Root Mean Square Deviation Values Research Articles

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.

Quantitative assessment of plantar pressure patterns in relation to foot deformities in people with hereditary motor and sensory neuropathies

BackgroundHereditary motor and sensory neuropathies (HMSN), also known as Charcot-Marie-Tooth disease, are characterized by affected peripheral nerves. This often results in foot deformities that can be classified into four categories: (1) plantar flexed first metatarsal, neutral hindfoot, (2) plantar flexed first metatarsal, correctable hindfoot varus, (3) plantar flexed first metatarsal, uncorrectable hindfoot varus, and (4) hindfoot valgus. To improve management and for the evaluation of surgical interventions, a quantitative evaluation of foot function is required. The first aim of this study was to provide insight into plantar pressure of people with HMSN in relation to foot deformities. The second aim was to propose a quantitative outcome measure for the evaluation of surgical interventions based on plantar pressure.MethodsIn this historic cohort study, plantar pressure measurements of 52 people with HMSN and 586 healthy controls were evaluated. In addition to the evaluation of complete plantar pressure patterns, root mean square deviations (RMSD) of plantar pressure patterns from the mean plantar pressure pattern of healthy controls were calculated as a measure of abnormality. Furthermore, center of pressure trajectories were calculated to investigate temporal characteristics. Additionally, plantar pressure ratios of the lateral foot, toes, first metatarsal head, second/third metatarsal heads, fifth metatarsal head, and midfoot were calculated to measure overloading of foot areas.ResultsLarger RMSD values were found for all foot deformity categories compared to healthy controls (p < 0.001). Evaluation of the complete plantar pressure patterns revealed differences in plantar pressure between people with HMSN and healthy controls underneath the rearfoot, lateral foot, and second/third metatarsal heads. Center of pressure trajectories differed between people with HMSN and healthy controls in the medio-lateral and anterior-posterior direction. The plantar pressure ratios, and especially the fifth metatarsal head pressure ratio, differed between healthy controls and people with HMSN (p < 0.05) and between the four foot deformity categories (p < 0.05).ConclusionsSpatially and temporally distinct plantar pressure patterns were found for the four foot deformity categories in people with HMSN. We suggest to consider the RMSD in combination with the fifth metatarsal head pressure ratio as outcome measures for the evaluation of surgical interventions in people with HMSN.

Prediction, Application, and Mechanism Exploration of Liquid–Liquid Equilibrium Data in the Extraction of Aromatics Using Sulfolane

Liquid–liquid equilibrium (LLE) data are critical for the design and optimization of processes for extracting aromatics. Partial LLE data for the non-aromatic–aromatic–sulfolane ternary system were acquired at 313.15 K and 101.3 kPa. The LLE data for the extraction of aromatics using sulfolane were predicted using the COSMO-RS model. Correspondingly, the predicted and experimental data were analyzed using the root mean square deviation (RMSD), distribution coefficient (D), and separation factor (S). The COSMO-RS model could better predict the LLE data for the extraction of aromatics by sulfolane. The results of quantum chemical calculation show that hydrogen bonds and van der Waals interactions between sulfolane–benzene and sulfolane–toluene were responsible for the strong selectivity of sulfolane for benzene and toluene over alkanes. The LLE data predicted by the COSMO-RS method using the UNIQUAC thermodynamic model were subjected to correlation analysis. The calculated RMSD values were all less than 0.0180, and the relative deviation (δ) between the simulated value of the main process index for the extraction column and the actual data was less than 2.5%, indicating that the obtained binary interaction parameters can be reliably used in designing and optimizing the extraction of aromatics using sulfolane.

Drug Repurposing of FDA Compounds against α-Glucosidase for the Treatment of Type 2 Diabetes: Insights from Molecular Docking and Molecular Dynamics Simulations.

