Molecular Dynamics Simulation Analysis Research Articles

The interplay between liquid–liquid and ferroelectric phase transitions in supercooled water

The distinctive characteristics of water, evident in its thermodynamic anomalies, have implications across disciplines from biology to geophysics. Considered a valid hypothesis to rationalize its unique properties, a liquid-liquid phase transition in water below the freezing point, in the so-called supercooled regime, has nowadays been observed in several molecular dynamics simulations and is being actively researched experimentally. The hypothesis of ferroelectric phase transition in supercooled water can be traced back to 1977, due to Stillinger. In this work, we highlight intriguing and far-reaching implications of water: The ferroelectric and liquid-liquid phase transitions can be designed as two facets of the same underlying phenomenon. Our results are based on the analysis of extensive molecular dynamics simulations and are explained in the context of a classical density functional theory in mean-field approximation valid for a polar liquid, where dipolar interaction is treated perturbatively. The theory underpins the potential role of ferroelectricity in promoting the liquid-liquid phase transition, being the density-polarization coupling inherent in the dipolar interaction potential. The existence of ferroelectric order in supercooled low-density liquid water is confirmed by the observation in molecular dynamics simulations of collective modes in space-time polarization correlation functions, traceable to spontaneous breaking of continuous rotational symmetry. Our work sheds light on water's supercooled behavior and opens the door to experimental investigations of the static and dynamic behavior of water's polarization.

DNA binding, and apoptosis-inducing activities of a β-ionone-derived ester in human myeloid leukemia cells: multispectral and molecular dynamic simulation analyses.

β-Ionone is the end-ring counterpart of β-carotenoids, which are widely found in fruits and vegetables. Recent studies have illustrated the antimetastatic, anti-proliferative, and apoptosis-inducing activities of β-ionone both in vitro and in vivo. We aimed to explore the anti-cancer potency of β-Ionone-derived ester, (E)-4-(2,6,6-trimethylcyclohex-1-enyl) but-3-en-2-ylpyrazine-2-carboxylate (4-TM.P). The cytotoxic effects of the compound on K562 cells were evaluated by MTT assay. The mechanisms of apoptosis induction were investigated by acridine orange/ethidium bromide (AO/EtBr) double staining, cell cycle analysis, and Annexin V/PI staining. Furthermore, the 4-TM.P-DNA interactions have been thoroughly elucidated by various methods, such as ultraviolet-visible spectroscopy, fluorescence assays, viscosity measurements, molecular docking, and dynamic simulation. The MTT cytotoxicity assay revealed that the growth of K562 cells was inhibited by treatment with β-ionone-derived ester, with an IC50 of 25 ± 5.0µM at 72h. Morphological studies revealed the occurrence of apoptosis in treated cells, and G0/G1 cell cycle arrest was observed after treatment of the cells with the IC50 value of the compound. Analyses of multi-spectroscopy and viscosity assays revealed that 4-TM.P binds to DNA in the minor groove mode, which was supported by molecular docking studies. The dynamic stability of the complex was also confirmed using molecular dynamic simulation analyses.

Revealing the potential therapeutic mechanism of Lonicerae Japonicae Flos in Alzheimer’s disease: a computational biology approach

