Docking Simulations Research Articles

Elucidating the binding dynamics and structural impacts of Pt(II) and Pd(II) complexes on human serum albumin: A comprehensive spectroscopic and computational study

The binding of drugs to plasma proteins, such as human serum albumin (HSA), encompasses two main functions: depot and transport, which are performed by these proteins. This binding has significant pharmacodynamic and pharmacokinetic consequences. 2-(furan-2-yl)-1H-imidazo[4,5-f][1,10]phenanthroline 1,2-diamino cyclohexane platinum (Pt(II)) or palladium (Pd(II)) complexes, have a similar structure. These new synthetic complexes have desirable anticancer activity, and the binding of these complexes with HSA was investigated. Spectroscopic and thermodynamic analyses indicate that the interactions between HSA and the complexes occur spontaneously with the static-dynamic quenching mechanism. However, the interactions are primarily driven by noncovalent forces such as hydrophobic interactions and π–π stacking, as evidenced by the positive enthalpy and entropy values associated with these complexes. In the circular dichroism (CD) results, HSA had fewer structural changes with the addition of the Pt(II) than the Pd(II) complex. Docking studies were performed at three Sudlow sites, I, II, and III, to identify the complex’s binding site on HSA. The reactive sites of HSA to Pt(II) and Pd(II) complexes mainly reside within its hydrophobic cavity in domain II (site II). Furthermore, molecular dynamics simulations showed low RMSD, Rg, and binding energy values during the 400 ns for the Pt(II) complex. The results suggest that the connection between the Pt(II) complex and HSA is reversible. The Pt(II) complex was a more desirable candidate than the Pd(II) complex. The results of the experimental methods are consistent with those of dynamic simulation and molecular docking methods, indicating that HSA is more stable in the presence of the Pt(II) complex.

A comprehensive investigation of the nano-[Cu2-(DIP)2-EA] effects on HSA through spectroscopic procedures and computer simulations

In this research, the toxicity of nano-[Cu2-(DIP)2-EA], a metal nano-complex consisting of ellagic acid and bathophenanthroline ligands, on human serum albumin (HSA) at a protein level was investigated. Molecular docking simulations and spectral analyses were conducted in a simulated physiological environment at pH 7.4 to explore the interaction of nano-[Cu2-(DIP)2-EA] with HSA. The results represented an increase in albumin absorption upon exposure to nano-[Cu2-(DIP)2-EA], demonstrating significant interaction between the two compounds. Steady-state and time-resolved fluorescence measurements pointed out that nano-[Cu2-(DIP)2-EA] induced static quenching of the albumin's intrinsic fluorescence with a high binding affinity of approximately 106 mol/L in a 1:1 interaction ratio. The thermodynamic variables clarified that binding of nano-[Cu2-(DIP)2-EA] to albumin occurs spontaneously and primarily driven by van der Waals interactions and H-bonds. The results of the computer simulations and the binding displacement experiments utilizing the site markers warfarin and ibuprofen revealed that nano-[Cu2-(DIP)2-EA] binds to site I within the subdomain IIA of albumin. Circular dichroism analysis elaborated that nano-[Cu2-(DIP)2-EA] slightly perturbed the microenvironment around of tryptophan residues and diminished the α-helix structure stability to a negligible amount.

The potency of bioactive constituents in Piper betle L. for Alzheimer Targeting on Caspase-3: in silico studies

Alzheimer’s disease (AD) is a neurodegenerative condition that can disrupt memory, cognition, and neurological functions, Recent studies highlight caspase-3 as a potential target, with several lines of evidence pointing to the enzyme's possible role in the onset of AD. Several findings revealed that betel leaf was also examined to treat AD by targeting acetylcholinesterase in vitro and in silico, yet no evaluation had not been done in caspase-3 activity. Using molecular docking, Lipinski's and PreADMET prediction, an in-silico analysis of compounds found in betel leaf (Piper betle L.) was conducted in order to determine whether these compounds could be applied as therapeutic candidates in the treatment of Alzheimer's. To ascertain the drug similarity and ADMET profile of the evaluated ligands, the Mcule and PreADMET sites were used in the studies, which were followed by the molecular docking simulation software AutoDock. The findings demonstrated that all the tested compounds passed the physicochemical features based on Lipinski rule. Further analysis then showed that arecoline bound to the critical amino acid that involved in caspase-3 inhibition. Further evaluation needs to be done to confirm the molecular mechanism of P. betle leaves to AD.

