Current computer-aided drug design最新文献

Objective: To investigate the therapeutic effect of Yiqi Jianpi Tongqiao (YJT) formula (Hedysarum Multijugum Maxim, Magnoliae Flos, Xanthii Fructus, Notopterygii Rhizoma Et Radix, Kaempferiae Rhizoma, Acoritataninowii Rhizoma, Saposhnikoviae Radix) on an allergic rhinitis mouse model, and to explore the active ingredients, key targets, and molecular mechanisms of this formula using network pharmacology and molecular docking methods.

Methods: An allergic rhinitis mouse model was established to observe changes in rhinitis symptoms, nasal mucosal morphology, and serum indicators after administering the YJT formula. The TCMSP, GeneCards, OMIM, and DisGeNET databases were used to screen for the active ingredients, action targets, and disease targets of the YJT formula. The Cytoscape software was used to construct a network of the active ingredients and action targets. The protein-protein interaction (PPI) network was used to predict hub genes. The corresponding active compounds with the hub genes' highest oral bioavailability (OB) values were identified, followed by molecular docking analysis.

Results: Animal experiments demonstrated that the YJT formula reduced rhinitis symptoms (nasal itching, runny nose, and face scratching) in allergic rhinitis mice, as well as decreased nasal mucosal inflammatory reactions and serum inflammatory indicators (histamine, OVAspecific IgE, IL-1β levels). Furthermore, 63 active components and 101 potential indicator targets of the YJT formula were identified, along with 5 hub genes (IL6, AKT1, IL1B, VEGFA, and PTGS2), and the corresponding active compounds with the highest OB values were quercetin, aloe-emodin, and denudanolide b. Molecular docking results revealed the binding energy between quercetin, aloe-emodin, denudanolide b and 5 hub genes (IL6, AKT1, IL1B, VEGFA, and PTGS2) were -5.78 to -10.22 kcal/mol, the binding energy between dexamethasone and 5 hub genes were -6.3 to -9.7 kcal/mol. In addition, GO and KEGG analysis suggested significant enrichment of these genes in biological processes such as response to lipopolysaccharide, response to molecule of bacterial origin, and response to reactive oxygen species, as well as signaling pathways like AGE-RAGE signaling pathway in diabetic complications, Lipid and atherosclerosis, and IL-17 signaling pathway.

Conclusion: The YJT formula has therapeutic effects in an allergic rhinitis mouse model, with the main active components being quercetin, aloe-emodin, and denudanolide b, and the key targets being IL6, AKT1, IL1B, VEGFA, and PTGS2, involving multiple signaling pathways.

Objective: The NLRP3 inflammasome mediates a range of inflammatory responses that are associated with an increasing number of pathological mechanisms. Over-activation of NLRP3 can exacerbate many diseases. However, NLRP3 antagonists have significant therapeutic potential. Moreover, NLRP3 plays an important role in limiting the growth and spread of some tumors, and NLRP3 agonists also have clinical value. MCC950 and BMS986299 are an antagonist and agonist of NLRP3, respectively. In light of the important clinical applications of NLRP3, especially for NLRP3 inhibitors, a computational method was used to investigate the interaction modes of MCC950 and BMS986299 with NLRP3 in order to design and develop more potent NLRP3 regulators.

Methods: In this study, the conformational behaviors of NLRP3 bound to the antagonist MCC950 in an inactive state and the agonist BMS986299 in an active state were investigated using 200 ns equilibrium all-atom molecular dynamics (MD) simulations, and then the analyses of the MD trajectories (RMSD, Rg, RMSF, SASA, PCA, and DCCM) were carried out to explore the mechanism of the antagonist and agonist on NLRP3 in the two different states.

Results: The RMSD, RMSF, Rg, SASA, and PCA analyses indicated that NLRP3 was more dispersive and less energetically stable in the active state than in the inactive state and that MCC950 significantly reduced the fluctuations of the interactive residues while BMS986299 did not. The antagonist MCC950 interacted with residues mainly in the NBD, HD1, WHD, and HD2 domains of NLRP3, whereas the agonist BMS986299 mainly in the NBD and WHD of NLRP3. Additionally, both compounds did not interact with residues located in the FISNA domain. The conformation of the FISNA domain appeared to change significantly when NLRP3 was translated from an inactive state to an active state.

Conclusion: The antagonist may interact with residues mainly in the NBD, HD1, WHD, and HD2 domains, and the agonist may interact in the NBD and WHD domains. Our study provided new insights into the development of NLRP3 regulators.