BackgroundAlzheimer’s disease (AD) is a degenerative brain disease without a cure. Lonicerae Japonicae Flos (LJF), a traditional Chinese herbal medicine, possesses a neuroprotective effect, but its mechanisms for AD are not well understood. This study aimed to investigate potential targets and constituents of LJF against AD.MethodsNetwork pharmacology and bioinformatics analyses were performed to screen potential compounds and targets. Gene Expression Omnibus (GEO) datasets related to AD patients were used to screen core targets of differential expression. Gene expression profiling interactive analysis (GEPIA) was used to validate the correlation between core target genes and major causative genes of AD. The receiver operating characteristic (ROC) analysis was used to evaluate the predictive efficacy of core targets based on GEO datasets. Molecular docking and dynamics simulation were conducted to analyze the binding affinities of effective compounds with core targets.ResultsNetwork pharmacology analysis showed that 112 intersection targets were identified. Bioinformatics analysis displayed that 32 putative core targets were identified from 112 intersection targets. Only eight core targets were differentially expressed based on GEO datasets. Finally, six core targets of MAPK8, CTNNB1, NFKB1, EGFR, BCL2, and NFE2L2 were related to AD progression and had good predictive ability based on correlation and ROC analyses. Molecular docking and dynamics simulation analyses elucidated that the component of lignan interacted with EGFR, the component of β-carotene interacted with CTNNB1 and BCL2, the component of β-sitosterol interacted with BCL2, the component of hederagenin interacted with NFKB1, the component of berberine interacted with EGFR and BCL2, and the component of baicalein interacted with NFKB1, EGFR and BCL2.ConclusionThrough a comprehensive analysis, this study revealed that six core targets (MAPK8, CTNNB1, NFKB1, EGFR, BCL2, and NFE2L2) and six practical components (lignan, β-carotene, β-sitosterol, hederagenin, berberine, and baicalein) were involved in the mechanism of action of LJF against AD. Our work demonstrated that LJF effectively treats AD through its multi-component and multi-target properties. The findings of this study will establish a theoretical basis for the expanded application of LJF in AD treatment and, hopefully, can guide more advanced experimental research in the future.

Advances in machine learning methods in copper alloys: a review.

Advanced copper and copper alloys, as significant engineering structural materials, have recently been extensively used in energy, electron, transportation, and aviation domains. Higher requirements urge the emergence of high-performance copper alloys. However, the traditional trial-and-error experimental observations and computational simulation research used to design and develop novel materials are time-consuming and costly. With the accumulation of material research and rapid development of computational ability, the thorough application of material genome engineering has sped up the development of novel materials and facilitates the process of systematic engineering application. This review summarizes the benefits of data-driven machine learning techniques and the state of the art of machine learning research in the area of copper alloys. It also displays the widely used computational simulation approaches (e.g., the first-principles calculation, molecular dynamics simulation, phase-field simulations, and finite element analysis) and their combined applications in material design and property prediction. Finally, the limitations of machine learning research methods are outlined, and future development directions are proposed.

Droplet impact dynamics on the surface of super-hydrophobic BNNTs stainless steel mesh.

The 'gas‒liquid‒solid' mechanism annealing method was used to create a superhydrophobic boron nitride nanotube (BNNT) stainless steel mesh in a tube furnace at 1250°C in an NH3 environment. Fe powder was used as a catalyst, and B:B2O3 = 4:1 was used as the raw material. The water droplets on the surface of the superhydrophobic material had a contact angle of approximately 150° and a slide angle of approximately 3°. By using molecular dynamics (MD) simulation technology, a three-dimensional braided physical model of nanodroplets and superhydrophobic BNNT mesh surfaces with the same contact angle and rolling angle was prepared via the function weaving method. The Weber number (We) was used as the entrance point to establish the relationship between macroscale experimental studies and nanoscale MD simulation analysis on the basis of these efforts. A study was conducted on the dynamic behaviour of droplets impacting a superhydrophobic BNNT filter surface. We suggest that the wettability, substrate structure, and impact velocity are connected to the impact dynamic behaviour of droplets on the basis of the data obtained at various scales. The findings demonstrate that when the droplet impact velocity increases, several droplet phenomena-such as impact-rebound, impact-spread-rebound, and impact-spread-breaking-polymerisation-spatter-appear on the substrate surface sequentially. The mechanism of impact behaviour at various scales is explained in light of these events. Furthermore, a better theoretical model is proposed to assess the droplet wetting transition at the nanoscale. This model accurately predicts the boundary Weber number that starts the wetting transition. Moreover, the connections among the impact velocity, spreading diameter, and contact time (or We) are examined. The tendencies found via MD simulations match the outcomes of the experiments. Our discoveries and outcomes broaden our understanding of how droplet impact affects the dynamic behaviour of superhydrophobic surfaces. A scientific foundation for examining the dynamic behaviour of droplets is provided by combining simulations and experiments.

