Root Mean Square Deviation Values Research Articles

Which one is more accurate, BILOG or R program? (a comparison for score test equating)

Evaluation may be carried out using different tests that are not necessarily parallel. Students with lower abilities may get higher scores while those with higher abilities get lower scores. Measurement errors caused by this condition require test equating. Several computer programs, including Bilog and the R program, can be used for test equating. Each program has a different level of accuracy, and the accuracy of the equating results will affect the standard errors of equating. This study aimed to find out the most accurate equating test method and the accuracy of the estimated BILOG and R program. This research used two sets of tests with equivalent group designs. The determination of the most accurate equating method was based on the root mean square deviation (RMSD) value. Equating test packages, A to package B with BILOG program estimation on the mean and Sigma method resulted in RMSD value of 0.320. In the mean and mean method, RMSD value is 0.250. Meanwhile, equating package A to package B using R program on the mean and sigma resulted in RMSD value of 0.300, and the mean and mean method with the RMSD value is 0.272. The mean and mean yield RMSD values smaller than the mean and sigma methods. Therefore, the mean and mean method is more accurate and applicable. Moreover, the estimation results of the BILOG program are more accurate and can be used in test equating.

UNIFAC PREDICTION OF VAPOR LIQUID EQUILIBRIA INVOLVING GAMMA-VALEROLACTONE DERIVATIVE SYSTEMS

Researchers have studied the hydrogenation of Gamma-Valerolactone (GVL) over Ru/C to produce 2-methyltetrahydrofuran (2-MTHF), a biomass-based platform chemical with potential as a biofuel and green solvent. Other byproducts of this reaction include 2-butanol (2-BuOH), 2-pentanol (2-PeOH), and 1,4-pentanediol (1,4-PDO). In this study, UNIFAC activity coefficient models were used to predict the vapor-liquid equilibrium of several systems included in the process to explain the phase behavior which is important in purification process. The accuracy of the UNIFAC model is tested by comparing the experimental boiling points for the binary system of 2-propanol + 1-butanol and the vapor-liquid equi-librium of the GVL + 2-MTHF system. From this comparison, the Root Mean Square Deviation (RMSD) values for the boiling point measurements are obtained to be 3.153%, and for the liquid and vapor phases in the vapor-liquid equilibrium measurements, the RMSD values are 1.934% and 0.298% respectively. These RMSD values indicate the level of accuracy of the UNIFAC model in representing the experimental data for both boiling point measurements and vapor-liquid equilibrium phase behavior. The prediction results of vapor-liquid equilibrium data for GVL derivative systems showed that the 2-BuOH + 2-MTHF system does form an azeotrope when the mol fraction of 2-BuOH is 0.0031 at 79.780C. The calculation was performed using ChemCAD commercial software for chemical process modeling and simulation

HSPiP, Computational, and Thermodynamic Model-Based Optimized Solvents for Subcutaneous Delivery of Tolterodine Tartrate and GastroPlus-Based In Vivo Prediction in Humans: Part I.

Tolterodine tartrate (TOTA) is associated with adverse effect, high hepatic access, varied bioavailability, slight aqueous solubility, and short half-life after oral delivery. Hansen solubility parameters (HSP, HSPiP program), experimental solubility (T = 298.2 to 318.2K and p = 0.1MPa), computational (van't Hoff and Apelblat models), and thermodynamic models were used to the select solvent(s). HSPiP predicted PEG400 as the most suitable co-solvent based on HSP values (δd = 17.88, δp = 4.0, and δh = 8.8 of PEG400) and comparable to the drug (δd = 17.6, δp = 2.4, and δh = 4.6 of TOTA). The experimental mole fraction solubility of TOTA was maximum (xe = 0.0852) in PEG400 confirming the best fit of the prediction. The observed highest solubility was attributed to the δp and δh interacting forces. The activity coefficient (ϒi) was found to be increased with temperature. The higher values of r2 (linear regression coefficient) and low RMSD (root mean square deviation) indicated a good correlation between the generated "xe" data for crystalline TOTA and the explored models (modified Apelblat and van't Hoff models). TOTA solubility in "PEG400 + water mixture" was endothermic and entropy-driven. IR (immediate release product) formulation can be tailored using 60% PEG400 in buffer solution for 2mg of TOTA in 0.25mL (dosing volume). The isotonic binary solution was associated with a pH of 7.2 suitable for sub-Q delivery. The approach would be a promising alternative with ease of delivery to children and aged patients.

