Molecular Dynamics Simulation Analysis Research Articles

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.

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.

In Silico Approach for Assessment of the Anti-tumor Potential of Cannabinoid Compounds by Targeting Glucose-6-Phosphate Dehydrogenase Enzyme.

Glucose-6-phosphate dehydrogenase (G6PD) is a pentose phosphate pathway (PPP) enzyme that generates NADPH, which is required for cellular redox equilibrium and reductive biosynthesis. It has been demonstrated that abnormal G6PD activation promotes cancer cell proliferation and metastasis. To date, no G6PD inhibitor has passed clinical testing successfully enough to be launched as a medicine. As a result, in this investigation, cannabinoids were chosen to evaluate their anticancer potential by targeting G6PD. Molecular docking indicated that three molecules, Tetrahydrocannabinolic acid (THCA), Cannabichromenic acid (CBCA), and tetrahydrocannabivarin (THCV), have the highest binding affinities for G6PD of -8.61, -8.39, and 8.01 Kcal mol. ADMET analysis found that all of them were safe prospective drug candidates. Molecular dynamics (MD) simulation and MM-PBSA analysis confirm the structural compactness and lower conformational variation of protein-ligand complexes, thereby maintaining structural stability and rigidity. Thus, our in silico investigation exhibited all three cannabinoids as potential competitive inhibitors of G6PD.

Cheminformatic evaluation of the multi-protein binding potential of some diselenide derivatives: A plausible drug discovery approach for leishmaniasis

Over twelve million individuals worldwide suffer from leishmaniasis, and an additional billion people are at risk in places where the disease is prevalent. This work was motivated by the lack of vaccination against leishmaniasis and the shortcomings of current anti-leishmanial treatments. Large compound libraries can be screened using computational methods, which can also be used to analyze pharmacokinetic features, explore protein–ligand interactions, and quickly, accurately, and precisely create novel pharmacological entities. Virtual docking screening was performed to assess the multi-protein targeting capability of certain diselenides using four Leishmania protein targets—2XOX, 3SPX, 5ZWY, and 6K91. Following the Lipinski filter's screening of a subset of analogues, density functional theory (DFT), molecular dynamics (MD) simulation analysis, and ADMET profiles were used to profile the lead compounds. The overall average binding affinity of ligands to target proteins is as follows: 3SPX (− 184.998 kcal/mol) > 6K91 (− 180.114 kcal/mol) > 2XOX (− 176.581 kcal/mol) > 5ZWY (− 157.198 kcal/mol). The focus is on ligands that target all investigated proteins with binding scores greater than the average binding scores for the proteins as a whole for which seven compounds were identified that also showed higher MolDock scores than both reference drugs (Miltefosine and Pentamidine). Further screening showed four compounds (4, 7, 25, and 26) passed Lipinski’s test, making them orally bioavailable with excellent ADMET properties that compared well to both reference medications. The DFT analysis and MD simulation results indicate these compounds' favorability, stability, and reactivity in binding to the studied targets, 3SPX and 6K91 with 25_3SPX and 4_6K91 showing the highest binding free energy (MM-GBSA) of − 88.35 kcal/mol and − 90.29 kcal/mol respectively. Conclusively, the chosen diselenides could be developed as prospective anti-leishmanial pharmacological compounds or as useful scaffolds for creating more potent anti-leishmanial drugs.

Cheminformatics-driven prediction of BACE-1 inhibitors: Affinity and molecular mechanism exploration

The β-secretase, sometimes referred to as BACE1 or Asp2, is the enzyme responsible for initiating the production of Aβ by breaking down the amyloid precursor protein. Hence, BACE is a pivotal target for pharmacological intervention aimed at diminishing the production of Aβ in Alzheimer's disease (AD). We did a quantitative structure-activity relationship (QSAR) study on 1235 compounds that had been experimentally reported as BACE-1 inhibitors (Ki) to find the target molecule and structural patterns linked to blocking the BACE-1 receptor. The OECD-recommended genetic algorithm-multiple linear regression (GA-MLR) QSAR model strikes a good balance between being able to make accurate predictions and understanding how things work. It achieves high values for many evaluation metrics, including R2tr = 0.8047, Q2LMO = 0.802, R2ex = 0.805, CCCex = 0.891, Q2-F1=0.801, Q2-F2=0.799, and Q2-F3=0.815. The mechanistic interpretation of QSAR has identified some nitrogen atoms that are required to block beta-secretase and make it less effective at doing its job. A positively charged aromatic carbon atom has a more significant impact on beta-secretase-1 inhibition. The docking study showed that the catalytic dye residues Asp32 and Asp228 become protonated when compound 27 is present, but they stay unprotonated when compound 27 is not present. These rings of pyrazine and pyridine interact hydrophobically with Tyr71 and Ile118 residues, confirming the pharmacophoric features seen in the QSAR data. We examined the stability of both the protein-ligand complex and the apo-protein. The apoprotein had an average gyration radius of 22.13, whereas the protein-ligand complex had an average gyration radius of 22.91. No changes were made to the results from the molecular docking, molecular dynamics (MD) simulation, MMGBSA (Molecular Mechanics Generalized Born Surface Area), or DFT analyses. Therefore, the current work could effectively contribute to the future development of BACE inhibitors in medication design.