Network Pharmacology and Molecular Dynamics Simulations Reveal the Mechanism of Total Alkaloid Components in Anisodus Tanguticus (Maxim.) Pascher in Treating Inflammation and Pain.

This study aimed to elucidate the mechanism that total alkaloids in Anisodus tanguticus (AT)(Maxim.) Pascher played anti-inflammatory and analgesic effects. In this paper, the anti-inflammatory effect in the total alkaloids of AT was confirmed via lipopolysaccharide (LPS)-induced inflammation model in RAW 264.7 cells and the main components of AT were immediately analyzed by UPLC/MS. Disease targets were obtained in GeneCards and DisGeNET. Targets of major compounds were searched in ETCM, TCMSP and other databases. The protein-protein interaction (PPI) network was constructed using STRING database, and Cytoscape was used for core targets screening. GO and KEGG enrichment analysis were performed using Daivid database. Sailvina was used for molecular docking. Molecular dynamics simulation analysis was performed using the Amber 20 program. The results showed that the main components in AT were anisodamine, atropine, fabiatrin, scopolamine, scopoletin and scopolin, possibly exerting anti-inflammatory and analgesic effects through pathways such as EGFR tyrosine kinase inhibitor resistance and IL-17 signaling pathway. Fabiatrin and scopolin could be potential drugs with good anti-inflammatory and analgesic effects.

Hybrid Molecules Containing Methotrexate, Vitamin D, and Platinum Derivatives: Synthesis, Characterization, In Vitro Cytotoxicity, In Silico ADME Docking, Molecular Docking and Dynamics.

Designing hybrid-based drugs is one promising strategy for developing effective anticancer drugs that explore combination therapy to enhance treatment efficacy, overcome the development of drug resistance, and lower treatment duration. Bisphosphonates and Vitamin D are commonly administered drugs for the treatment of bone diseases and the prevention of bone metastases. Platinum-based and methotrexate are widely used anticancer drugs in clinics. However, their use is hampered by adverse side effects. Hybrid-based compounds containing either bisphosphonate, vitamin D, platinum-based, or methotrexate were synthesized and characterized using FTIR, 1H-,31P, 13C-NMR, and UHPLC-HRMS which confirmed their successful synthesis. The hydroxyapatite bone binding assay revealed a promising percentage binding affinity of the bisphosphonate hybrid compounds. In vitro cytotoxicity assays on MCF-7 and HT-29 cell lines revealed a promising cytotoxic effect of hybrid 19 at 50 and 100 μg/mL on HT-29 and hybrid 15 on MCF-7 at 100 μg/mL. Molecular docking and dynamics simulation analysis revealed a binding affinity of -9.70 kcal/mol for hybrid 15 against Human 3 alpha-hydroxysteroid dehydrogenase type 3, showing its capability to inhibit Human 3 alpha-hydroxysteroid dehydrogenase type 3. The Swiss ADME, ProTox-II, GUSAR (General Unrestricted Structure-Activity Relationships), and molecular docking and dynamics studies revealed that these compounds are promising anticancer compounds.

Therapeutic Effect of Shikimic Acid on Heat Stress-Induced Myocardial Damage: Assessment via Network Pharmacology, Molecular Docking, Molecular Dynamics Simulation, and In Vitro Experiments

Abstract: Background: Rising global temperatures have been linked to an increased incidence of heat stress (HS)-induced myocardial damage. Methods: This study aimed to investigate the therapeutic potential of shikimic acid (SA) on HS-induced myocardial damage using network pharmacology, molecular docking, molecular dynamics (MD) simulations, and in vitro experiments. Results: Network pharmacology analysis indicated that SA significantly attenuates the inflammatory response to HS by modulating 60 targets, including TNF, IL-6, and STAT3, which are enriched in the PI3K/AKT signaling pathway. Molecular docking and MD simulation analyses demonstrated that SA forms stable complexes with TNF (−6.642 kcal/mol) and IL-6 (−7.261 kcal/mol), with no significant conformational changes over a 100 ns simulation period. In vitro experiments demonstrated that SA, within the concentration range of 250 μM to 31.25 μM, significantly promoted the proliferation of normal HL-1 cells by an average of 31.0%. Moreover, it enhanced the survival rate of HL-1 cells exposed to 43 °C for 3 h by approximately 59.9% and downregulated the expression of Hsp90 and Hsp70. Additionally, this concentration range of SA reduced the expression of TNF-α, IL-6, TLR2, and COL1A1. Conclusions: These findings offer evidence for the therapeutic potential of SA in HS-induced myocardial damage.