Design, synthesis, and bioevaluation of novel unsaturated cyanoacetamide derivatives: In vitro and in silico exploration

In this study, we synthesized novel α,β-unsaturated 2-cyanoacetamide derivatives (1–5) using microwave-assisted Knoevenagel condensation. Characterization of these compounds was carried out using FTIR and 1H NMR spectroscopy. We then evaluated their in vitro antibacterial activity against both gram-positive and gram-negative pathogenic bacteria. Additionally, we employed in silico methods, including ADMET prediction and density functional theory (DFT) calculations of molecular orbital properties, to investigate these cyanoacetamide derivatives (1–5). Molecular docking was used to assess the binding interactions of these derivatives (1–5) with seven target proteins (5MM8, 4NZZ, 7FEQ, 5NIJ, ITM2, 6SE1, and 5GVZ) and compared them to the reference standard tyrphostin AG99. Notably, derivative 5 exhibited the most favorable binding affinity, with a binding energy of -7.7 kcal mol−1 when interacting with the staphylococcus aureus (PDB:5MM8), while also meeting all drug-likeness criteria. Additionally, molecular dynamics simulations were carried out to evaluate the stability of the interaction between the protein and ligand, utilizing parameters such as Root-Mean-Square Deviation (RMSD), Root-Mean-Square Fluctuation (RMSF), Radius of Gyration (Rg), and Principal Component Analysis (PCA). A 50 nanosecond molecular dynamics (MD) simulation was performed to investigate stability further, incorporating RMSD and RMSF analyses on compound 5 within the active binding site of the modeled protein across different temperatures (300, 305, 310, and 320 K). Among these temperatures, compound 5 exhibited an RMSD value ranging from approximately 0.2 to 0.3 nm at 310 K (body temperature) with the 5MM8 target, which differed from the other temperature conditions. The in silico results suggest that compound 5 maintained significant conformational stability throughout the 50 ns simulation period. It is consistent with its low docking energy and in vitro findings concerning α,β-unsaturated cyanoacetamides.Key insights from this study include:•The creation of innovative α,β-unsaturated 2-cyanoacetamide derivatives (1–5) employing cost-effective, licensed, versatile, and efficient software for both in silico and in vitro assessment of antibacterial activity.•Utilization of FTIR and NMR techniques for characterizing compounds 1–5.

Mammalian maltase-glucoamylase and sucrase-isomaltase inhibitory effects of Artocarpus heterophyllus: An in vitro and in silico approach

Alpha-glucosidase (maltase, sucrase, isomaltase and glucoamylase) activities which are involved in carbohydrate metabolism are present in human intestinal maltase-glucoamylase (MGAM) and sucrase-isomaltase (SI). Hence, these proteins are important targets to identify drugs against postprandial hyperglycemia thereby for diabetes. To find natural-based drugs against MGAM and SI, Artocarpus heterophyllus leaf was explored for MGAM and SI inhibition in in vitro and in silico. A. heterophyllus leaf aqueous active fraction (AHL-AAF) was prepared using Soxhlet extraction followed by silica column chromatography. The phytoconstituents of AHL-AAF were determined using LC-ESI-MS/MS. AHL-AAF showed dose-dependent and mixed inhibition against maltase (IC50 = 460 µg/ml; Ki = 300 µg/ml), glucoamylase (IC50 = 780 µg/ml; Ki = 480 µg/ml), sucrase (IC50 = 900 µg/ml, Ki = 504 µg/ml) and isomaltase (IC50 = 860 µg/ml, Ki = 400 µg/ml). AHL-AAF phytoconstituents interaction with N-terminal (Nt) and C-terminal (Ct) subunits of human MGAM and SI was analyzed using induced-fit docking, molecular dynamics (MD), and binding free energy calculation. In docking studies, rhamnosyl hexosyl methyl quercetin (RHMQ), P-coumaryl-O-16-hydroxy palmitic acid (PCHP), and spirostanol interacted with active site amino acids of human MGAM and SI. Among these RHMQ stably interacted with all the subunits (Nt-MGAM, Ct-MGAM, Nt-SI and Ct-SI) whereas PCHP with Ct-MGAM and Nt-SI during MD analysis. In molecular docking, the docking score of RHMQ with NtMGAM, CtMGAM, NtSI and CtSI was −8.48, −12.88, −11.98 and −11.37 kcal/mol. The docking score of PCHP for CtMGAM and NtSI was −8.59 and −8.4 kcal/mol, respectively. After MD simulation, the root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values further confirmed the stable protein-ligand interaction. The RMSD value of all the complexes were around 2.5 Å and the corresponding RMSF values were also quite low. In MM/GBSA analysis, the involvement of Van der Waals and lipophilic energy in the protein/ligand interactions are understood. Further binding free energy for Nt-MGAM-PCHP, Nt-MGAM-RHMQ, Nt-SI-PCHP, Nt-SI-RHMQ, Ct-MGAM-PCHP, Ct-MGAM-RHMQ and Ct-SI-RHMQ complexes was found to be −24.94, −46.60, −46.56, −44.48, −40.3, −41.86 and −19.39 kcal/mol, respectively. Altogether, AHL-AAF showed inhibition of α-glucosidase activities of MGAM and SI. AHL-AAF could be further studied for its effect on diabetes in in vivo.