Identification of Aurora A kinase allosteric inhibitors: A comprehensive virtual screening through fingerprint-based similarity search, molecular docking, machine learning and molecular dynamics simulation

The Aurora A kinase (AAK) protein controls spindle assembly and promotes cell divisions in various diseases including cancer. In the present study, allosteric inhibition of AAK protein through different advanced computational screening approaches is employed to target AAK’s allosteric inhibition-modulation. Precisely, extensive computational techniques including allosteric binding sites recognition of AAK protein, fingerprint-based similarity search, multi-step molecular docking through AutoDock Vina and PLANTS, and a 100 ns molecular dynamics (MD) simulations studies were carried out followed by the calculation of binding free energy with MM-GBSA based approaches, has been employed for identification of potential allosteric inhibitors-modulators of AAK protein. The study outcome highlighted that all three identified small molecular chemical entities exhibit strong binding interaction affinity in both the docking analyses at the allosteric domain of AAK protein and also greater interaction stability in comparison to the considered standard compound. In addition, all identified three screened hits also show acceptable pharmacokinetics and medicinal chemistry properties, which certainly dictates their potentiality for becoming good drug-like compounds for inhibiting-modulating the activity of AAK protein binds with similar amino acids of the allosteric domain of AAK protein with selected three compounds. All the selected molecules were found to show an acceptable ADMET profile. Moreover, the MM-GBSA-based binding energy was found to be in the range of −8 to −35 Kcal/mol, which showed a strong association between proposed molecules and AAK protein. Comprehensive computational approach shows that the selected proposed three inhibitors of AAK protein are the best candidates as potential inhibitors.

Molecular mechanism of Dang-Shen-Yu-Xing decoction against Mycoplasma bovis pneumonia based on network pharmacology, molecular docking, molecular dynamics simulations and experimental verification.

Mycoplasma bovis pneumonia is a highly contagious respiratory infection caused by Mycoplasma bovis. It is particularly prevalent in calves, posing a significant threat to animal health and leading to substantial economic losses. Dang-Shen-Yu-Xing decoction is often used to treat this condition in veterinary clinics. It exhibits robust anti-inflammatory effects and can alleviate pulmonary fibrosis. However, its mechanism of action remains unclear. Therefore, this study aimed to preliminarily explore the molecular mechanism of Dang-Shen-Yu-Xing decoction for treating mycoplasma pneumonia in calves through a combination of network pharmacology, molecular docking, molecular dynamics simulation methods, and experimental validation. The active components and related targets of Dang-Shen-Yu-Xing decoction were extracted from several public databases. Additionally, complex interactions between drugs and targets were explored through network topology, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. Subsequently, the binding affinity of drug to disease-related targets was verified through molecular docking and molecular dynamics simulation. Finally, the pharmacodynamics were verified via animal experiments. The primary network topology analysis revealed two core targets and 10 key active components of Dang-Shen-Yu-Xing decoction against Mycoplasma bovis pneumonia. Kyoto Encyclopedia of Genes and Genomes enrichment analysis showed that the mechanism of Dang-Shen-Yu-Xing decoction for treating mycoplasma bovis pneumonia involved multiple signaling pathways, with the main pathways including PI3K-Akt and IL17 signaling pathways. Moreover, molecular docking predicted the binding affinity and conformation of the core targets of Dang-Shen-Yu-Xing decoction, IL6, and IL10, with the associated main active ingredients. The results showed a strong binding of the active ingredients to the hub target. Further, molecular docking dynamics simulation revealed three key active components of IL10 induced by Dang-Shen-Yu-Xing decoction against Mycoplasma bovis pneumonia. Finally, animal experiments confirmed Dang-Shen-Yu-Xing decoction pharmacodynamics, suggesting that it holds potential as an alternative therapy for treating mycoplasma bovis pneumonia.