Luteolin ameliorates chronic stress-induced depressive-like behaviors in mice by promoting the Arginase-1+ microglial phenotype via a PPARγ-dependent mechanism.

Accumulating evidence shows that neuroinflammation substantially contributes to the pathology of depression, a severe psychiatric disease with an increasing prevalence worldwide. Although modulating microglial phenotypes is recognized as a promising therapeutic strategy, effective treatments are still lacking. Previous studies have shown that luteolin (LUT) has anti-inflammatory effects and confers benefits on chronic stress-induced depression. In this study, we investigated the molecular mechanisms by which LUT regulates the functional phenotypes of microglia in mice with depressive-like behaviors. Mice were exposed to chronic restraint stress (CRS) for 7 weeks, and were administered LUT (10, 30, 40 mg· kg-1 ·day-1, i.g.) in the last 4 weeks. We showed that LUT administration significantly ameliorated depressive-like behaviors and decreased hippocampal inflammation. LUT administration induced pro-inflammatory microglia to undergo anti-inflammatory arginase (Arg)-1+ phenotypic polarization, which was associated with its antidepressant effects. Furthermore, we showed that LUT concentration-dependently increased the expression of PPARγ in LPS + ATP-treated microglia and the hippocampus of CRS-exposed mice, promoting the subsequent inhibition of the NLRP3 inflammasome. Molecular dynamics (MD) simulation and microscale thermophoresis (MST) analysis confirmed a direct interaction between LUT and peroxisome proliferator-activated receptor gamma (PPARγ). By using the PPARγ antagonist GW9662, we demonstrated that LUT-driven protection, both in vivo and in vitro, resulted from targeting PPARγ. First, LUT-induced Arg-1+ microglia were no longer detected when PPARγ was blocked. Next, LUT-mediated inhibition of the NLRP3 inflammasome and downregulation of pro-inflammatory cytokine production were reversed by the inhibition of PPARγ. Finally, the protective effects of LUT, which attenuated the microglial engulfment of synapses and prevented apparent synapse loss in the hippocampus of CRS-exposed mice, were eliminated by blocking PPARγ. In conclusion, this study showed that LUT ameliorates CRS-induced depressive-like behaviors by promoting the Arg-1+ microglial phenotype through a PPARγ-dependent mechanism, thereby alleviating microglial pro-inflammatory responses and reversing microglial phagocytosis-mediated synapse loss.

Investigating the role of PmrB mutation on Colistin antibiotics drug resistance in Klebsiella Pneumoniae

Klebsiella pneumoniae, a member of the Enterobacteriaceae family, naturally resides in the digestive tracts of both healthy animals and humans. Carbapenem-resistant Klebsiella pneumoniae (CRKP) poses a significant health risk for hospitalized patients worldwide, greatly reducing the effectiveness of commonly used antibiotics. This leaves healthcare providers with limited treatment options, often relying on colistin. PmrB is important for the survival of Klebsiella pneumonia and, a mutation in the PmrB protein is accountable for the development of colistin antibiotic resistance in Klebsiella pneumonia. This is especially important because colistin is a fundamental component in the treatment of pneumonia. Three mutated residues—T157P, G207D, and T246A—are responsible for colistin resistance. The structural alterations and underlying mechanisms in the PmrB protein that cause resistance owing to mutation remain unclear. As a result, this study is focused to the exploration of the putative mechanism of resistance resulting from these mutations, as well as the structure modification of normal and mutant PmrB proteins, using molecular docking and molecular dynamics simulations analysis. Our results demonstrated that the interaction paradigm for the mutants has been altered and thus showing a significant effect upon the hydrogen bonding network. Interestingly, the binding of Colistin with the three mutant demonstrate unstable behavior as compared with WT+Colistin. The proposed drug-resistance mechanism will help to guide the development of PmrB drugs. These finding may give a new framework for developing novel drugs against the mutant version of PmrB.