Computational insights into KRAS G12C inhibition: exploring possible repurposing of Azacitidine and Ribavirin

Kirsten rat sarcoma (KRAS) stands out as the most prevalent mutated oncogene, playing a crucial role in the initiation and progression of various cancer types, including colorectal, lung and pancreatic cancer. The oncogenic modifications of KRAS are intricately linked to tumor development and are identified in 22% of cancer patients. This has spurred the necessity to explore inhibition mechanisms, with the aim of investigating and repurposing existing drugs for diagnosing cancers dependent on KRAS G12C In this investigation, 26 nucleoside-based drugs were collected from literature to assess their effectiveness against KRAS G12C. The study incorporates in-silico molecular simulations and molecular docking examinations of these nucleoside-derived drugs with the KRAS G12C protein using Protein Data Bank (PDB) ID: 5V71. The docking outcomes indicated that two drugs, Azacitidine and Ribavirin, exhibited substantial binding affinities of −8.7 and −8.3 kcal/mol, respectively. These drugs demonstrated stability in binding to the active site of the protein during simulation studies. Root mean square deviation (RMSD) analyses indicated that the complexes closely adhered to an equilibrium RMSD value ranging from 0.17 to 0.2 nm. Additionally, % occupancies, bond angles and the length of hydrogen bonds were calculated. These findings suggest that Azacitidine and Ribavirin may potentially serve as candidates for repurposing in individuals with KRAS-dependent cancers. Communicated by Ramaswamy H. Sarma

Determination of Novel SARS-CoV-2 Inhibitors by Combination of Machine Learning and Molecular Modeling Methods.

Within the scope of the project, this study aimed to find novel inhibitors by combining computational methods. In order to design inhibitors, it was aimed to produce molecules similar to the RdRp inhibitor drug Favipiravir by using the deep learning method. For this purpose, a Trained Neural Network (TNN) was used to produce 75 molecules similar to Favipiravir by using Simplified Molecular Input Line Entry System (SMILES) representations. The binding properties of molecules to Viral RNA-dependent RNA polymerase (RdRp) were studied by using molecular docking studies. To confirm the accuracy of this method, compounds were also tested against 3CL protease (3CLpro), which is another important enzyme for the progression of SARS-CoV-2. Compounds having better binding energies and RMSD values than favipiravir were searched with similarity analysis on the ChEMBL drug database in order to find similar structures with RdRp and 3CLpro inhibitory activities. A similarity search found new 200 potential RdRp and 3CLpro inhibitors structurally similar to produced molecules, and these compounds were again evaluated for their receptor interactions with molecular docking studies. Compounds showed better interaction with RdRp protease than 3CLpro. This result presented that artificial intelligence correctly produced structures similar to favipiravir that act more specifically as RdRp inhibitors. In addition, Lipinski's rules were applied to the molecules that showed the best interaction with RdRp, and 7 compounds were determined to be potential drug candidates. Among these compounds, a Molecular Dynamic simulation study was applied for ChEMBL ID:1193133 to better understand the existence and duration of the compound in the receptor site. The results confirmed that the ChEMBL ID:1193133 compound showed good Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), hydrogen bonding, and remaining time in the active site; therefore, it was considered that it could be active against the virus. This compound was also tested for antiviral activity, and it was determined that it did not delay viral infection, although it was cytotoxic between 5mg/mL-1.25mg/mL concentrations. However, if other compounds could be tested, it might provide a chance to obtain activity, and compounds should also be tested against the enzymes as well as the other types of viruses.

In silico simulation of hyperoside, isoquercetin, quercetin, and quercitrin as potential antivirals against the pNP868R protein of African swine fever virus.