Molecular Docking and Dynamic Simulation Approach to Target Penicillin-Binding Protein 1B (LpoB) of Salmonella typhimurium with Flavonoids

Background and Objective: Lipopolysaccharide (LPS) is an essential constituent of the outer membrane of gram-negative bacteria, such as Salmonella typhimurium, and it plays a crucial role by inducing disease in the host. Penicillin-binding protein 1B (LpoB) is a key enzyme in the production of peptidoglycans, making it a potential target for the development of new antimicrobials. Flavonoids are naturally occurring plant-derived chemicals with a wide range of pharmacological properties, including antibacterial capabilities. The goal of this study was to identify the potential flavonoid that inhibits the protein LpoB using computational approaches and compare it with the standard antibiotic ciprofloxacin. Methods: The study was carried out by selecting fifty flavonoids based on Lipinski’s rule of five. Molecular docking was carried out for selected flavonoids and ciprofloxacin against the LpoB protein using AutoDock 4. A 100 nanosecond molecular dynamic simulation was performed for apoprotein, LopB-fisetin, and LpoB-ciprofloxacin complexes, followed by free energy calculation by Molecular Mechanics Generalized Born Surface Area (MMGBSA) solvation analysis. Results: The docking results revealed that fisetin displayed five hydrogen bonds with a binding affinity of -4.67 kcal/mol, and ciprofloxacin exhibited a binding affinity of -4.36 kcal/mol with two hydrogen bonds. The apoprotein and fisetin complex remained stable throughout the 100 ns molecular dynamic simulation, while the ciprofloxacin complex lost its stability. The MMGBSA analysis with fisetin showed better binding free energy compared to ciprofloxacin. Conclusion: The present study has emphasized the potential of flavonoids as probable candidates that can inhibit the protein LpoB. The integration of molecular docking, dynamic simulations, and MMGBSA analysis has provided significant insight into the thermodynamics and binding interactions of the LpoB- fisetin complex, and it has enabled further experimental validations.

Novel benzothiazole/benzothiazole thiazolidine-2,4-dione derivatives as potential FOXM1 inhibitors: In silico, synthesis, and in vitro studies.

The oncogenic transcription factor FOXM1 overexpressed in breast and other solid cancers, is a key driver of tumor growth and progression through complex interactions, making it an attractive molecular target for the development of targeted therapies. Despite the availability of small-molecule inhibitors, their limited specificity, potency, and efficacy hinder clinical translation. To identify effective FOXM1 inhibitors, we synthesized novel benzothiazole derivatives (KC10-KC13) and benzothiazole hybrids with thiazolidine-2,4-dione (KC21-KC36). These compounds were evaluated for FOXM1 inhibition. Molecular docking and molecular dynamics simulation analysis revealed their binding patterns and affinities for the FOXM1-DNA binding domain. The interactions with key amino acids such as Asn283, His287, and Arg286, crucial for FOXM1 inhibition, have been determined with the synthesized compounds. Additionally, the molecular modeling study indicated that KC12, KC21, and KC30 aligned structurally and interacted similarly to the reference compound FDI-6. In vitro studies with the MDA-MB-231 breast cancer cell line demonstrated that KC12, KC21, and KC30 significantly inhibited FOXM1, showing greater potency than FDI-6, with IC50 values of 6.13, 10.77, and 12.86 µM, respectively, versus 20.79 µM for FDI-6. Our findings suggest that KC12, KC21, and KC30 exhibit strong activity as FOXM1 inhibitors and may be suitable for in vivo animal studies.

In silico design and ADMET evaluation of new inhibitors for PIM1 kinase using QSAR studies, molecular docking, and molecular dynamic simulation

The proviral Integration site of Moloney (PIM) kinase is highly expressed in various diseases, including cancer, making the development of selective inhibitors for this protein important. A series of PIM1 inhibitors, triazolo [4, 3-b] pyridazin-3-yl-quinoline derivatives, have been studied to design new inhibitors. The activity and structural features of these derivatives were investigated to understand their interactions with PIM1 using molecular docking, molecular dynamic simulation, and QSAR techniques.In a study of 30 compounds using the structure-activity technique and the MLR method, a linear model with R2train = 0.91 and R2test = 0.96 was obtained. The model utilized descriptors such as RDF080v, RDF105v, RDF135v, Mor03v, and H046 to express the structural characteristics of the inhibitors. To enhance the model, the SVR non-linear method with the RBF function was also used, resulting in an improved model with R2train = 0.98 and R2test = 0.98.Furthermore, the molecular docking technique was employed to investigate the interaction of compounds with high (compound 25) and low (compound 13) inhibitory activity. It was observed that the rings with nitrogen atoms interacted with the protein. The molecular binding results indicate that groups such as OMe and rings with Nitrogen can enhance the inhibitory activity of the compounds. Additionally, oxygen and nitrogen atoms contribute to an increased number of hydrogen bonds, thereby increasing the inhibitory activity of the compounds.Additionally, the stability and bonding modes of active and inactive compounds were studied using molecular dynamic simulation. Based on the results, four new inhibitors were designed, demonstrating better inhibition efficiency with the PIM1 kinase compared to the reference compounds. Moreover, the designed compounds underwent evaluation for ADMET, yielding promising results.