Aims: The machine learning-based QSAR modeling procedure, molecular generations, and molecular dynamic simulations were applied to virtually screen the DNA polymerase theta inhibitors.

Background: The DNA polymerase theta (Polθ or POLQ) is an attractive target for treatments of homologous recombination deficient (such as BRCA deficient) cancers. There are no approved drugs for targeting POLQ, and only one inhibitor is in Phase Ⅱclinical trials; thus, it is necessary to develop novel POLQ inhibitors.

Objectives: To build machine learning models that predict the bioactivities of POLQ inhibitors. To build molecular generation models that generate diverse molecules. To virtually screen the generated molecules by the machine learning models. To analyze the binding modes of the screening results by molecular dynamic simulations.

Methods: In the present work, 325 inhibitors with POLQ polymerase domain bioactivities were Collected. Two machine learning methods, random forest and deep neural network, were used for building the ligand- and structure-based quantitative structure-activity relationship (QSAR) models. The substructure replacement-based method and transfer learning-based deep recurrent neural network method were used for molecular generations. Molecular docking and consensus QSAR models were carried out for virtual screening. The molecular dynamic simulations and MM/GBSA binding free energy calculation and decomposition were used to further analyze the screening results.

Results: The MCC values of the best ligand- and structure-based consensus QSAR models reached 0.651 and 0.361 for the test set, respectively. The machine learning-based docking scores had better-predicted ability to distinguish the highly and weakly active poses than the original docking scores. The 96490 molecules were generated by both molecular generation methods, and 10 molecules were retained by virtual screening. Four favorable interactions were concluded by molecular dynamic simulations.

Conclusion: We hope that the screening results and the binding modes are helpful for designing the highly active POLQ polymerase inhibitors and the models of the molecular design workflow can be used as reliable tools for drug design.

Background: Exogenous substances modulate metabolism by regulating the expression and function of UDP-glycosyltransferases (UGTs). However, the exact mechanism in the intestine was rarely understood. Herein, we explored the effects of representative flavonoids and organic acids on the regulation of UGT1A1.

Methods: MTT assays and western blot analysis were used to explore the effect of polyphenols. X-ray diffraction was used to reveal the catalytic mechanisms of UGTs.

Results: MTT assays showed that these compounds basically had no cytotoxicity, even in concentrations up to 200 μM. Then, through western blot assays, UGT1A1 expression was increased after being treated with liquiritigenin and caffeic acid. Furthermore, liquiritigenin and caffeic acid enhanced the nuclear translocation of Nrf2. Moreover, a 2.5-Å crystal structure of the complex containing UGTs C-terminal domain and organic acid was solved, and the UDPGA binding pocket could be occupied by organic acid, suggesting the enzyme activity might be impaired by organic acid.

Conclusion: Above all, liquiritigenin and caffeic acid maintained the metabolism balance by upregulating the expression of UGT1A1 via Nrf2 activation and inhibiting the enzyme activity in Caco-2 cells.

Background: Drug-resistant Staphylococcus aureus represents a substantial healthcare challenge worldwide, and its range of available therapeutic options continues to diminish progressively. Thus, this study aimed to identify potential inhibitors against FemA, a crucial protein involved in the cell wall biosynthesis of S. aureus.

Materials and methods: The screening process involved a comprehensive structure-based virtual screening on the StreptomDB database to identify ligands with potential inhibitory effects on FemA using AutoDock Vina. The most desirable ligands with the highest binding affinity and pharmacokinetic properties were selected. Two ligands with the highest number of hydrogen bonds and hydrophobic interactions were further analyzed by molecular dynamics (MD) using the GROMACS version 2018 simulation package.

Results: Six H-donor conserved residues were selected as protein active sites, including Arg- 220, Tyr-38, Gln-154, Asn-73, Arg-74, and Thr-24. Through virtual screening, a total of nine compounds with the highest binding affinity to the FemA protein were identified. Frigocyclinone and C21H21N3O4 exhibited the highest binding affinity and demonstrated favorable pharmacokinetic properties. Molecular dynamics analysis of the FemA-ligand complexes further indicated desirable stability and reliability of complexes, reinforcing the potential efficacy of these ligands as inhibitors of FemA protein.

Conclusion: Our findings suggest that Frigocyclinone and C21H21N3O4 are promising inhibitors of FemA in S. aureus. To further validate these computational results, experimental studies are planned to confirm the inhibitory effects of these compounds on various S. aureus strains. Combining computational screening with experimental validation contributes valuable insights to the field of drug discovery in comparison to the classical drug discovery approaches.