African swine fever (ASF) causes disease in pigs with up to 100% mortality rates. There is no effective vaccine to protect against it. This study aimed to perform in silico docking of ASF virus (ASFV) pNP868R protein with potential flavonoid ligands to identify ligands that interfere with mRNA cap formation. The ASFV pNP868R protein was tested with hyperoside, isoquercetin, quercetin, and quercitrin in this in silico simulation. ASFV pNP868R protein was extracted from the Research Collaboration for Structural Bioinformatics Protein Data Bank (RCSB PDB) database with PDB ID 7D8U (https://www.rcsb.org/structure/7D8U). Standard ligands were separated from proteins using UCSF Chimera 1.13. The standard ligand was redocked to protein using AutoDockTools 1.5.6 with the AutoDock4 method for validation. In the docking process, the grid box size was 40 × 40 × 40 Å3 with x, y, and z coordinates of 16.433, -43.826, and -9.496, respectively. The molecular docking process of the proposed ligand-protein complex can proceed if the standard ligand position is not significantly different from its original position in the viral protein's pocket. The root mean square deviation (RMSD), root mean square fluctuation (RMSF), and radius of gyration (RoG) of the hyperoside with the lowest energy binding need to be analyzed with molecular dynamics using Groningen machine for chemical simulation 5.1.1. Molecular docking and dynamic simulation revealed that hyperoside had the most stable and compact binding to the pNP868R protein. Hyperoside binds to the protein at the minimum energy of -9.07 KJ/mol. The RMSD, RMSF, and RoG values of 0.281 nm, 0.2 nm, and 2.175 nm, respectively, indicate the stability and compactness of this binding. Hyperoside is the most likely antiviral candidate to bind to the pNP868R protein in silico. Therefore, it is necessary to test whether this flavonoid can inhibit mRNA capping in vitro and elicit the host immune response against uncapped viral mRNA.

Analysis of Molecular Docking and Dynamics Simulation of Mahogany (Swietenia macrophylla King) Compounds Against the PLpro Enzyme SARS-COV-2

Background: Using natural ingredients as antivirals can be considered a treatment for SARS-CoV-2. One of the potential plants, mahogany (Swietenia macrophylla King), is widely used in various countries as an antiviral treatment. Paparin-like protease (PLpro) is an essential cysteine ​​protease that regulates viral replication and interferes with the regulation of immune sensing. Objective: This study aims to predict which compounds in the mahogany plant have good affinity, patterns, and stability interaction against the target protein of SARS-CoV-2. Methods: The drug-likeness parameter using SwissADME was used to screen compounds that will be docked against PLpro using the Autodock program. The parameters observed in molecular docking analysis are the value of bond energy and interaction model to amino acid residues. The compounds in mahogany plants that have the best interactions were then analyzed using molecular dynamics simulation methods to determine the stability of their bonds based on the values of Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF). Results: Twenty-two compounds met the drug-likeness requirements. Molecular docking analysis showed that the compounds predicted to have the best binding affinity and have an interaction pattern similar to natural ligands towards the molecular target of PLpro are 7-deacetoxy-7-oxogedunin and 3β-hydroxy-stigmast-5-en-7-one. The molecular dynamics simulation results revealed that based on the RMSD and RMSF values, the compound 3β-hydroxy-stigmast-5-en-7-one showed higher stability than 7-deacetoxy-7-oxogedunin. Conclusion: 3β-hydroxy-stigmast-5-en-7-one and 7-deacetoxy-7-oxogedunin were predicted to have good interaction with PLPro; however, 3β-hydroxy-stigmast-5-en-7-one showed the higher interaction stability.

Novel computational and drug design strategies for the inhibition of human T-cell leukemia virus 1-associated lymphoma by Astilbin derivatives

Human T-cell leukemia virus 1 (HTLV-1) associated lymphoma is a devastating malignancy triggered by HTLV-1 infections. We employeda comprehensive drug design and computational strategy in this work to explore the inhibitory activitiesof Astilbin derivatives against HTLV-1-associated lymphoma. We evaluated the stability, binding affinities, and various computational analysis of Astilbin derivatives against target proteins, such as HTLV-1 main protease and HTLV-1 capsid protein. The root mean square deviation (RMSD), root mean square fluctuation, radius of gyration, hydrogen bond analysis, principal component analysis (PCA) and dynamic cross-correlation matrix (DCCM) were applied to characterize these protein–ligand interactions further. Ligand-03 and ligand-04 exhibited notable binding affinity to HTLV-1 capsid protein, while ligand-05 displayed high binding affinity to HTLV-1 protease. MD simulation analysis revealed that ligand-03, bound to HTLV-1 capsid protein, demonstrated enhanced stability with lower RMSD values and fewer conformational changes, suggesting a promising binding orientation. Ligand-04, despite stable binding, exhibited increased structural deviations, making it less suitable. Ligand-05 demonstrated stable binding to HTLV-1 protease throughout the simulation period at 100 nanoseconds. Hydrogen bond analysis indicated that ligand-05 formed persistent hydrogen bonds with significantresidues, contributing to its stability. PCA highlighted ligand-03's more remarkable conformational changes, while DCCM showed ligand-05's distinct dynamics, indicating its different behavior in the complex. Furthermore, binding free energy calculations supported the favorable interactions of ligand-03 and ligand-04 with HTLV-1 capsid protein, while ligand-05 showed weaker interactions with HTLV-1 protease. Molecular electrostatic potential and frontier molecular orbital analyses provided insights into these compounds’ charge distribution and stability. In conclusion, this research found Astilbin derivatives as potential inhibitors of HTLV-1-associated lymphoma. Future attempts at drug development will benefit from the steady interaction landscape provided by Ligand-03, Ligand-04 and Ligand-05, which showed the most attractive binding profile with the target protein. These results open up new opportunities for innovative drug development, and more experimental testing should be done between Astilbin derivatives and HTLV-1-associated lymphoma. Communicated by Ramaswamy H. Sarma