Evaluation of inhibition effect and interaction mechanism of antiviral drugs on main protease of novel coronavirus: Molecular docking and molecular dynamics studies

The outbreak of pneumonia caused by the novel coronavirus (SARS-CoV-2) has presented a challenge to public health. The identification and development of effective antiviral drugs is essential. The main protease (3CLpro) plays an important role in the viral replication of SARS-CoV-2 and is considered to be an effective therapeutic target. In this study, according to the principle of drug repurposing, a variety of antiviral drugs commonly used were studied by molecular docking and molecular dynamics (MD) simulations to obtain potential inhibitors of main proteases. 24 antiviral drugs were docked with 5 potential action sites of 3CLpro, and the drugs with high binding strength were further simulated by MD and the molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) binding free energy calculations. The results showed that the drugs with high flexibility could bind to 3CLpro better than those with low flexibility. The interaction mechanism between antiviral drugs and main protease was analyzed in detail by calculating the root mean square displacement (RMSD), root mean square fluctuation (RMSF) and interaction residues properties. The results showed that the six drugs with high flexibility (Remdesivir, Simnotrelvir, Sofosbuvir, Ledipasvir, Indinavir and Raltegravir) had strong binding strength with 3CLpro, and the last four antiviral drugs can be used as potential candidates for main protease inhibitors.

Molecular docking and molecular dynamics simulation studies reveal repurposing I-Motif ligand as a promising protease inhibitor against SARS-CoV-2 variants

ABSTRACT The COVID-19 caused by the SARS-CoV-2 virus has escalated into a global pandemic, urgently necessitating effective treatments. Tremendous research of the SARS-CoV-2 main protease have enabled insight understanding of its mechanism and potential inhibitors. Due to its crucial role in viral replication, the protease is considered an attractive target for antiviral therapy. This study aimed to identify novel potent inhibitors of main protease protein by repurposing i-Motif (iM) binding compounds from the G4LDB database. iM ligands are known for their ability to stabilise iM structures in DNA, and their repurposing as protein inhibitors is an alternative therapeutic approach. To achieve this, we performed in silico studies with six iM binding compounds. Molecular docking, molecular dynamics (MD) simulations and MM/GBSA binding free energy analysis revealed favourable conformational stability and superior binding affinity of the three proposed iM ligands, including iML0042 (−59.91 ± 3.82 kcal/mol), iML0043 (−56.37 ± 3.87 kcal/mol), and iML0094 (−84.68 ± 3.40 kcal/mol), to SARS-CoV-2 Mpro variants compared to the reference inhibitor nirmatrelvir (−34.35 ± 3.74 kcal/mol). The results suggested that repurposing iM ligands as protease inhibitors is a promising strategy. Our findings revealed significant candidate inhibitors and are recommended for further development as potential protease inhibitors against SARS-CoV-2.

Molecular characterization and functional analysis of genes mediating emamectin benzoate action to the pinewood nematode (Bursaphelenchus xylophilus)