In silico docking, ADME/drug likeness and molecular dynamics simulation analysis of few phytoconstituents to identify potential inhibitor of PBP 4 of Staphylococcus aureus

In silico docking, ADME/drug likeness and molecular dynamics simulation analysis of few phytoconstituents to identify potential inhibitor of PBP 4 of Staphylococcus aureus

Overcoming methicillin resistance by methicillin-resistant Staphylococcus aureus: Computational evaluation of napthyridine and oxadiazoles compounds for potential dual inhibition of PBP-2a and FemA proteins

Abstract The treatment of the various infections caused by Staphylococcus aureus has become challenging due to the evolving resistance against current therapeutics. In this study, the potentials of napthyridine and oxadiazole derivatives to serve as dual inhibitors of penicillin-binding protein 2a (PBP-2a) and FemA protein, which are crucial to resistance to methicillin-based drugs by S. aureus, were evaluated using molecular modeling techniques. Seventy-two compounds were subjected to molecular docking against the proteins, and the hit compounds were subjected to drug-likeness evaluation and in silico pharmacokinetics prediction. The compounds with good safety profiles were subjected to a 250-ns molecular dynamics (MD) simulation and other relevant analyses based on the MD trajectories. Five hit compounds were selected based on their high affinity for the targets as evidenced by their docking scores ranging from −8.6 to −10.1 kcal/mol for PBP-2a and −9.6 to −9.9 kcal/mol for FemA. These compounds also passed Lipinski’s rule of five evaluation with no violation and possessed high human intestinal absorption potential, showcasing their potential as orally administered therapeutic agents. However, three of the compounds were potential mutagens. MD simulation revealed that the final two compounds maintained stable interactions with the target proteins over 250 ns, with minimal deviations and fluctuations. Hydrogen bond stability and energy decomposition analysis further confirmed the strong binding affinity of the hit compounds compared to the control drug, methicillin. Conclusively, the compounds with the CID “135964525” and “44130718” are worthy of further experimental validation in the development of potential inhibitors of PBP-2a and FemA.

Predicting the Mechanism of Tiannanxing-shengjiang Drug Pair in Treating Pain Using Network Pharmacology and Molecular Docking Technology.

This study aimed to analyze the potential targets and mechanism of the Tiannanxing-shengjiang drug pair in pain treatment using network pharmacology and molecular docking technology. The active components and target proteins of Tiannanxing-Shengjiang were obtained from the TCMSP database. The pain-related genes were acquired from the DisGeNET database. The common target genes between Tiannanxing-Shengjiang and pain were identified and subjected to the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analyses on the DAVID website. AutoDockTools and molecular dynamics simulation analysis were used to assess the binding of the components with the target proteins. Ten active components were screened out, such as stigmasterol, β-sitosterol, and dihydrocapsaicin. A total of 63 common targets between the drug and pain were identified. GO analysis showed the targets to be mainly associated with biological processes, such as inflammatory response and forward regulation of the EKR1 and EKR2 cascade. KEGG analysis revealed 53 enriched pathways, including pain-related calcium signaling, cholinergic synaptic signaling, and serotonergic pathway. Five compounds and 7 target proteins showed good binding affinities. These data suggest that Tiannanxing-shengjiang may alleviate pain through specific targets and signaling pathways. The active ingredients in Tiannanxing-shengjiang might alleviate pain by regulating genes, such as CNR1, ESR1, MAPK3, CYP3A4, JUN, and HDAC1 through the signaling pathways, including intracellular calcium ion conduction, cholinergic prominent signaling, and cancer signaling pathway.

Exploration of Pharmacological Mechanism of Cinnamomum tamala Essential Oil in Treating Inflammation based on Network Pharmacology, Molecular Modelling, and Experimental Validation.