Molecular hybrids of substituted phenylcarbamoylpiperidine and 1,2,4-triazole methylacetamide as potent 15-LOX inhibitors: Design, synthesis, DFT calculations and molecular docking studies

Inflammation is a multifaceted phenomenon triggered by potentially active mediators acutely released arachidonic acid metabolites partially in lipoxygenase (LOX) pathway which are primarily accountable for causing several diseases in humans. It is widely believed that an inhibitor of the LOX pathway represents a rational approach for designing more potent antiinflammatory leads with druggable super safety profiles. In our continual efforts in search for anti-LOX molecules, the present work was to design a new series of N-alkyl/aralkyl/aryl derivatives (7a-o) of 4-phenyl-5-(1-phenylcarbamoylpiperidine)-4H-1,2,4-triazole-3-thiol which was commenced in seriate formation of phenylcarbamoyl derivative (1), hydrazide (2), semicarbazide (3) and 4-phenyl-5-(1-phenylcarbamoylpiperidine)-4H-1,2,4-triazole-3-thiol (4). The aimed compounds were obtained by reacting 4-phenyl-5-(1-phenylcarbamoylpiperidine)-4H-1,2,4-triazole-3-thiol with assorted N-alkyl/aralkyl/aryl electrophiles. All compounds were characterized by FTIR, 1H-, 13C-NMR spectroscopy, EI-MS and HR-EI-MS spectrometry and screened against soybean 15-LOX for their inhibitory potential using chemiluminescence method. All the compounds except 7m and 7h inhibited the said enzyme remarkably. Compounds 7c,7l, 7j and 7a displayed potent inhibitions ranging from IC50 1.92 ± 0.13 µM to 7.65 ± 0.12 µM. Other analogues 7g, 7o, 7e, 7b, 7d, 7k and 7n revealed excellent inhibitory values ranging from IC50 12.45 ± 0.38 µM to 24.81 ± 0.47 µM. All these compounds did not reveal DPPH radical scavenging activity. Compounds 7i-o maintained > 90 % human blood mononuclear cells (MNCs) viability at 0.125 mM as assayed by MTT whilst others were found toxic. Pharmacokinetic profiles predicted good oral bioavailability and drug-likeness properties of the active scaffolds. SAR investigations showed that phenyl substituted analogue on amide side decreased inhibitory activity due to inductive and mesomeric effects while the mono-alkyl substituted analogues were more active than disubstituted ones and ortho substituted analogues were more potent than meta substituted ones. MD simulation predicted the stability of the 7c ligand and receptor complex as shown by their relative RMSD (root mean square deviation) values. Molecular docking studies displayed hydrogen bonding between the compounds and the enzyme with Arg378 which was common in 7n, 7g, 7h and baicalein. In 7a and quercetin, hydrogen bonding was established through Asn375. RMSD values exhibited good inhibitory profiles in the order quercetin (0.73 Å) < 7 g < baicalein < 7a < 7n < 7 h (1.81 Å) and the binding free energies followed similar pattern. Density functional theory (DFT) data established good correlation between the active compounds and significant activity was associated with more stabilized LUMO (lowest unoccupied molecular orbitals) orbitals. Nevertheless, the present studies declare active analogues like 7c, 7 l, 7a, 7j as leads. Work is ongoing in derivatizing active molecules to explore more effective leads as 15-LOX inhibitors as antiinflammatory agents.

Exploring the potential of fluoro‐flavonoid derivatives as anti‐lung cancer agents: DFT, molecular docking, and molecular dynamics techniques