Type 2 diabetes mellitus is a chronic health problem that can be controlled by slowing one's carbohydrate metabolism by inhibiting α-glucosidase, an enzyme responsible for carbohydrate degradation. Currently, drugs for type 2 diabetes have limitations in terms of safety, efficiency, and potency, while cases are rapidly increasing. For this reason, the study planned and moved towards drug repurposing by utilizing food and drug administration (FDA)-approved drugs against α-glucosidase, and investigated the molecular mechanisms. The target protein was refined and optimized by introducing missing residues, and minimized to remove clashes to find the potential inhibitor against α-glucosidase. The most active compounds were selected after the docking study to generate a pharmacophore query for the virtual screening of FDA-approved drug molecules based on shape similarity. The analysis was performed using Autodock Vina (ADV)-based on binding affinities (-8.8 kcal/mol and -8.6 kcal/mol) and root-mean-square-deviation (RMSD) values (0.4 Å and 0.6 Å). Two of the most potent lead compounds were selected for a molecular dynamics (MD) simulation to determine the stability and specific interactions between receptor and ligand. The docking score, RMSD values, pharmacophore studies, and MD simulations revealed that two compounds, namely Trabectedin (ZINC000150338708) and Demeclocycline (ZINC000100036924), are potential inhibitors for α-glucosidase compared to standard inhibitors. These predictions showed that the FDA-approved molecules Trabectedin and Demeclocycline are potential suitable candidates for repurposing against type 2 diabetes. The in vitro studies showed that trabectedin was significantly effective with an IC50 of 1.263 ± 0.7 μM. Further investigation in the laboratory is needed to justify the safety of the drug to be used in vivo.

Identification of Novel Protein Targets of Prodigiosin for Breast Cancer Using Inverse Virtual Screening Methods.

Prodigiosin (PG) is chemically formulated as 4-methoxy-5-[(5-methyl-4-pentyl-2H-pyrrol-2ylidene)methyl]-2,2'-bi-1H-pyrrole and it is an apoptotic agent. Only a few protein targets for PG have been identified so far for regulating various diseases; nevertheless, finding more PG targets is crucial for novel drug discovery research. A bioinformatics method was applied in this work to find additional potential PG targets. Initially, a text mining analysis was conducted to determine the relationship between PG and a variety of metabolic processes. One hundred sixteen proteins from the KEGG pathway were selected for the docking study. Inverse virtual screening was performed by Discovery Studio software 4.1 using CHARMm-based docking tool. Twelve proteins are screened out of 116 because their CDOCKER interaction energy is larger than - 40.22kcal/mol. The best docking score with PG was reported to be - 44.25kcal/mol, - 44.99kcal/mol, and - 40.91kcal/mol for three novel proteins, such as human epidermal growth factor-2 (HER-2), mitogen-activated protein kinase (MEK), and S6 kinase protein (S6K) respectively. The interactions in the S6K/PG complex are predominantly hydrophobic; however, hydrogen bond interactions can be identified in the MEK/PG and HER-2/PG complexes. The root-mean-square deviation (RMSD) and key interaction score system (KISS) were further used to validate the docking approach. The docking approach employed in this work has a low RMSD value (2.44Å) and a high KISS score (0.5), indicating that it is significant.

Investigations of p-tolyloxy-1,3,4-oxadiazole propionamides as soybean 15-lipoxygenase inhibitors in comforting with in vitro and in silico studies

