Acetylcholinesterase (AChE) and β-secretase (BACE-1) have become attractive therapeutic targets for Alzheimer's disease (AD). Flavones are flavonoid derivatives with various bioactive effects, ...including AChE and BACE-1 inhibition. In the present work, a series of 14 flavone derivatives was synthesized in relatively high yields (35-85%). Six of the synthetic flavones (
,
,
,
,
and
) had completely new structures. The AChE and BACE-1 inhibitory activities were tested, giving pIC
3.47-4.59 (AChE) and 4.15-5.80 (BACE-1). Three compounds (
,
and
) exhibited the highest biological effects on both AChE and BACE-1. A molecular docking investigation was conducted to explain the experimental results. These molecules could be employed for further studies to discover new structures with dual action on both AChE and BACE-1 that could serve as novel therapies for AD.
Acetylcholinesterase (AChE) and beta-secretase (BACE-1) are the two crucial enzymes involved in the pathology of Alzheimer's disease. The former is responsible for many defects in cholinergic ...signaling pathway and the latter is the primary enzyme in the biosynthesis of beta-amyloid as the main component of the amyloid plaques. These both abnormalities are found in the brains of Alzheimer's patients. In this study, in silico models were developed, including 3D-pharmacophore, 2D-QSAR (two-dimensional quantitative structure-activity relationship), and molecular docking, to screen virtually a database of compounds for AChE and BACE-1 inhibitory activities. A combinatorial library containing more than 3 million structures of curcumin and flavonoid derivatives was generated and screened for drug-likeness and enzymatic inhibitory bioactivities against AChE and BACE-1 through the validated in silico models. A total of 47 substances (two curcumins and 45 flavonoids), with remarkable predicted pIC
values against AChE and BACE-1 ranging from 4.24-5.11 (AChE) and 4.52-10.27 (BACE-1), were designed. The in vitro assays on AChE and BACE-1 were performed and confirmed the in silico results. The study indicated that, by using in silico methods, a series of curcumin and flavonoid structures were generated with promising predicted bioactivities. This would be a helpful foundation for the experimental investigations in the future. Designed compounds which were the most feasible for chemical synthesis could be potential candidates for further research and lead optimization.
Interleukin 6 (IL-6) is a cytokine with various biological functions in immune regulation, hematopoiesis, and inflammation. Elevated IL-6 levels have been identified in several severe disorders such ...as sepsis, acute respiratory distress syndrome (ARDS), and most recently, COVID-19. The biological activity of IL-6 relies on interactions with its specific receptor, IL-6Rα, including the membrane-bound IL-6 receptor (mIL-6R) and the soluble IL-6 receptor (sIL-6R). Thus, inhibition of the interaction between these two proteins would be a potential treatment for IL-6 related diseases. To date, no orally available small-molecule drug has been approved. This study focuses on finding potential small molecules that can inhibit protein-protein interactions between IL-6 and its receptor IL-6Rα using its crystal structure (PDB ID: 5FUC). First, two pharmacophore models were constructed based on the interactions between key residues of IL-6 (Phe74, Phe78, Leu178, Arg179, Arg182) and IL-6Rα (Phe229, Tyr230, Glu277, Glu278, Phe279). A database of approximately 22 million compounds was screened using 3D-pharmacophore models, molecular docking models, and ADMET properties. By analyzing the interactive capability of successfully docked compounds with important amino acids, 12 potential ligands were selected for further analysis via molecular dynamics simulations. Based on the stability of the complexes, the high interactions rate of each ligand with the key residues of IL-6/IL-6Rα, and the low binding free energy calculation, two compounds ZINC83804241 and ZINC02997430, were identified as the most potential IL-6 inhibitor candidates. These results will pave the way for the design and optimization of more specific compounds to combat cytokine storm in severe coronavirus patients.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
IL(interleukin)-6 is a multifunctional cytokine crucial for immunological, hematopoiesis, inflammation, and bone metabolism. Strikingly, IL-6 has been shown to significantly contribute to the ...initiation of cytokine storm—an acute systemic inflammatory syndrome in Covid-19 patients. Recent study has showed that blocking the IL-6 signaling pathway with an anti-IL-6 receptor monoclonal antibody (mAb) can reduce the severity of COVID-19 symptoms and enhance patient survival. However, the mAb has several drawbacks, such as high cost, potential immunogenicity, and invasive administration due to the large-molecule protein product. Instead, these issues could be mitigated using small molecule IL-6 inhibitors, but none are currently available. This study aimed to discover IL-6 inhibitors based on the PPI with a novel camelid Fab fragment, namely 68F2, in a crystal protein complex structure (PDB ID: 4ZS7). The pharmacophore models and molecular docking were used to screen compounds from DrugBank databases. The oral bioavailability of the top 24 ligands from the screening was predicted by the SwissAMDE tool. Subsequently, the selected molecules from docking and MD simulation illustrated a promising binding affinity in the formation of stable complexes at the active binding pocket of IL-6. Binding energies using the MM-PBSA technique were applied to the top 4 hit compounds. The result indicated that DB08402 and DB12903 could form strong interactions and build stable protein–ligand complexes with IL-6. These potential compounds may serve as a basis for further developing small molecule IL-6 inhibitors in the future.