AbstractThe present investigation utilized in silico methodologies to explore the diverse pharmacological activities, toxicity profiles, and chemical reactivity of a series of fluoro‐flavonoid compounds (1–14), which are secondary metabolites of plants known for their broad range of biological effects. A comprehensive strategy is utilized, incorporating methods such as prediction of activity spectra for substances (PASS) prediction, absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessments, and density functional theory (B3LYP) calculations using three basis sets: 6‐31G(d,p), 6‐311G(d,p), and 6‐311++G(d,p). Furthermore, the study employed molecular docking technique to identify target proteins, including HER2 (7JXH), EGFR (4UV7), FPPS (1YQ7), HPGDS (1V40), DCK (1P60), and KEAP1 on Nrf2 (1X2J), for the investigated compounds, with cianidanol and genistein serving as reference drugs for the docking process. The investigated fluoro‐flavonoid compounds exhibited significantly greater binding affinities (ranging from −8.3 to −10.6 kcal mol−1) toward HER2, HPGDS, and KEAP1 compared to the reference drugs, cianidanol and genistein, which displayed binding affinities ranging from −8.4 to −9.4 kcal mol−1. Furthermore, molecular dynamics simulations were conducted to assess the stability of the protein‐ligand interaction, using the root‐mean‐square deviation (RMSD), root‐mean‐square fluctuation (RMSF), Radius of gyration (Rg) parameters and principle component analysis (PCA). Among the tested fluoro‐flavonoid analogs, analog 11 showed a RMSD value of .15 nm with the HER2 protein target, indicating a stable interaction. Based on in silico results, it appears that the fluoro‐flavonoid compound 11 has the potential to serve as a targeted anti‐lung cancer drug. However, additional in vivo and in vitro studies are necessary to confirm this hypothesis.

Validation of a Computationally Efficient Model of the Mu-Opioid Receptor

The mu-opioid receptor (MOR) is a transmembrane protein and the primary target for pain-modulating drugs. Opioid drugs come with detrimental side-effects such as physical dependence and addiction. However, recent studies show that understanding structural properties and dynamics of MOR may aid in the design of opioid drugs with reduced side-effects. Molecular dynamics simulations allow researchers to study changes in protein conformation at an atomistic level. However, modeling systems including MOR embedded in a lipid bilayer can be computationally expensive. This study evaluates a modeling approach that uses harmonic restraints on the transmembrane regions of MOR to model the rigidity of the lipid bilayer without explicitly simulating lipid molecules, reducing the number of atoms in the simulation. The proposed model allows MOR to be simulated 49% faster than a simulation explicitly including the lipid bilayer. To assess the accuracy of the proposed model, simulations were performed of MOR in a lipid bilayer, the free MOR in water and MOR in water with harmonic restraints applied to all transmembrane residues using NAMD 3.0 alpha and the CHARMM36 force field. Dynamic properties of MOR were shown to be different in each system, with the free MOR having a higher root mean square deviation (RMSD) than MOR with an explicitly modeled lipid bilayer. The systems with harmonic restraint constants of 0.001 kcal/mol/Å2 applied to the transmembrane residues had RMSD values comparable to those in an explicitly modeled lipid bilayer. This study demonstrates that using restraints on the transmembrane residues of MOR is a feasible way of modeling the ligand-free receptor with reduced computational costs. This model could allow the dynamics of MOR in a lipid bilayer environment to be studied more efficiently. KEYWORDS: Molecular Dynamics; Atomistic Simulations; Computational Modeling; Mu-Opioid Receptor; G-Protein Coupled Receptor; Lipid Bilayer, Opioid, Transmembrane Protein

Computational Insight of Phase Transformation and Drug Release Behaviour of Doxycycline-Loaded Ibuprofen-Based In-Situ Forming Gel.

This research investigates the gel formation behaviour and drug-controlling performance of doxycycline-loaded ibuprofen-based in-situ forming gels (DH-loaded IBU-based ISGs) for potential applications in periodontal treatment. The investigation begins by exploring the physical properties and gel formation behaviour of the ISGs, with a particular focus on determining their sustained release capabilities. To gain a deeper understanding of the molecular interactions and dynamics within the ISGs, molecular dynamic (MD) simulations are employed. The effects of adding IBU and DH on reducing surface tension and water tolerance properties, thus affecting molecular properties. The phase transformation phenomenon is observed around the interface, where droplets of ISGs move out to the water phase, leading to the precipitation of IBU around the interface. The optimization of drug release profiles ensures sustained local drug release over seven days, with a burst release observed on the first day. Interestingly, different organic solvents show varying abilities to control DH release, with dimethyl sulfoxide (DMSO) demonstrating superior control compared to N-Methyl-2-pyrrolidone (NMP). MD simulations using AMBER20 software provide valuable insights into the movement of individual molecules, as evidenced by root-mean-square deviation (RMSD) values. The addition of IBU to the system results in the retardation of IBU molecule movement, particularly evident in the DMSO series, with the diffusion constant value of DH reducing from 1.2452 to 0.3372 and in the NMP series from 0.3703 to 0.2245 after adding IBU. The RMSD values indicate a reduction in molecule fluctuation of DH, especially in the DMSO system, where it decreases from over 140 to 40 Å. Moreover, their radius of gyration is influenced by IBU, with the DMSO system showing lower values, suggesting an increase in molecular compactness. Notably, the DH-IBU configuration exhibits stable pairing through H-bonding, with a higher amount of H-bonding observed in the DMSO system, which is correlated with the drug retardation efficacy. These significant findings pave the way for the development of phase transformation mechanistic studies and offer new avenues for future design and optimization formulation in the ISG drug delivery systems field.