Inflammatory disorders are the prime contributor to public health issue and the development of more effective and safer anti-inflammatory drugs in addition to other therapeutic alternatives to treat inflammatory illnesses, particularly chronic inflammatory diseases, is one of the foremost current issues. In this regard, our present work is concerned with the synthesis of a new series of N-alkyl/aralkyl/aryl derivatives (7a–o) of 5-((p-tolyloxymethyl)-4H-1,3,4-oxadiazole-2-ylthio)propionamide which was instigated by the successive conversions of p-tolyloxyacetic acid into ester, hydrazide and 5-(p-tolyloxymethyl)-4H-1,3,4-oxadiazole-2-thiol. The planned compounds (7a–o) were attained by the reaction of 5-(p-tolyloxymethyl)-4H-1,3,4-oxadiazole-2-thiol with variety of N-alkyl/aralkyl/aryl electrophiles in potassium hydroxide and were characterized by FTIR, 1H-, 13C-NMR spectroscopy, EI-MS and HR-EI-MS spectrometry and probed for their inhibiting potential against soybean 15-lipoxygenase (15-LOX) enzyme. The compounds 7a, 7n, 7 g, 7e, 7h, 7i, 7j and 7b promulgated the potent inhibiting potential with IC50 values 9.43 ± 0.45, 16.75 ± 0.49, 19.45 ± 0.37, 21.32 ± 0.46, 22.64 ± 0.56, 23.53 ± 0.62, 24.32 ± 0.45 and 29.15 ± 0.57 µM, respectively, while excellent to good inhibitory activities were shown by 7o, 7 m, 7k, 7f, 7c, 7 l and 7d with IC50 values in the range 30.29 ± 0.56 to 52.54 ± 0.64 µM. Compounds 7i–o maintained 91.12 ± 1.5 to 98.23 ± 1.2% blood mononuclear cells (MNCs) viability at 0.25 mM by MTT assay whilst compounds 7d–h observed 46.51 ± 1.3 to 57.12 ± 1.4% viability where as the most toxic compounds were 7b (12.51 ± 1.4%), 7a (28.12 ± 1.5%) and 7c (38.23 ± 1.5%) as compared with controls. Pharmacokinetic profiles predicted good oral bioavailability and drug-likeness properties of molecules as per rule of five. Molecular docking studies displayed hydrogen bonding between the compounds and the enzyme with Arg378 which was common in 7n, 7 g, 7h and baicalein. In 7a and quercetin, hydrogen bonding was established through Asn375; Tyr512 and Val589 were also involved in bonding with other analogues. RMSD (root mean square deviation) values exhibited good inhibitory profiles in the order quercetin (0.73 Å)<7 g (0.98 Å)<baicalein (1.23 Å)<7a (1.27 Å)<7n (1.75 Å)<7h (1.81 Å) whereas the binding free energies (kJ/mol) increasing order: (−37.56 kJ/mol)< quercetin (−35.43 kJ/mol)<7n (−34.55 kJ/mol)<7 g (−33.38 kJ/mol)<7h (31.75 kJ/mol)<7a (−31.63 kJ/mol). Density functional theory (DFT) data established good correlation between the IC50 values of compounds and HOMO–LUMO (highest occupied and lowest unoccupied molecular orbitals) energy calculations. It was found that compounds with more stabilized LUMO orbitals had significant biological activity. The work collectively supports steps taken forward in search for potential ‘leads’ as anti-inflammatory agents wherein compounds 7a, 7n, 7i, 7j possessed ‘lead’ like properties for further investigations. Communicated by Ramaswamy H. Sarma

COMPARATIVE CHAINS DYNAMICS OF TRIOSEPHOSPHATE ISOMERASE INVESTIGATED BY MOLECULAR DYNAMICS SIMULATION

Triosephosphate isomerase is an enzyme which catalyzes the inter-conversion between glyceraldehyde-3-phosphate and dihydroxyacetone phosphate in the fifth step of the glycolytic pathway. In this study, molecular dynamics simulation technique was employed to investigate the dynamics of the two monomer chains of triosephosphate isomerase of trypanosoma brucei brucei (TbTIM) using GROMACS 2016.04 software. The MD simulation of the x-ray structure of TbTIM was performed using the GROMOS 9643a1 force field and simple point charge water model under isothermal-isobaric condition with periodic boundary conditions imposed on x, y, z directions. The Root Mean Square Deviation (RMSD) Root Mean Square fluctuation (RMSF), Radius of Gyration (ROG), Solvent accessible surface area (SASA) and hydrogen bonds were computed. The RMSD values indicate that chain-B shows transition between two conformational states with higher RMSD value of 0.45 nm when compared to chain-A with RMSD of 0.27 nm. The RMSF values indicates that residues of loop 6 (residues 166 to 177) have the highest fluctuations in both chains compared to other residues with chain-A having higher fluctuations peak. The ROG values of chain-A varies from 1.675 nm to 1.761 nm while that of chain-B varies from 2.480 nm to 2.590 nm implying that chain-A is more compact during the simulation than chain-B. The SASA values indicates that chain-B has more contact with solvent than chain-A. 160 hydrogen bonds were found which indicates the stability of the protein during the simulation. From the RMSD, ROG, SASA values, it is evident that chain-B of triosephosphate isomerase of trypanosoma bruceibrucei displayed greater structural dynamics than chain-A during the MD simulation.