Background: Klebsiella species have emerged as well-known opportunistic pathogens causing nosocomial infections with β-lactamase-mediated resistance as a prevalent antibiotic resistance mechanism. The discovery and emergence of metallo-β-lactamases, mainly new- Delhi metallo-β-lactamases (NDMs), have increased the threat and challenges in healthcare facilities.

Objective: A computational screening was conducted using 570 natural compounds from Dr. Duke's Phytochemical and Ethnobotanical data to discover promising inhibitors for NDM-6, NDM-9, and NDM-23 of the Klebsiella species.

Methods: Using homology modeling on the Raptor-X web server, the structures of the three NDM variants were predicted. The structures were validated using various computational tools and MD simulation for 50 ns. Lipinski - Vebers' Filter and ADMET Screening were used to screen 570 compounds, followed by docking in Biovia Discovery Studio 2019 using the CDOCKER module. GROMACS was used to simulate the compounds with the highest scores with the proteins for 50 ns. Using the MM-PBSA method and g_mmpbsa tool, binding free energies were estimated and per-residue decomposition analysis was conducted.

Results: The three structures predicted were found stable after the 50 ns MD Simulation run. The compounds Budmunchiamine-A and Rhamnocitrin were found to have the best binding energy towards NDM-6, NDM-9, and NDM-23, respectively. From the results of MD Simulation, MM-PBSA binding free energy calculations, and per-residue decomposition analysis, the Protein-ligand complex of NDM-6 with Budmunchiamine A and NDM-9 with Rhamnocitrin was relatively more stable than the complex of NDM-23 and Rhamnocitrin.

Conclusion: The study suggests that Budmunchiamine-A and Rhamnocitrin are potential inhibitors of NDM-6 and NDM-9, respectively, and may pave a path for in-vivo and in-vitro studies in the future.

Background: The purpose of this research is to develop an analytical method and validate it according to ICH guidelines for the estimation of Toremifene by RP-HPLC-PDA with molecular docking and ADMET analysis. From molecular docking, it came to know the receptor affinity specifically to estrogen receptors (ERα and ERβ), which are responsible for cancer therapy. ADMET analyses secure its therapeutic potential as well safety of the drug.

Methods: An isocratic method has developed by RP-HPLC-PDA (AGILENT 1100) with symmetry of 100 mm x 4.6 mm x 5 μm particle size C18 column and optimise mobile phase is methanol: 0.1% OPA (orthophosphoric acid) water ratio of 43:57% v/v. Under different conditions like acidic, alkaline, oxidative, and neutral environments, toremifene was tested for degradation.

Results: The developed method is validated in accordance with ICH guidelines. A calibration curve with an r2 value of 0.9987 has been prepared across the range of 10 to 50 μg/ml with five standard dilutions. The retention time of the drug is 5.575 minutes. The validation results are system suitability (%RSD-0.76), inter-day precision (%RSD 0.14-0.29), intraday precision (%RSD 0.08-0.34), accuracy (%RSD 0.16-0.96), and robustness (%RSD 0.16-0.35). In different intended conditions, four peaks are in 1 N HCl, two peaks in 1 N NaOH, three peaks in 10% H2O2 (1hr), and one peak in neutral.

Conclusion: Toremifene, a Selective Estrogen Receptor Modulator (SERM), Drug pharmacokinetic properties and receptor binding affinity results are helpful in designing the analytical method. Developing the RP-HPLC-PDA method is found to be novel, simple and precise. It could be used for testing toremifene in bulk and pharmaceutical tablet dosage forms in quality control, as well as stability tests.

Objective: Cancer poses a great threat to human health, and effective drugs to treat it are always needed. Several compounds containing a 2-aminopyrazine framework have been identified as antitumor agents with SHP2 inhibition activities. This current work aimed to search for more potent novel compounds possessing a 2-aminopyrazine moiety with antitumor activities.

Methods: A series of 12 novel 2-aminopyrazine derivatives was synthesized, and their structures were confirmed by spectroscopic techniques. The inhibitory activities of all the synthesized compounds against MDA-MB-231 and H1975 cancer cell lines were evaluated by an MTT assay. The most potent compound 3e was analyzed by flow cytometry. Subsequently, computational studies were performed to investigate the possible antitumor mechanisms of compound 3e.