Isolation and protein MdtQ analysis of outer membrane vesicles released by carbapenem-resistant Klebsiella pneumoniae

Carbapenem-resistant Klebsiella pneumoniae (CRKP) has emerged as a leading public health problem, and is increasingly being reported worldwide with resistance to a wide spectrum of antibiotics. Recent reports have demonstrated that the outer membrane vesicles (OMVs) of gram-negative bacteria are potent resistance factors, but their role in the drug resistance of CRKP has not been elucidated. In order to investigate the effects of OMV components on drug resistance and to explore the mechanism of antimicrobial resistance in CRKP, we isolated the OMVs through ultracentrifugation, separated the OMV proteins through mass spectrometry (MS), and performed bioinformatics analysis. A total of 3,192 proteins were detected by nano LC-MS/MS analysis, with 108 (61.4%) cytoplasmic proteins, 50 (28.4%) cytoplasmic membrane proteins, nine (5.1%) periplasmic proteins, six (3.4%) outer membrane proteins, two (1.1%) extracellular proteins, and one (0.6%) other protein detected in the vesicles. MdtQ was detected as the only multidrug resistance outer membrane protein. Further experiments confirmed that MdtQ included the 1440 BP sequence and had a unique three-dimensional structure. To superimpose MdtQ with KPC-2 resistant proteins, I7ACB1, I7AKP2, and Q93LQ9, the root mean square deviation (RMSD) values were calculated (0.379, 0.671, and 1.35, respectively). I7ACB1 had the lowest RMSD value, indicating that it had the best superimposition effect. Furthermore, MdtQ had 20 biological pocket structures, and the four most important pockets were evenly distributed around the inner perimeter of its three-dimensional structure. These findings may provide a theoretical basis for controlling the spread of bacterial resistance in the future.

Benchmark Study of Density Functional Theory Methods in Geometry Optimization of Transition Metal-Dinitrogen Complexes.

The current benchmark study is focused on determining the most precise theoretical method for optimizing the geometry of transition metal-dinitrogen complexes. To accomplish this goal, seven density functional (DF) methods from five distinct classes of density functional theory (DFT) have been selected, including B3LYP-D3(BJ), BP86-D3(BJ), PBE0-D3(BJ), ωB97X-D, M06, M06-L, and TPSSh-D3(BJ). These DFs will be utilized with the Karlsruhe basis set (def2-SVP). To carry out this benchmark study, a total of forty-two structurally diverse transition metal-dinitrogen compounds with experimentally known X-ray data have been selected from the Cambridge Crystallographic Data Centre (CCDC). Based on a comparison of the theoretical data with experimental values (X-ray) of the selected transition metal-dinitrogen compounds, statistical parameters such as root-mean-square deviation (RMSD) and N-N and M-N bond lengths are obtained to evaluate the performance of the seven chosen DFs. According to the obtained results, among all DFT methods used in the study, Minnesota functionals (M06 and M06-L) and TPSSh-D3(BJ) show good performance, with lower RMSD values. This suggests that these three methods are the most reliable for optimizing the geometry of transition metal-dinitrogen complexes. Based on the absolute errors of the N-N and M-N bond lengths relative to the X-ray data, further analysis is conducted, and it is determined that M06-L is the best functional for optimizing the geometry of transition metal-dinitrogen compounds. Additionally, the influence of using a high-level basis set (def2-TZVP) compared to def2-SVP on the calculated RMSD among the seven chosen methods is found to be negligible.

In vitro and silico studies of geraniin interfering with HSV-2 replication by targeting glycoprotein D

Residues ASN94 and GLN41 presented the highest frequency in molecular docking tests. The geraniin-glycoprotein D(gD) complexes was stable with RMSD(root mean square deviation)value less than 0.3 nm. The Molecular dynamic (MD) simulations revealed stable hydrogen bonds between gD and geraniin. Root mean square fluctuation (RMSF) values were less than 0.15 nm around the interface of geraniin-gD complex. In virucidal assays showed a much higher anti-HSV-2 inhibition activity of geraniin as compared to acyclovir(ACV).Human immunodeficiency virus transactivator (HIV-TAT) treatment significantly enhanced HSV-2 replication and lethal effect on HaCaT cells. The inhibitory rate of geraniin against HSV-2 coinfected with HIV-TAT was significantly decreased. The immunofluorescence results also revealed that HSV-2 gD expression presented a green fluorescence on HaCaT cells membranes and showed clear downregulation in geraniin-treated cells, but was expressed clearly on cell membranes under geraniin, HSV-2 and HIV-TAT cotreatment. The anti-apoptotic effect from geraniin persisted after 72 h, while the anti-apoptotic effect from geraniin diminished when HIV-TAT and geraniin were combined.