Graphical abstract
Inhibition of human pancreatic lipase, a crucial enzyme in dietary fat digestion and absorption, is a potent therapeutic approach for obesity treatment. In this study, human pancreatic lipase ...inhibitory activity of aurone derivatives was explored by molecular modeling approaches. The target protein was human pancreatic lipase (PDB ID: 1LPB). The 3D structures of 82 published bioactive aurone derivatives were docked successfully into the protein catalytic active site, using AutoDock Vina 1.5.7.rc1. Of them, 62 compounds interacted with the key residues of catalytic trial Ser152-Asp176-His263. The top hit compound (
), with a docking score of -10.6 kcal⋅mol
, was subsequently submitted to molecular dynamics simulations, using GROMACS 2018.01. Molecular dynamics simulation results showed that
formed a stable complex with 1LPB protein via hydrogen bonds with important residues in regulating enzyme activity (Ser152 and Phe77). Compound
showed high potency for further studies, such as the synthesis, in vitro and in vivo tests for pancreatic lipase inhibitory activity.
Aurones are a minor subgroup of flavonoids. Unlike other subgroups such as chalcones, flavones, and isoflavones, aurones have not been extensively explored as pancreatic lipase inhibitors. In this ...work, we studied the pancreatic lipase inhibitory potency of synthetic aurone derivatives. Thirty-six compounds belonging to four series (4,6-dihydroxyaurone, 6-hydroxyaurone, 4,6-dialkoxyaurone, and 6-alkoxyaurone) were designed and synthesized. Their in vitro inhibitory activities were determined by spectrophotometric assay in comparison with quercetin and orlistat. Alkoxyaurone derivatives with long-chain (6-10 carbons) alkoxy substituents showed greater potency. Of them, 4,6-dialkoxyaurone 8 displayed the highest activity against pancreatic lipase (IC
of 1.945 ± 0.520 µM) relative to quercetin (IC
of 86.98 ± 3.859 µM) and orlistat (IC
of 0.0334 ± 0.0015 µM). Fluorescence quenching measurement confirmed the affinity of alkoxyaurone derivatives to pancreatic lipase. Kinetic study showed that 8 inhibited lipase through a competitive mechanism (K
of 1.288 ± 0.282 µM). Molecular docking results clarified the role of long-chain substituents on ring A in interacting with the hydrophobic pockets and pushing the inhibitor molecule closer to the catalytic triad. The findings in this study may contribute to the development of better pancreatic lipase inhibitors with aurone structure.
This paper develops a multistage optimization method for designing a new flexure hinge (FH). The proposed method is a combination of the topology optimization, the deep artificial neural network ...(DANN)-based modeling, and the water cycle algorithm-based size optimization. Firstly, solid isotropic material with penalization is employed to topologize the FH. Then, the topological FH is modified to transform into a compliant configuration. Finite element method is used to collect the output datasets of the hinge. Subsequently, the architectures of DANN are optimized to formulate the objective functions and constraints of the hinge. The results showed that the prediction accuracy of the developed DANN is better than that of the multivariate general linear model. Lastly, the geometrical sizes of the hinge are optimized by hybridizing the optimal DANN and the water cycle algorithm. The results found that the optimal solutions found from the proposed method are greater than those obtained from the other metaheuristic algorithms. Based on the results of Wilcoxon, Friedman, and Post-hoc tests, the proposed method outperforms the other methods. Besides, the results indicated that the performances of the FH are superior to the conventional hinges. The proposed optimization framework can be considered as a systematic design method for compliant mechanisms and related engineering areas.
Display omitted
•A new optimization design framework is developed for flexure hinge.•The proposed framework undergoes three main phases: (i) topology optimization by SIMP, (ii) surrogate-based model by DANN, and (iii) size optimization by WCA.•Prediction accuracy and effectiveness of the developed framework is superior to other metaheuristic methods through statistical comparison.•Performances of the developed flexure hinge are greater than those of the existing flexure hinges.