Emamectin benzoate (EB) is a highly effective and low-toxicity pesticide for the control of Bursaphelenchus xylophilus. However, its action mechanism in B. xylophilus has not yet been verified. Here, the genes (Bxy-glc-1, Bxy-glc-2, Bxy-glc-4, and Bxy-avr-14) encoding the glutamate-gated chloride channel (GluCl) of B. xylophilus were analysed and cloned. Functional validation of the target genes was conducted using RNAi and pathogenicity detection assays. The results of the bioinformatics analysis showed that the four GluCl genes contained the Cys-loop region and three transmembrane structural domains. Molecular docking and molecular dynamics simulation predictions revealed that BXY-GLC-2, BXY-GLC-4, and BXY-GLC-1 all had strong binding affinities to EB, and BXY-AVR-14 had no binding affinity to EB. The expression and in situ hybridisation of Bxy-glc-1, Bxy-glc-2, Bxy-glc-4, and Bxy-avr-14 was significantly higher in adult B. xylophilus than at other developmental stages. Interference of Bxy-glc-1, Bxy-glc-2, and Bxy-glc-4 significantly reduced adult mortality relative to the control group, and interference of Bxy-avr-14 did not have a significant on adult mortality. Adult mortality was lowest in the combined Bxy-glc-2 + Bxy-glc-4 treatment group, followed by the Bxy-glc-1 + Bxy-glc-2 and Bxy-glc-1 + Bxy-glc-4 groups. No significant changes were observed in the mortality rate of the Bxy-avr-14 group and the combination of the other three genes. The dsBxy-glc-1, dsBxy-glc-2, and dsBxy-glc-4 groups accelerated the progression of pine wilt disease induced by EB relative to the sole EB-treated group. Our results confirmed that Bxy-glc-1, Bxy-glc-2, and Bxy-glc-4 are target genes of GluCl in B. xylophilus.

Real-time analysis of the biomolecular interaction between gelsolin and Aβ1-42 monomer and its implication for Alzheimer's disease

Biomolecular interaction acts a pivotal part in understanding the mechanisms underlying the development of Alzheimer's disease (AD). Herein, we built a biosensing platform to explore the interaction between gelsolin (GSN) and different β-amyloid protein 1-42 (Aβ1-42) species, including Aβ1-42 monomer (m-Aβ), Aβ1-42 oligomers with both low and high levels of aggregation (LLo-Aβ and HLo-Aβ) via dual polarization interferometry (DPI). Real-time molecular interaction process and kinetic analysis showed that m-Aβ had the strongest affinity and specificity with GSN compared with LLo-Aβ and HLo-Aβ. The impact of GSN on inhibiting aggregation of Aβ1-42 and solubilizing Aβ1-42 aggregates was evaluated by circular dichroism (CD) spectroscopy. The maintenance of random coil structure of m-Aβ and the reversal of β-sheet structure in HLo-Aβ were observed, demonstrating the beneficial effects of GSN on preventing Aβ from aggregation. In addition, the structure of m-Aβ/GSN complex was analyzed in detail by molecular dynamics (MD) simulation and molecular docking. The specific binding sites and crucial intermolecular forces were identified, which are believed to stabilize m-Aβ in its soluble state and to inhibit the fibrilization of Aβ1-42. Combined theoretical simulations and experiment results, we speculate that the success of GSN sequestration mechanism and the balance of GSN levels in cerebrospinal fluid and plasma of AD subjects may contribute to a delay in AD progression. This research not only unveils the molecular basis of the interaction between GSN and Aβ1-42, but also provides clues to understanding the crucial functions of GSN in AD and drives the development of AD drugs and therapeutic approaches.

Green synthesis and antimicrobial evaluation of Ag/TiO2 and Ag/SeO2 Core-Shell nanocomposites using r. Officinalis extract: A combined experimental and docking study

The escalating threat of antibiotic resistance necessitates the development of novel, sustainable antibacterial agents. This study investigates the potential of utilizing Rosmarinus officinalis leaf extracts to synthesize Ag/TiO2 and Ag/SeO2 nanocomposites. R. officinalis extract, a rich source of phenolic and flavonoid compounds, effectively and safely acts as a reducing and capping agent for the green synthesis of Ag/TiO2 and Ag/SeO2 nanocomposites. Characterization of nanocomposites revealed the nanoparticles’ nanoscale size, ranging from 43.34 to 96.58 nm for Ag/TiO2 and 8.04 to 21.72 nm for Ag/SeO2. Both types of nanoparticles exhibited a spherical morphology and distinct crystalline structure. The nanoparticles demonstrated significant antibacterial properties against multiple bacterial strains. The effective concentration for antibacterial activity was determined to be 30.99 mg/mL for Ag-TiO2 and 32.41 mg/mL for Ag-SeO2 nanoparticles. The surface charge of the nanoparticles was measured to be −14.0 mV for Ag-TiO2 and −15.4 mV for Ag/SeO2. Molecular docking simulations investigated the interactions between rosmarinic acid, its derivatives, and the antibiotic cefotaxime with a bacterial protein (e.g., DNA gyrase). These simulations provided insights into the distinct antibacterial mechanisms of these compounds. Briefly, this research highlights the potential of R. officinalis-derived nanocomposites as promising antibacterial agents. The eco-friendly synthesis and promising results pave the way for their development and application in medicine, biochemistry, and environmental fields.