Assimilation of Sentinel-2 Biophysical Variables into a Digital Twin for the Automated Irrigation Scheduling of a Vineyard

Decision support systems (DSS) are needed to carry out precision irrigation. Key issues in this regard include how to deal with spatial variability and the adoption of deficit irrigation strategies at the field scale. A software application originally designed for water balance-based automated irrigation scheduling locally fine-tuned through the use of sensors has been further developed with the emerging paradigm of both digital twins and the Internet of Things (IoT). The aim of this research is to demonstrate the feasibility of automatically scheduling the irrigation of a commercial vineyard when adopting regulated deficit irrigation (RDI) strategies and assimilating in near real time the fraction of absorbed photosynthetically active radiation (fAPAR) obtained from Sentinel-2 imagery. In addition, simulations of crop evapotranspiration obtained by the digital twin were compared with remote sensing estimates using surface energy balance models and Copernicus-based inputs. Results showed that regression between instantaneous fAPAR and in situ measurements of the fraction of intercepted photosynthetically active radiation (fIPAR) had a coefficient of determination (R2) ranging from 0.61 to 0.91, and a root mean square deviation (RMSD) of 0.10. The conversion of fAPAR to a daily time step was dependent on row orientation. A site-specific automated irrigation scheduling was successfully adopted and an adaptive response allowed spontaneous adjustments in order to stress vines to a certain level at specific growing stages. Simulations of the soil water balance components performed well. The regression between digital twin simulations and remote sensing-estimated actual (two-source energy balance Priestley–Taylor modeling approach, TSEB-PTS2+S3) and potential (Penman–Monteith approach) evapotranspiration showed RMSD values of 0.98 mm/day and 1.14 mm/day, respectively.

Cellulose dissolution in mixtures of ionic liquids and molecular solvents: The fruitful synergism of experiment and theory

We investigated the dependence of dissolution of microcrystalline cellulose (MCC) in binary solvent mixtures of ionic liquids (ILs) and the molecular solvents (MSs) N,N-dimethylacetamide (DMAc) and dimethyl sulfoxide (DMSO). The ILs we used are based on 1-(n-butyl)-3-methylimidazolium cation, BuMeIm+, with acetate (AcO−) and chloride (Cl−) anions. As experimental variables, we changed the mole fraction of the MS (χDMAc or χDMSO) and the temperature (T). MCC dissolution was determined using an optical microscope and expressed on the mass fraction scale (m%). The order of maximum m% was BuMeImAcO-DMSO > BuMeImAcO-DMAc ≫ BuMeImCl-DMSO. To rationalize this dependence, we used molecular dynamics (MD) simulations employing, as a model for cellulose, a crystallite of eight chains, each containing ten anhydroglucose units (AGUs). We calculated the root-mean-square-deviation (RMSD) and the radial distribution function, g(r). Values of RMSD showed that the separation of decamer-chains follows the same order as the maximum m%; more chain separation was taken to indicate greater crystallite dissolution. Additionally, the maximum values and the sharpness of the g(r) peaks followed the same order of dissolution, due to a combination of hydrogen bonding between the hydroxyl groups of the AGU and ions of the IL. We also recorded the turbidity of MCC-IL-DMSO solutions and the conductance of cellobiose-IL-MS solutions; the results of both experiments corroborated our interpretations of the MD simulation results. Our study suggests that MD simulations can be fruitfully employed to predict the best candidates among a series of solvents, e.g., IL-MS. This screening saves labor and material in the search for optimal solvents for cellulose dissolution.

The Potency of Alkaloid Derivates as Anti-Breast Cancer Candidates: In Silico Study

Breast cancer is the most frequent malignancy in women worldwide. One of the target receptors for the treatment of breast cancer are estrogen, progesterone, and HER2 receptors. An alternative treatment using natural ingredients has been developed, one of which is alkaloid compounds. This study aims to determine the activity of alkaloid compounds as anti-breast cancer agents through an in-silico method. Virtual screening (AutoDock Vina), molecular docking (AutoDock Tools), molecular dynamics (Desmond), scanning Lipinski's rule of five, as well as pharmacokinetic and toxicity parameters, were performed. The results of virtual screening, molecular docking, and molecular dynamics show that the compounds daurisoline, solasodine, and sambutoxin have stable interactions with the HER2 receptor, with the lowest values of RMSD (Root Mean Square Deviation) and RMSF (Root Mean Square Fluctuation) compared to other compounds. Based on the results of the study conducted, it was shown that daurisoline, solasodine, and sambutoxin were predicted to be used as anti-HER2 candidates for the treatment of breast cancer.