Metabolomics combined with network pharmacology revealed a paradigm for determining the mechanism underlying the metabolic action of Gegen Qinlian Decoction amelioration of ulcerative colitis in mice

Ulcerative colitis (UC) is a common disease of the digestive system that is challenging to treat. Gegen Qinlian Decoction (GQD), which is an ancient classic formula in Chinese medicine, is effective at alleviating the symptoms of UC, but comprehensive research on its mechanism of action has not been performed. Here, we explored the material basis and potential molecular mechanism underlying GQD-mediated protection against UC by integrated metabolomics and network pharmacology. First, differentially expressed metabolites were screened and identified via a metabolomics approach, and the metabolic pathway was analyzed via MetaboAnalyst. Second, a protein–protein interaction (PPI) network was constructed to identify hub genes that encode metabolic enzymes. Third, the differentially expressed metabolites were used to construct a compound-reaction-enzyme-gene network. Finally, the metabolites were compared with relevant active components for molecular docking, molecular dynamics (MD) simulation, and verification experiment. GQD intervention alleviated UC in mice and significantly inhibited metabolic dysfunction in mice with UC; specifically, GQD reversed the abnormal changes in metabolites in the colon and serum, and regulated the arachidonic acid metabolism, tryptophan metabolism, glycerophospholipid metabolism, and purine metabolism pathways. Further literature review and molecular docking analysis with targeted MD simulation and Poisson-Boltzmann surface area (MM-PBSA) analysis were performed, revealing that GQD may inhibit the disruption of arachidonic acid metabolism and tryptophan metabolism by suppressing PTGS2 and CYP450 protein expression; these results were verified by qRT-PCR, WB, and surface plasmon resonance (SPR) assays. Our experiments indicated that GQD alleviated UC in mice by systematically regulating arachidonic acid metabolism and tryptophan metabolism, supporting further research and the development of GQD as a novel drug for ameliorating UC.

Deciphering the conformational changes induced by high-risk nsSNPs in β-lactoglobulin

Whey protein from bovine milk is highly valued in the food and pharmaceutical industries because of its high protein content and abundance of essential amino acids. The relationship between whey protein and the β-lactoglobulin (BLG) gene has been extensively discussed because BLG is the most abundant whey protein, making up approximately 50 % of the total whey protein in bovine milk. In recent years, researchers have been interested in this gene because of its critical role in healthy milk production, and any genetic polymorphism in this gene may deteriorate the milk quality. In the current study, we identified several deleterious and damaging non-synonymous single nucleotide polymorphisms (nsSNPs) in BLG and analyzed their destabilizing effects using different computational algorithms. Cumulative results from all tools and evolutionary conservation profiles of BLG suggested that four nsSNPs, G17A, W19C, F136S, and C119R, were the most deleterious and could affect the structural integrity of the protein. Detailed molecular dynamics simulation analysis revealed that all variants induced major structural alterations, that affected the ability of the protein to interact with natural and synthetic ligands. Particularly, the G17A, F136S, and C119R variants induced large conformational changes in the EF loop and main α-helix of BLG, which may affect the access of natural and synthetic ligands to the central calyx of BLG. We hope that the suggested nsSNPs will guide future studies and assist researchers in improving the quality of bovine milk.