Approaching Pharmacological Space: Events and Components.

The pharmacological space comprises all the dynamic events that determine the bioactivity (and/or the metabolism and toxicity) of a given ligand. The pharmacological space accounts for the structural flexibility and property variability of the two interacting molecules as well as for the mutual adaptability characterizing their molecular recognition process. The dynamic behavior of all these events can be described by a set of possible states (e.g., conformations, binding modes, isomeric forms) that the simulated systems can assume. For each monitored state, a set of state-dependent ligand- and structure-based descriptors can be calculated. Instead of considering only the most probable state (as routinely done), the pharmacological space proposes to consider all the monitored states. For each state-dependent descriptor, the corresponding space can be evaluated by calculating various dynamic parameters such as mean and range values.The reviewed examples emphasize that the pharmacological space can find fruitful applications in structure-based virtual screening as well as in toxicity prediction. In detail, in all reported examples, the inclusion of the pharmacological space parameters enhances the resulting performances. Beneficial effects are obtained by combining both different binding modes to account for ligand mobility and different target structures to account for protein flexibility/adaptability.The proposed computational workflow that combines docking simulations and rescoring analyses to enrich the arsenal of docking-based descriptors revealed a general applicability regardless of the considered target and utilized docking engine. Finally, the EFO approach that generates consensus models by linearly combining various descriptors yielded highly performing models in all discussed virtual screening campaigns.

Optical control of butyrylcholinesterase (BChE) activity via photoswitchable azobenzene for potential treatment of Alzheimer’s disease

Photopharmacology is an emerging method in medicinal chemistry to achieve light-controlled drug activity. Azobenzene-based photoswitchable ligands have found widespread application as chemical tools in photopharmacological studies. This study pioneers the design and synthesis of a novel series of photoswitchabled butyrylcholinesterase (BChE) inhibitors, achieved by strategically integrating an azo moiety into an N-benzyl benzamide scaffold. Through a meticulous investigation of the structure–activity relationship (SAR), we discovered that the lead compound, Azo-9, exhibits dynamic cis/trans conformational shifts, dynamically modulating its BChE-binding efficacy. This unique property translates into potential therapeutic benefits, including neuroprotection and cognitive enhancement. Complementary molecular docking simulations underscored the preferential binding of the cis-isomer of Azo-9 to BChE, which was subsequently validated in a glutamate-mediated neuronal injury model. Collectively, Azo-9 emerges as a promising precision tool for Alzheimer’s disease (AD) therapy, while also facilitating deeper insights into the disease’s underlying mechanisms.

Unraveling modulation effects on albumin synthesis and inflammation by Striatin, a bioactive protein fraction isolated from Channa striata: In silico proteomics and in vitro approaches

Hypoalbuminemia, associated with inflammation in severely ill patients, can emerge due to decreased albumin production. Transforming growth factor-beta (TGF-β) and nuclear factor-kappa B (NF-κB) are critical signaling pathways responsible for decreased albumin expression. This study explores the protein content and modulation effects of Striatin on albumin synthesis and inflammation, employing in silico proteomics and in vitro investigations. In the in silico proteomics realm, LC/MS-MS protein sequencing, 3D modeling, protein-protein docking simulations, 100 ns molecular dynamics (MD) simulations, and MM/PBSA binding free energy calculations were carried out. Complementing this, in vitro studies examined Albumin gene expression and extracellular secretion in HepG2 cells subjected to lipopolysaccharides-induced hypoalbuminemia. Furthermore, the study probed Striatin's influence on the NF-ᴋB expression, given albumin's role as a negative acute-phase protein. The results unveiled nucleoside diphosphate kinase (NdK) and parvalbumin (PV) as the prominent constituents within Striatin. Notably, NdK and PV exhibited the ability to disrupt hydrogen bonds with specific residues in both TGF-β and NF-κB complexes, thereby enhancing their flexibility, akin to the action of the FKBP12 complex (antagonist complex). In the in vitro experiments, Striatin demonstrated a dose and time-dependent inhibition of hypoalbuminemia, with peak efficacy observed at a concentration of 20 μg/mL. At this concentration, Striatin also suppressed NF-κB expression when co-incubated with lipopolysaccharides. While these findings suggest potential inhibitory effects of Striatin on TGF-β and NF-κB activities, they are preliminary and warrant further investigation. This study highlights Striatin's potential as a therapeutic agent for inflammation-related hypoalbuminemia, though additional research is needed to fully validate these results.