Compliant mechanisms are promising candidates in precision engineering, soft robotics, space, and bioengineering due to their advantages of free friction, free lubricant, no backlash, monolithic ...structure, and minimal assembly. However, designing and analyzing of compliant mechanisms are facing the high complexity due to a coupling of kinematic and mechanical behavior in comparison to rigid-body mechanisms. Especially, considering a multi-objective optimization design for compliant mechanisms, the problem is more complicated. Thus, this paper presents a new efficient hybrid methodology for solving the multi-objective optimization design. A hybridization is developed through a combination of finite element method, statistical technique, desirability function approach, fuzzy logic system, adaptive neuro-fuzzy inference system (ANFIS), and Lightning attachment procedure optimization (LAPO). A bistable compliant mechanism is investigated as an application example of the proposed method. First, design variables of the mechanism are determined, and then central composite design is employed to construct a numerically experimental matrix. Though using analysis of variance and Taguchi approach, the design variables are refined to make new populations. Subsequently, desirability values of two performances of the mechanism are computed, and the results are transferred into the fuzzy logic system. The output of fuzzy logic system is considered as single combined objective function. By developing the ANFIS model, the relation between the refined design variables and the output of fuzzy logic system is established. Finally, LAPO algorithm is adopted for solving the multi-objective optimization problem for the mechanism. Three numerical examples are investigated to validate the performance efficiency of the proposed method. The results demonstrate that the proposed method is more efficient than Taguchi-based fuzzy logic. Besides, through Wilcoxon signed rank test and Friedman test, it reveals that the performances of proposed approach are superior to those of the Jaya algorithm and TLBO algorithm. The results of this article can be extended for other complex compliant mechanisms as well as optimization problems with multiple objective functions and more complex constraints.
•An efficient hybridization of desirability function approach, fuzzy logic system, adaptive neuro-fuzzy inference system, and Lightning attachment procedure optimization is proposed.•Search spaces of design variables are reduced through statistical technique.•Performance efficiency of the proposed hybrid approach is superior to Taguchi-based fuzzy logic.•roposed approach is outperformed to ANFIS-Jaya and ANFIS-TLBO by non-parameter statistical comparison.
The overexpression of ABCC2/MRP2, an ATP-binding cassette transporter, contributes to multidrug resistance in cancer cells. In this study, a quantitative structure–activity relationship (QSAR) ...analysis on ABCC2 inhibitors has been carried out, aiming to establish a computational prediction model for ABCC2 modulators. Seven classification models and two regression models were built by SONNIA 4.2, and two other regression models were built by MOE 2008.10 based on a data set comprising 372 compounds collected from 16 relevant publications. The CPG-C iABCC2 model for classifying ABCC2 inhibitors has total accuracy of 0.88 and Matthews correlation coefficient MCC = 0.75. The CPG-C iEG model for classifying ABCC2 inhibitors (substrate EG: β-estradiol 17-β-
d
-glucuronide) has total accuracy of 0.91 and MCC = 0.82. The regression model PLS EG-IC
50
for predicting ABCC2 inhibitors (substrate EG) gave root-mean-square error RMSE = 0.26,
Q
2
= 0.73 and
R
pred
2
=
0.63
. The regression model PLS CDCF-IC
50
for predicting ABCC2 inhibitors substrate CDCF: 5(6)-carboxy-2′,7′-dichlorofluorescein gave RMSE = 0.31,
Q
2
= 0.74 and
R
pred
2
=
0.67
. Four 2D-QSAR models were applied to 1661 compounds, with results indicating 369 compounds having the ability to reverse the efflux of both EG and CDCF by ABCC2, 152 among them having IC
50
< 100 µM.
Graphic abstract
To overcome the limited stroke of existing micropositioning stages in precision engineering systems, this article proposes an optimal design of a new micropositioner based on the cricket-mimicked ...bistable mechanism. The suggested micropositioner is potential for polishing application. The proposed bistable mechanism is combined with a positive-stiffness mechanism to achieve a large stroke with centimeter range. The design targets of micropositioner are to deliver a large stroke, a high frequency, and a small parasitic motion but also ensure working safety. To solve three objective functions with four constraints, a hybrid optimization approach is proposed, namely fuzzy logic, teaching learning-based optimization (TLBO), and artificial neural network (ANN). The fuzzy logic is proposed to combine three objective functions into a single objective function, so-called output fuzzy. In the modeling, the TLBO is employed to determine the optimum ANN structure. Then, the multi-objective optimization problem of the micropositioner is converted into the single optimization task through the TLBO. Besides, the influences of the geometrical parameters on the performance qualities of the micropositioner are investigated. The results showed the performance indexes of TLBO-assisted ANN are reasonable and reliable. The optimum design parameters are found at
l
1
= 60.93 mm,
l
2
= 10.42 mm,
t
1
= 2.77 mm,
t
2
= 1.37 mm, and
t
3
= 9.28 mm. A prototype of ABS micropositioner is manufactured by fused deposition modeling 3D printer. The displacement and the parasitic motion were experimentally measured about 14.9513 mm and 0.0061 mm, respectively. The frequency and the stress were simulated in ANSYS software about 617.9227 Hz and 38.7659 MPa, respectively. The output stroke is over 1 cm which is potential for wide applications.
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