Results: The results indicated that compound 3e exhibited potent antitumor activities with IC50 values of 11.84±0.83μM against H1975 cells and 5.66±2.39μM against MDA-MB-231 cells, which were more potent than the SHP2 inhibitor GS493 (IC50 = 19.08±1.01 μM against H1975 cells and IC50 = 25.02±1.47 μM against MDA-MB-231 cells). Further analysis by flow cytometry demonstrated that compound 3e induced cell apoptosis in H1975 cells. The results of the molecular docking and MD simulations, including RMSD, RMSF, PCA, DCCM and binding energy and decomposition analyses, revealed that compound 3e probably selectively inhibited SHP2.

Conclusion: A new compound having a 2-aminopyrazine substructure with potent inhibitory activities against the H1975 and MDA-MB-231 cancer cells was obtained, meriting further investigation as an antitumor drug.

Background: Hyperlipidemia is characterized by an abnormally elevated serum cholesterol, triglycerides, or both. The relationship between an elevated level of LDL and cardiovascular diseases is well-established. Cholesteryl ester transfer protein (CETP) is an enzyme that moves cholesterol esters and triglycerides between LDL, VLDL, and HDL. CETP inhibition leads to a reduction in cardiovascular disease by raising HDL and minimizing LDL.

Objective: This study synthesized ten meta-chlorinated benzene sulfonamides 6a-6j and explored their structure-activity relationship.

Methods: The synthesized molecules were characterized using 1H-NMR, 13C-NMR, IR, and HR-MS. Moreover, cheminformatics analyses included pharmacophore mapping, LibDock studies, and cheminformatics characterization using 2-dimensional (2D) molecular descriptors and principal component analysis.

Results: Based on in vitro functional CETP assays, compounds 6e, 6i, and 6j demonstrated the strongest inhibitory activities against CETP, reaching 100% inhibition. The inhibitory activity of compounds 6a-6d and 6f-6h ranged from 47.5% to 96.5% at 10 μM concentration. Pharmacophore mapping results suggested CETP inhibitory action, while the docking scores and calculated binding energies predicted favoring binding at the CETP active site. Best-scoring docking poses predicted critical hydrophobic features corresponding to key interactions with His232 and Cys13. Cheminformatics analysis using 2D molecular descriptors indicated that the synthesized compounds span various physicochemical properties and drug-likeness.

Conclusion: It was found that a chloro moiety at the ortho-position, or a nitro group at the meta and para-positions, improves the CETP inhibitory activity of synthesized analogs. Computational studies suggest the formation of stable ligand-protein complexes between compounds 6a- 6j and CETP.

Objective: The study aimed to explore the crucial genes involved in cancer-related biological processes, including EMT, autophagy, apoptosis, anoikis, and metastasis. It also sought to identify common genes among the pathways linked to these biological processes, determine the level of Bcl-2 expression in various types of cancers, and find a potent inhibitor of Bcl-2 among natural compounds.

Methods: Common genes involved in the pathways related to EMT, autophagy, apoptosis, anoikis, and metastasis were explored, and the level of the most frequently overexpressed gene that was Bcl-2, in various types of cancers was analyzed by gene expression analysis. A set of 102 natural compounds was sorted according to their docking scores using molecular docking and filtering. The top-ranked molecule was chosen for additional molecular dynamics (MD) simulation for 100 ns. Differential gene expression analysis was performed for Dioscin using GEO2R.

Results: The study identified four common genes, Bcl-2, Bax, BIRC3, and CHUK, among the pathways linked to EMT, autophagy, apoptosis, anoikis, and metastasis. Bcl-2 was highly overexpressed in many cancers, including Acute Myeloid Leukemia, Diffuse large B cell lymphoma, and Thymoma. The Dioscin structure in the Bcl-2 binding site received the highest docking score and the most relevant interactions. Dioscin's determined binding free energy by MM/GBSA was -52.21 kcal/mol, while the same calculated by MM/PBSA was -9.18 kcal/mol. A p-value of less than 0.05 was used to determine the statistical significance of the analysis performed using GEO2R. It was observed that Dioscin downregulates Bcl-2, BIRC3, and CHUK and upregulates the pro-apoptotic protein Bax.

Conclusion: The study concluded that Dioscin has the potential to act as a protein inhibitor, with a noteworthy value of binding free energy and relevant interactions with the Bcl-2 binding site. Dioscin might be a good alternative for targeting multiple cancer pathways through a single target.