Cinnamomum tamala (Buch.-Ham.) T.Nees & Eberm., also known as Indian Bay leaf, holds a distinctive position in complementary and alternative medicinal systems due to its anti-inflammatory properties. However, the active constituents and key molecular targets by which C. tamala essential oil (CTEO) exerts its anti-inflammatory action remain unclear. The present study used network pharmacology and experimental validation to investigate the mechanism of CTEO in the treatment of inflammation. GC-MS analysis was used to identify the constituents of CTEO. The key constituents and core targets of CTEO against inflammation were obtained by network pharmacology. The binding mechanism between the active compounds and inflammatory genes was ascertained by molecular docking and molecular dynamics simulation analysis. The pharmacological mechanism predicted by network pharmacology was verified in lipopolysaccharide-stimulated murine macrophage (RAW 264.7) cell lines. Forty-nine constituents were identified by GC-MS analysis, with 44 constituents being drug-like candidates. A total of 549 compounds and 213 inflammation-related genes were obtained, revealing 68 overlapping genes between them. Compound target network analysis revealed cinnamaldehyde as the core bioactive compound with the highest degree score. PPI network analysis demonstrated Il-1β, TNF-α, IL8, IL6 and TLR4 as key hub anti-inflammatory targets. KEGG enrichment analysis revealed a Toll-like receptor signalling pathway as the principally regulated pathway associated with inflammation. A molecular docking study showed that cinnamaldehyde strongly interacted with the Il-1β, TNF-α and TLR-4 proteins. Molecular dynamics simulations and MMPBSA analysis revealed that these complexes are stable without much deviation and have better free energy values. In cellular experiments, CTEO showed no cytotoxic effects on RAW 264.7 murine macrophages. The cells treated with LPS exhibited significant reductions in NO, PGE2, IL-6, TNF-α, and IL-1β levels following treatment with CTEO. Additionally, CTEO treatment reduced the ROS levels and increased the antioxidant enzymes such as SOD, GSH, GPx and CAT. Immunofluorescence analysis revealed that CTEO inhibited LPS-stimulated NF-κB nuclear translocation. The mRNA expression of TLR4, MyD88 and TRAF6 in the CTEO group decreased significantly compared to the LPS-treated group. The current findings suggest that CTEO attenuates inflammation by regulating TLR4/MyD88/NF- κB signalling pathway.

Phytochemical Analysis and Anti‐inflammatory Potential of Floscopa Scandens Lour. and Exploring Ecdysterone as Promising Therapeutic Agent: An HR‐LCMS Screening and Molecular Docking Analysis

AbstractThis study delved into the exploration of bioactive constituent profiling of Floscopa scandens Lour. by using HRLC‐MS. The plant is well‐known as a folklore herb. It is extensively utilized in traditional medicine to address various ailments such as fractures, sore eyes, fevers, abscesses, pyoderma, and acute nephritis. This study aimed to explore the phytochemical composition of F. scandens and assess the anti‐inflammatory activity of the ecdysterone marker compound by molecular docking studies followed by MD simulations. Extracts were prepared using hexane, chloroform, and methanol solvents. Chromatographic techniques were applied to isolate compounds from the methanol extract, which underwent phytochemical screening via HR‐LCMS. Functional groups were assessed using NMR and Fourier transform infrared (FTIR), confirming the presence of bioactive compounds. HR‐LCMS analysis identified 21 phytoconstituents in the methanolic fraction, with ecdysterone being a prominent component characterized through spectroscopic techniques. Our findings confirm known molecules while unveiling new bioactive constituents, particularly highlighting the potential of ecdysterone as a novel chemical entity. Molecular docking and molecular dynamic simulation analysis further show the anti‐inflammatory properties of ecdysterone with various enzymes in the body.

Investigating pH-induced Conformational Switch in PIM-1: An Integrated Multi Spectroscopic and MD Simulation Study

PIM-1 kinase, a Ser/Thr kinase, is 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 of PIM-1 across different pH levels using various spectroscopic techniques. Spectroscopic results indicate that PIM-1 maintains its secondary and tertiary structure within the pH range of 7.0 to 9.0. However, protein aggregation occurs in the acidic pH range of 5.0 to 6.0. Additionally, kinase assays suggested that PIM-1 activity is optimal within the pH range of 7.0 to 9.0. Subsequently, we performed a 100ns 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.

Computational investigation of Pluchea indica mechanism targeting peroxisome proliferator-activated receptor gamma

Introduction: Pluchea indica is known to have diverse pharmacological properties, including anti-inflammatory, antioxidant, antimicrobial, and anticancer activities. However, there is a pressing need to thoroughly investigate the molecular interactions between P. indica compounds and peroxisome proliferator-activated receptor gamma (PPARG). This study aimed to elucidate the molecular mechanisms behind P. indica and PPARG, and its potential implications for diabetes mellitus. Methods: The computational investigation employed Pharmacological Network pharmacology, homology modeling, deep learning docking, and molecular dynamics to explore the active compounds and targets within P. indica against the PPARG. Results: Three active compounds were identified namely pinoresinol, syringaresinol, and plucheoside A, all of which complied with the Lipinski rule of five. The deep learning-based pose scores were determined as follows: Pinoresinol 0.55, syringaresinol 0.32, and plucheoside A 0.44. Additionally, protein-protein interactions were observed with PPARG and associated with the PPAR signaling pathway. Molecular dynamics simulation analysis showed the stability of the three compounds over a 100 ns period. Free energy calculations using Molecular Mechanics-Generalized Born and Surface Area (MM-GBSA) yielded ΔG values of -44.39 kcal/mol, -51.83 kcal/mol, and -40.27 kcal/mol for pinoresinol, syringaresinol, and plucheoside A, respectively. Conclusion: Pluchea indica might be developed to treat various diseases, particularly those involving the PPARG signaling pathway. It suggests the possibility of being developed as a focused medication for diabetes.