Vibrational, theoretical characterisation and In Silico investigation of Norcinnamolaurine: a natural lead for inhibiting AURKA and overcoming immune evasion in Triple-Negative Breast Cancer

ABSTRACT Alkaloids represent a diverse category of natural compounds with noteworthy pharmacological and therapeutic applications. Benzylisoquinoline alkaloids (BIAs) are distinguished by their varied structures and potential medicinal properties. This study specifically investigates Norcinnamolaurine, a BIA found in multiple species and acknowledged for its therapeutic advantages. In the current investigation, we comprehensively analyzed Norcinnamolaurine, encompassing Frontier Molecular Orbital studies, vibrational spectroscopy, nonlinear optical properties, natural bond orbital evaluations, and Fukui's analysis. Additionally, we executed an E-pharmacophore-based screening utilizing the AURKA-Norcinnamolaurine complex. The generated hypothesis underwent database screening; lead compounds from the Natural Product and Drug Bank databases exhibited enhanced binding affinities ranging from −8.602 to −7.148 kcal/mol, demonstrating improved interactions within the AURKA binding pocket. Subsequently, the identified lead compounds were subjected to further analysis via MMGBSA, DFT, and Molecular Dynamics Simulations (MDS). Our findings indicate that Norcinnamolaurine exhibits a superior binding affinity towards the target protein. Significant outcomes were also observed in the vibrational and FMO studies. Moreover, MDS analysis revealed that the resultant complexes maintained relative stability, exhibiting minimal deviation and fluctuations. This stability was corroborated through additional assessments using MMPBSA and PCA/FEL methodologies.

Investigating pH-induced conformational switch in PIM-1: An integrated multi spectroscopic and MD simulation study

PIM-1 is a Ser/Thr kinase, which has been extensively studied as a potential target for cancer therapy due to its significant roles in various cancers, including prostate and breast cancers. Given its importance in cancer, researchers are investigating the structure of PIM-1 for pharmacological inhibition to discover therapeutic intervention. This study examines structural and conformational changes in PIM-1 across different pH using various spectroscopic and computational techniques. Spectroscopic results indicate that PIM-1 maintains its secondary and tertiary structure within the pH range of 7.0–9.0. However, protein aggregation occurs in the acidic pH range of 5.0–6.0. Additionally, kinase assays suggested that PIM-1 activity is optimal within the pH range of 7.0–9.0. Subsequently, we performed a 100 ns all-atom molecular dynamics (MD) simulation to see the effect of pH on PIM-1 structural stability at the molecular level. MD simulation analysis revealed that PIM-1 retains its native conformation in alkaline conditions, with some residual fluctuations in acidic conditions as well. A strong correlation was observed between our MD simulation, spectroscopic, and enzymatic activity studies. Understanding the pH-dependent structural changes of PIM-1 can provide insights into its role in disease conditions and cellular homeostasis, particularly regarding protein function under varying pH conditions.

Rational Design for Enhancing Cellobiose Dehydrogenase Activity and Its Synergistic Role in Straw Degradation.

Addressing the demand for efficient biological degradation of straw, this study employed rational design coupled with structural biology and enzyme engineering techniques to enhance the catalytic activity of cellobiose dehydrogenase (PsCDH, CDH form Pycnoporus sanguineus). By predicting and modifying the active site and key amino acids of PsCDH, several CDH immobilized enzyme preparations with higher catalytic activities were successfully obtained. The excellent mutant T1 (C286Y/A461H/F464R) exhibited a 2.7-fold increase in enzyme activity compared to the wild type. Simulated calculations indicated that the enhancement of catalytic activity was primarily due to the formation of additional intermolecular interactions between CDH and the substrate, as well as the enlargement of the substrate pocket to reduce steric hindrance effects. Additionally, molecular dynamics simulation analysis revealed a potential correlation between structural stability and enzyme activity. When PsCDH was added to a multienzyme synergistic straw degradation system, the cellulose degradation rate increased by 1.84-fold. Moreover, mutant T1 further increased the degradation of lignocellulose in the mixed system. This study provides efficient enzyme sources and modification strategies for the high-efficiency biological conversion of straw and unconventional feedstock degradation, thereby possessing significant academic value and application prospects.

Insights into the Therapeutic Potential of Active Ingredients of Citri Reticulatae Pericarpium in Combatting Sarcopenia: An In Silico Approach.