Sustainability analysis of sandstone using smart material by EMI approach.

In India, sandstone was broadly used to construct structures like Agra Fort, Red Fort Delhi, and Allahabad Fort. Around the world, many historical structures were collapsed due to the adverse effect of damages. Structural health monitoring (SHM) is very useful to take appropriate action against the failure of the structure. The electro-mechanical impedance (EMI) technique is used to continuously monitor the damage. A piezoelectric ceramic (PZT) is used in the EMI technique. PZT is a smart material used as a sensor or an actuator in a certain specific manner. The EMI technique work in the 30 to 400kHz frequency range. This technique helped to analyze the hairline crack, location, and severity of damage to structural elements. A 10cm length and 5cm diameter sandstone cylinder was used in the experimental work. An electric marble cutter was used to create the artificial damages of 2mm, 3mm, 4mm, and 5mm respectively along the length, at the same place in specimens. The conductance signature and susceptance signature were measured for each depth of damage. The comparative result of healthy and damaged state with different depth were concluded based on the conductance signature and susceptance signature form the sample. Statistical methods like root mean square deviation (RMSD) is used for the quantification of damage. The sustainability of sandstone has been analyzed with the help of the EMI technique and RMSD values. This paper motivates the application of the EMI technique to the historical building made of sandstone as key material.

West Nile virus-associated HLA-DRB1 alleles in the Greek population: A structural perspective.

The HLA system plays a significant role via the regulation of the immune system and contributes to the progression and protection of many diseases. In our previous study, several HLA-DRB1 alleles were found to have a susceptible or protective role toward infection and neuroinvasion of West Nile Virus (WNV) in the Greek population. As expected, the majority of polymorphic positions are located in the peptide-binding region of the molecule. In the present work, the structure of these alleles was studied in silico, to examine the effect of polymorphism on the conformation of DRB1 proteins, with the aspect of WNV association. More specifically, molecular dynamics simulations were used for structural prediction of 23 available alleles. These modeled alleles were evaluated using root-mean-square deviation (RMSD) and root-mean-square fluctuation analysis. Low RMSD values indicate that different alleles have similar structures. Furthermore, low fluctuation was observed in the peptide-binding region between alleles with the higher and the lowest RMSD values. These findings indicate that probably variable residues do not affect the behavior of DRB1 alleles in WNV disease, by causing structural differences between them.

LassoHTP: A High-Throughput Computational Tool for Lasso Peptide Structure Construction and Modeling.

Lasso peptides are a subclass of ribosomally synthesized and post-translationally modified peptides with a slipknot conformation. With superior thermal stability, protease resistance, and antimicrobial activity, lasso peptides are promising candidates for bioengineering and pharmaceutical applications. To enable high-throughput computational prediction and design of lasso peptides, we developed a software, LassoHTP, for automatic lasso peptide structure construction and modeling. LassoHTP consists of three modules, including the scaffold constructor, mutant generator, and molecular dynamics (MD) simulator. With a user-provided sequence and conformational annotation, LassoHTP can either generate the structure and conformational ensemble as is or conduct random mutagenesis. We used LassoHTP to construct eight known lasso peptide structures de novo and to simulate their conformational ensembles for 100 ns MD simulations. For benchmarking, we calculated the root mean square deviation (RMSD) of these ensembles with reference to their experimental crystal or NMR PDB structures; we also compared these RMSD values against those of the MD ensembles that are initiated from the PDB structures. Dihedral principal component analysis was also conducted. The results show that the LassoHTP-initiated ensembles are similar to those of the PDB-initiated ensembles. LassoHTP offers a computational platform to develop strategies for lasso peptide prediction and design.