Antioxidant Effect of Naringin Demonstrated Through a Bayes' Theorem Driven Multidisciplinary Approach Reveals its Prophylactic Potential as a Dietary Supplement for Ischemic Stroke.

Naringin (NAR), a flavanone glycoside, occurs widely in citrus fruits, vegetables, and alcoholic beverages. Despite evidence of the neuroprotective effects of NAR on animal models of ischemic stroke, brain cell-type-specific data about the antioxidant efficacy of NAR and possible protein targets of such beneficial effects are limited. Here, we demonstrate the brain cell type-specific prophylactic role of NAR, an FDA-listed food additive, in an in vitro oxygen-glucose deprivation (OGD) model of cerebral ischemia using MTT and DCFDA assays. Using Bayes' theorem-based predictive model, we first ranked the top-10 protein targets (ALDH2, ACAT1, CTSB, FASN, LDHA, PTGS1, CTSD, LGALS1, TARDBP, and CDK1) from a curated list of 289 NAR-interacting proteins in neurons that might be mediating its antioxidant effect in the OGD model. When preincubated with NAR for 2days, N2a and CTX-TNA2 cells could withstand up to 8h of OGD without a noticeable decrease in cell viability. This cerebroprotective effect is partly mediated by reducing intracellular ROS production in the above two brain cell types. The antioxidant effect of NAR was comparable with the equimolar (50µM) concentration of clinically used ROS-scavenger and neuroprotective edaravone. Molecular docking of NAR with the top-10 protein targets from Bayes' analysis showed the lowest binding energy for CDK1 (- 8.8kcal/M). Molecular dynamics simulation analysis showed that NAR acts by inhibiting CDK1 by stably occupying its ATP-binding cavity. Considering diet has been listed as a risk factor for stroke, NAR may be explored as a component of functional food for stroke or related neurological disorders.

Unsupervised Machine Learning in the Analysis of Nonadiabatic Molecular Dynamics Simulation.

The all-atomic full-dimensional-level simulations of nonadiabatic molecular dynamics (NAMD) in large realistic systems has received high research interest in recent years. However, such NAMD simulations normally generate an enormous amount of time-dependent high-dimensional data, leading to a significant challenge in result analyses. Based on unsupervised machine learning (ML) methods, considerable efforts were devoted to developing novel and easy-to-use analysis tools for the identification of photoinduced reaction channels and the comprehensive understanding of complicated molecular motions in NAMD simulations. Here, we tried to survey recent advances in this field, particularly to focus on how to use unsupervised ML methods to analyze the trajectory-based NAMD simulation results. Our purpose is to offer a comprehensive discussion on several essential components of this analysis protocol, including the selection of ML methods, the construction of molecular descriptors, the establishment of analytical frameworks, their advantages and limitations, and persistent challenges.

Comprehensive analysis of lignin dimer dissolution microscopic mechanism in different aromatic-based deep eutectic solvent

Aromatic-based deep eutectic solvent (DES) is a novel kind of DES that can dissolve lignin efficiently. Density functional (DFT) calculation, molecular dynamics (MD) simulation and multivariate analysis were used to investigate the interaction mechanism of five aromatic-based DES on two lignin dimer models. The effects of dissolution temperature and the type of aromatic hydrogen bond donor (HBD) on the breaking bonds between β-O-4 and 5–5 substructural units or interacting with different functional groups on lignin were investigated. With the introduction of DES, the electrostatic interaction between Cl- and lignin was obvious, while the van der Waals interaction between HBD, Ch+ and lignin was obvious. Among all the aromatic-based DES, choline chloride/p-hydroxybenzoic acid (ChCl/PB) is considered to have efficient dissolution effect. In the process of lignin dissolution, γ-OH was the preferred site for PB and Cl- acting on the lignin dimer (β-O-4), and the proportion of hydrogen bonding with γ-OH is 40 %. It was distributed around the lignin dimer (β-O-4) at 0.28–0.32 nm, and the total interaction energy was −4041.1452 kJ/mol. This study provided novel insights and theoretical basis for the preparation of renewable DES using aromatic components.