Sarcopenia is a systemic medical disorder characterized by a gradual decline in muscular strength, function, and skeletal muscle mass. Currently, there is no medication specifically approved for the treatment of this condition. Therefore, the identification of new pharmacological targets may offer opportunities for the development of novel therapeutic strategies. The current in silico study investigated the active ingredients and the mode of action of Citri Reticulatae Pericarpium (CRP) in addressing sarcopenia. The active ingredients of CRP and the potential targets of CRP and sarcopenia were determined using various databases. The STRING platform was utilized to construct a protein-protein interaction network, and the key intersecting targets were enriched through the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses. Molecular docking was used to determine the binding interactions of the active ingredients with the hub targets. The binding affinities obtained from molecular docking were subsequently validated through molecular dynamics simulation analyses. Five active ingredients and 45 key intersecting targets between CRP and sarcopenia were identified. AKT1, IL6, TP53, MMP9, ESR1, NFKB1, MTOR, IGF1R, ALB, and NFE2L2 were identified as the hub targets with the highest degree node in the protein-protein interaction network. The results indicated that the targets were mainly enriched in PIK3-AKT, HIF-1, and longevity-regulating pathways. The active ingredients showed a greater interaction affinity with the hub targets, as indicated by the results of molecular docking and molecular dynamics simulations. Our findings suggest that the active ingredients of Citri Reticulatae Pericarpium, particularly Sitosterol and Hesperetin, have the potential to improve sarcopenia by interacting with AKT1 and MTOR proteins through the PI3K-AKT signaling pathway.

Phytoconstituents of Withania somnifera (L.) Dunal (Ashwagandha) unveiled potential cerebroside sulfotransferase inhibitors: insight through virtual screening, molecular dynamics, toxicity, and reverse pharmacophore analysis

Cerebroside sulfotransferase (CST) is considered as therapeutic target for substrate reduction therapy (SRT) for metachromatic leukodystrophy (MLD). The present study evaluates the therapeutic potential of 57 phytoconstituents of Withania somnifera against CST. Using binding score cutoff ≤-7.0 kcal/mol, top 10 compounds were screened and after ADME and toxicity-based screening, Withasomidienone, 2,4-methylene-cholesterol, and 2,3-Didehydrosomnifericin were identified as safe and potent drug candidates for CST inhibition. Key substrate binding site residues involved in interaction were LYS82, LYS85, SER89, TYR176, PHE170, PHE177. Four steroidal Lactone-based withanolide backbone of these compounds played a critical role in stabilizing their position in the active site pocket. 100 ns molecular dynamics simulation and subsequent trajectory analysis through structural deviation and compactness, principal components, free energy landscape and correlation matrix confirmed the stability of CST-2,3-Didehydrosomnifericin complex throughout the simulation and therefore is considered as the most potent drug candidate for CST inhibition and Withasomidienone as the second most potent drug candidate. The reverse pharmacophore analysis further confirmed the specificity of these two compounds towards CST as no major cross targets were identified. Thus, identified compounds in this study strongly present their candidature for oral drug and provide route for further development of more specific CST inhibitors.

Immunoinformatics Design of a Multiepitope Vaccine (MEV) Targeting Streptococcus mutans: A Novel Computational Approach.