Pioneering bioinformatics with agent-based modelling: an innovative protocol to accurately forecast skin or respiratory allergic reactions to chemical sensitizers.

The assessment of theallergenic potential of chemicals, crucial for ensuring public health safety, faces challenges in accuracy and raises ethical concerns due to reliance on animal testing. This paper presents a novel bioinformatic protocol designed to address the critical challenge of predicting immune responses to chemical sensitizers without the use of animal testing. The core innovation lies in the integration of advanced bioinformatics tools, including the Universal Immune System Simulator (UISS), which models detailed immune system dynamics. By leveraging data from structural predictions and docking simulations, our approach provides a more accurate and ethical method for chemical safety evaluations, especially in distinguishing between skin and respiratory sensitizers. Our approach integrates a comprehensive eight-step process, beginning with the meticulous collection of chemical and protein data from databases like PubChem and the Protein Data Bank. Following data acquisition, structural predictions are performed using cutting-edge tools such as AlphaFold to model proteins whose structures have not been previously elucidated. This structural information is then utilized in subsequent docking simulations, leveraging both ligand-protein and protein-protein interactions to predict how chemical compounds may trigger immune responses. The core novelty of our method lies in the application of UISS-an advanced agent-based modelling system that simulates detailed immune system dynamics. By inputting the results from earlier stages, including docking scores and potential epitope identifications, UISS meticulously forecasts the type and severity of immune responses, distinguishing between Th1-mediated skin and Th2-mediated respiratory allergic reactions. This ability to predict distinct immune pathways is a crucial advance over current methods, which often cannot differentiate between the sensitization mechanisms. To validate the accuracy and robustness of our approach, we applied the protocol to well-known sensitizers: 2,4-dinitrochlorobenzene for skin allergies and trimellitic anhydride for respiratory allergies. The results clearly demonstrate the protocol's ability to differentiate between these distinct immune responses, underscoring its potential for replacing traditional animal-based testing methods. The results not only support the potential of our method to replace animal testing in chemical safety assessments but also highlight its role in enhancing the understanding of chemical-induced immune reactions. Through this innovative integration of computational biology and immunological modelling, our protocol offers a transformative approach to toxicological evaluations, increasing the reliability of safety assessments.

Trajectory planning and automatic docking of LNG five-axis loading arm

PurposeIn response to the challenges posed by the conventional manual flange docking method in the LNG (Liquefied Natural Gas) loading process, such as low positioning accuracy, constraints on production efficiency and safety hazards, this study analyzed the LNG five-axis loading arm’s main functions and structural characteristics.Design/methodology/approachAn automated solution for the joints of the LNG loading arm was designed. The forward kinematic model of the LNG loading arm was established using the Denavit–Hartenberg (D-H) parameter method, and its workspace was analyzed. The Newton–Raphson iteration method was employed to solve the inverse kinematics of the LNG loading arm, facilitating trajectory planning. The relationship between the target position and the joint variables was established to verify the stability of the arm’s motion. Flange center identification was achieved using the Hough transform function. Based on the ROS platform, combined with Gazebo and Rviz, an experimental simulation of automatic docking of the LNG loading arm was conducted.FindingsThe docking errors in the XYZ directions were all less than 0.8 mm, meeting the required docking accuracy. Moreover, the motion performance of the loading arm during docking was smooth and free of abrupt changes, validating its capability to accomplish the automatic docking task.Originality/valueThe proposed trajectory planning and automatic docking scheme can be used for the rapid filling of LNG filling arms and LNG tankers to improve the efficiency of LNG transportation. In guiding the docking, the proposed automatic docking scheme is an accurate and efficient way to improve safety.

