The functional and structural characterisation of the bZIP transcription factors from Myristica fragrans Houtt. associated to plant disease-resistant defence: An insight from transcriptomics and computational modelling

The bZIP transcription factors play crucial roles in various aspects of plant biology, including development, defence mechanisms, senescence, and responses to both biotic and abiotic environmental stresses. Myristica fragrans Houtt. transcriptome analysis has identified 15 bZIP transcription factors, each exhibiting major conserved domains and motifs such as BRLZ, MFMR, and DOG1. Functional characterisation of these identified MfbZIP factors indicates their predominant localisation within the nucleus. Phylogenetic analysis reveals that MfbZIP factors cluster into three subgroups alongside annotated bZIP sequences from Magnolia sinica and Arabidopsis thaliana. Moreover, gene ontology (GO) analysis highlights several key functions of MfbZIP, including involvement in defence responses, abscisic acid-induced signalling pathways, and DNA-binding transcription factor activity. Further investigation through KEGG pathway analysis reveals that the amino acid sequences of MfbZIP contain binding motifs for proteins such as TGA, implicated in plant hormone signal transduction pathways associated with disease resistance. To confirm the disease-defence-related activity of the TGA binding protein within MfbZIP, we employed amino acid sequences for 3-D ab initio modelling. Subsequently, we analysed TGA-NPR1 interactions using docking and molecular dynamics simulation analysis. These analyses shed light on the functional and structural aspects of TGA, demonstrating its stable association with NPR1 protein and its significance in the expression of PR1 protein, thus playing a pivotal role in defence responses against pathogens.