Dental caries, a persistent oral health challenge primarily linked to Streptococcus mutans, extends its implications beyond dental decay, affecting over 4 billion individuals globally. Despite its historical association with childhood, dental caries often persists into adulthood with prevalence rates ranging from 60 to 90% in children and 26 to 85% in adults. Currently, there is a dearth of multiepitope vaccines (MEVs) specifically designed to combat S. mutans. To address this gap, we employed an immunoinformatics approach for MEV design, identifying five promising vaccine candidates (PBP2X, PBP2b, MurG, ATP-F, and AGPAT) based on antigenicity and conservation using several tools including CELLO v.2.5, Vaxign, v2.0, ANTIGENpro, and AllerTop v2.0 tools. Subsequent identification of linear B-cell and T-cell epitopes by SVMTrip and NetCTL/NetMHC II tools, respectively, guided the construction of a MEV comprising 10 Cytotoxic T Lymphocyte (CTL) epitopes, 5 Helper T Lymphocyte (HTL) epitopes, and 5 linear B-cell epitopes, interconnected by suitable linkers. The resultant MEV demonstrated high antigenicity, solubility, and structural stability. In silico immune simulations showcased the MEV's potential to elicit robust humoral and cell-mediated immune responses. Molecular docking studies revealed strong interactions between the MEV construct and Toll-Like Receptors (TLRs) and Major Histocompatibility Complex (MHC) molecules. Remarkably, the MEV-TLR-4 complexes exhibited a low energy score, high binding affinity, and a low dissociation constant. The Molecular Dynamic (MD) simulation analysis suggested that MEV-TLR-4 complexes had the highest stability and minimal conformational changes indicating equilibrium within 40 nanosecond time frames. Comprehensive computational analyses strongly support the potential of the proposed MEV to combat dental caries and associated infections. The study's computational assays yielded promising results, but further validation through in vitro and in vivo experiments is needed to assess its efficacy and safety.

Elucidation of significant regulatory proteins in the JNK pathway modulated by truncated pardaxin, PC6 through molecular dynamic simulation

ABSTRACT Cancer remains a critical global health issue, with current treatments often causing significant side effects. This has spurred the search for alternative therapies, such as bioactive peptides, which offer advantages such as higher selectivity against cancer cells and ease of modification. Pardaxin, a bioactive peptide, has shown anticancer effects on various cell lines via the JNK pathway. A truncated form of pardaxin, PC6, has demonstrated anticancer properties with reduced haemolytic effects though its cell death mechanism is unclear. This study aimed to investigate PC6-induced cell death, focusing on the JNK cascade compared to parental pardaxin (PAR). JNK cascade genes were sourced from the Gene Ontology database, followed by docking screening and protein-peptide network analysis. The network identified 65 genes involved in the JNK pathway, which were verified through gene enrichment analysis. Molecular dynamic simulation and binding affinity analysis showed that PC6 had a higher affinity (−88.69, −82.17, −54.93 kcal/mol) for MAPK8, MAPK9 and HRAS proteins than PAR (−68.88, −76.64, −38.63 kcal/mol). These findings suggest that PC6 specifically interacts with these proteins to induce apoptosis via the JNK cascade, highlighting its potential as an effective anticancer agent.

Interactive Structural Analysis of KH3-4 Didomains of IGF2BPs with Preferred RNA Motif Having m6A Through Dynamics Simulation Studies.

m6A modification is the most common internal modification of messenger RNA in eukaryotes, and the disorder of m6A can trigger cancer progression. The GGACU is considered the most frequent consensus sequence of target transcripts which have a GGAC m6A core motif. Newly identified m6A 'readers' insulin-like growth factor 2 mRNA-binding proteins modulate gene expression by binding to the m6A binding sites of target mRNAs, thereby affecting various cancer-related processes. The dynamic impact of the methylation at m6A within the GGAC motif on human IGF2BPs has not been investigated at the structural level. In this study, through in silico analysis, we mapped IGF2BPs binding sites for the GGm6AC RNA core motif of target mRNAs. Subsequent molecular dynamics simulation analysis at 400 ns revealed that only the KH4 domain of IGF2BP1, containing the 503GKGG506 motif and its periphery residues, was involved in the interaction with the GGm6AC backbone. Meanwhile, the methyl group of m6A is accommodated by a shallow hydrophobic cradle formed by hydrophobic residues. Interestingly, in IGF2BP2 and IGF2BP3 complexes, the RNA was observed to shift from the KH4 domain to the KH3 domain in the simulation at 400 ns, indicating a distinct dynamic behavior. This suggests a conformational stabilization upon binding, likely essential for the functional interactions involving the KH3-4 domains. These findings highlight the potential of targeting IGF2BPs' interactions with m6A modifications for the development of novel oncological therapies.