Utilizing Cinnamomum verum (a culinary spice), as a functional food ingredient ameliorating hypercholesterolemia: In-vivo, in-vitro, and in-silico multi-model analysis

Hypercholesterolemia involves elevated levels of total cholesterol (T.C.), low-density lipoprotein (LDL), very low-density lipoprotein (VLDL), and reduced high-density lipoprotein (HDL), linked to sedentary lifestyles, irregular eating habits, high-fat diets, type 2 diabetes, and various hereditary and environmental factors. It poses significant health risks, including high blood pressure, atherosclerosis, fatty liver, and cardiovascular disease. This study aimed to evaluate the lipid-lowering effects of ethanolic extract of Cinnamon in hypercholesterolemia-induced rats using in-vivo, in-vitro, and in-silico approaches. In the present work, thirty female Albino rats were divided into six groups: Group I (basal diet), Group II (high-fat diet), Group III (statin treatment), and Groups IV-VI (high-fat diet with different doses of cinnamon extract). Serum lipid profiles were measured after four weeks of treatment. In-vitro HMG-CoA reductase inhibition was assessed. In-silico studies, including molecular docking, ADME analysis, toxicity prediction, and molecular dynamics (M.D.) simulations, were conducted. DFT studies with MESP/HOMO/LUMO analysis provided electronic property insights. High-fat diet increased body weight and serum lipid levels in rats. Cinnamon extract significantly reduces body weight and serum LDL, VLDL, and triglycerides while increasing HDL levels. Histopathology showed reduced fat accumulation and normal liver morphology in cinnamon-treated groups. In-vitro analysis revealed significant HMG-CoA reductase inhibition by cinnamon extract. In-silico docking confirmed strong binding affinities of cinnamon compounds to HMG-CoA reductase. ADME analysis and toxicity prediction indicated favorable pharmacokinetics. MD simulations showed stable ligand-protein complexes, and DFT studies highlighted the electronic properties of active compounds. To conclude, the cinnamon ethanolic extract demonstrated effective lipid-lowering properties in hypercholesterolemic rats, supported by in-vitro and in-silico analyses, suggesting its potential as a therapeutic agent for hypercholesterolemia. Further research is needed to explore underlying mechanisms and clinical outcomes.

Computational insights into the inhibitory mechanism of type 2 diabetes mellitus by bioactive components of Oryza sativa L. indica (black rice).

Type 2 diabetes mellitus is a metabolic disease categorized by hyperglycemia, resistance to insulin, and ß-cell dysfunction. Around the globe, approximately 422 million people have diabetes, out of which 1.5million die annually. In spite of innovative advancements in the treatment of diabetes, no biological drug has been known to successfully cure and avert its progression. Thereupon, natural drugs derived from plants are emerging as a novel therapeutic strategy to combat diseases like diabetes. The current study aims to investigate the antidiabetic potential of natural compounds of Oryza sativa L. indica (black rice) in disease treatment. Antioxidant activity and alpha amylase assays were performed to evaluate the therapeutic potential of the extract of Oryza sativa L. indica. Gas chromatography-mass spectrometry (GC-MS) was used for identification of constituents from the ethanol extract. ADMET profiling (absorption, distribution, metabolism, excretion, and toxicity), network pharmacology, and molecular dynamics simulation were employed in order to uncover the active ingredients and their therapeutic targets in O. sativa L. indica against type 2 diabetes mellitus. GC-MS of the plant extract provided a list of 184 compounds. Lipinski filter and toxicity parameters screened out 18 compounds. The topological parameters of the protein-protein interaction (PPI) were used to shortlist the nine key proteins (STAT3, HSP90AA1, AKT1, SRC, ESR1, MAPK1, NFKB1, EP300, and CREBBP) in the type 2 diabetes mellitus pathways. Later, molecular docking analysis and simulations showed that C14 (1H-purine-8-propanoic acid, .alpha.-amino-2, 3, 6, 7-tetrahydro-1,3,7-trimethyl-2,6-dioxo-) and C18 (cyclohexane-carboxamide, N-furfuryl) bind with AKT1 and ESR1 with a binding energy of 8.1, 6.9, 7.3, and 7.2kcal/mol, respectively. RMSD (root-mean-square deviation) and RMSF (root-mean-square fluctuation) values for AKT1 and ESR1 have shown very little fluctuation, indicating that proteins were stabilized after ligand docking. This study suggests therapeutic drug candidates against AKT1 and ESR1 to treat type 2 diabetes mellitus. However, further wet-lab analysis is required to discover the best remedy for type 2 diabetes mellitus.