Calculating 13 C NMR chemical shifts of large molecules using the eXtended ONIOM method at high accuracy with a low cost.

Fragmentation-based methods for nuclear magnetic resonance (NMR) chemical shift calculations have become more and more popular in first-principles calculations of large molecules. However, there are many options for a fragmentation-based method to select, such as theoretical methods, fragmentation schemes, the number of levels of theory, etc. It is important to study the optimal combination of the options to achieve a good balance between accuracy and efficiency. Here we investigate different combinations of options used by a fragmentation-based method, the eXtended ONIOM (XO) method, for 13 C chemical shift calculations on a set of organic and biological molecules. We found that: (1) introducing Hartree-Fock exchange into density functional theory (DFT) could reduce the calculation error due to fragmentation in contrast to pure DFT functionals, while a hybrid functional, xOPBE, is generally recommended; (2) fragmentation schemes generated from the molecular tailoring approach (MTA) with small level parameter n, for example, n = 2 and the degree-based fragmentation method (DBFM) with n = 1, are sufficient to achieve satisfactory accuracy; (3) the two-level XO (XO2) NMR calculation is superior to the calculation with only one level of theory, as the second level (i.e., low level) of theory provides a way to well describe the long-range effect. These findings are beneficial to practical applications of fragmentation-based methods for NMR chemical shift calculations of large molecules.

Exploring therapeutic mechanisms of San-Huang-Tang in nonalcoholic fatty liver disease through network pharmacology and experimental validation.

ETHNOPHARMACOLOGICAL RELEVANCE: San-Huang-Tang (SHT), a traditional Chinese medicine (TCM) formula, has been clinically used to treat obesity and type 2 diabetes mellitus. Recently it has proved that SHT have a good effect on non-alcoholic fatty liver disease (NAFLD). AIM OF THE STUDY: Our study was designed to investigate the therapeutic mechanisms of the SHT against NAFLD. The data of SHT were obtained through network pharmacology platform and validated experimentally in vivo and in vitro. MATERIALS AND METHODS: The candidate targets of SHT were predicted by network pharmacological analysis and crucial targets were chosen by the protein-protein interaction (PPI) network. Furthermore, Gene Ontology (GO) and Kyoto encyclopedia of genes and Genomes (KEGG) were applied to analyze the NAFLD-related signaling pathways affected by SHT, and then the analysis results were verified with molecular biological experiments in vivo and in vitro. RESULTS: Molecules were screened with network pharmacological analysis, and then the improvement of insulin resistance of NAFLD mice was measured by IPITTs and IPGTTs. Through series of molecular experiments, it is revealed that SHT could increase the transcription of insulin receptor (INSR) and insulin receptor substrate (IRS1), and enhance the phosphorylation of both threonine protein kinase (AKT) and forkhead box O1 (FoxO1). CONCLUSIONS: Screened by bioinformatics and verified by experiments in vivo and in vitro, SHT could contribute to NAFLD by affecting insulin resistance via activating INSR/IRS1/AKT/FoxO1 pathway. Our research findings provide not only an experimental basis for the therapeutic effect of SHT but also a new target against NAFLD.

Origin of the temperature dependence of 13C pNMR shifts for copper paddlewheel MOFs.

An efficient protocol for the calculation of 13C pNMR shifts in metal-organic frameworks based on Cu(ii) paddlewheel dimers is proposed, which involves simplified structural models, optimised using GFN2-xTB for the high-spin state, and CAM-B3LYP-computed NMR and EPR parameters. Models for hydrated and activated HKUST-1 and hydrated STAM MOFs with one, two and three Cu dimers have been used. The electronic ground states are low-spin and diamagnetic, with pNMR shifts arising from thermal population of intermediate- and high-spin excited states. Treating individual spin configurations in a broken symmetry (BS) approach, and selecting two or more of these to describe individual excited states, the magnetic shieldings of these paramagnetic states are evaluated using the approach by Hrobárik and Kaupp. The total shielding is then evaluated from a Boltzmann distribution between the energy levels of the chosen configurations. The computed pNMR shifts are very sensitive to temperature and, therefore, to the relative energies of the BS spin states. In order to reproduce the temperature dependence of the pNMR shifts seen in experiment, some scaling of the calculated energy gaps is required. A single scaling factor was applied to all levels in any one system, by fitting to experimental results at several temperatures simultaneously. The resulting scaling factor decreases with an increasing number of dimer units in the model (e.g., from ∼1.7 for mono-dimer models to 1.2 for tri-dimer models). The approach of this scaling factor towards unity indicates that models with three dimers are approaching a size where they can be considered as reasonable models for the 13C shifts of infinite MOFs. The observed unusual temperature dependencies in the latter are indicated to arise both from the "normal" temperature dependence of the pNMR shifts of the paramagnetic states and the populations of these states in the thermal equilibrium.

[Molecular mechanism of Epimedii Folium in treatment of osteoporosis based on network pharmacology].

Osteoporosis is a systematic bone disease,characterized by deterioration in bone mass or micro-architecture,and increasing risk of fragility and fractures. With the development of aging problems,osteoporosis has been a global health problem. At present,due to the undesirable side effects of synthetic osteoporosis inhibitors,more efforts are made in treatment of osteoporosis by traditional Chinese medicine and its prescriptions. Epimedii Folium,one of the most common herbs for osteoporosis,has attracted great attentions worldwide.In this study,network pharmacology was employed to analyze the active components and potential molecular mechanism of Epimedii Folium on osteoporosis. Component-target network analysis showed that those with higher molecular network degree were flavonoids,with estrogen-like activity,antioxidation and free radical-scavenging activities,playing certain roles in preventing and treating osteoporosis. On the other hand,the targets with high degree were mostly related with sex hormone,osteoclast differentiation,bone matrix degradation,and reactive oxygen species in drug-target network. Multiple components of Epimedii Folium could be interacted with these targets. This study shows that Epimedium could prevent and treat osteoporosis through multiple active ingredients acting on multiple targets.

NMR chemical shifts of urea loaded copper benzoate. A joint solid-state NMR and DFT study.

We report solid-state 13C NMR spectra of urea-loaded copper benzoate, Cu2(C6H5CO2)4·2(urea), a simplified model for copper paddlewheel-based metal-organic frameworks (MOFs), along with first-principles density functional theory (DFT) computation of the paramagnetic NMR (pNMR) chemical shifts. Assuming a Boltzmann distribution between a diamagnetic open-shell singlet ground state (in a broken-symmetry Kohn-Sham DFT description) and an excited triplet state, the observed δ(13C) values are reproduced reasonably well at the PBE0-⅓/IGLO-II//PBE0-D3/AE1 level. Using the proposed assignments of the signals, the mean absolute deviation between computed and observed 13C chemical shifts is below 30 ppm over a range of more than 1100 ppm.

Calculation and experimental measurement of paramagnetic NMR parameters of phenolic oximate Cu(ii) complexes.

We present a strategy for predicting the unusual 1H and 13C shifts in NMR spectra of paramagnetic bisoximato copper(ii) complexes using DFT. We demonstrate good agreement with experimental measurements, although 1H-13C correlation spectra show that a combined experimental and theoretical approach remains necessary for full assignment.

Discovery of a potent angiotensin converting enzyme inhibitor via virtual screening.

Prompted by the prominent role of angiotensin converting enzyme (ACE) in hypertension, heart failures, myocardial infarction and diabetic nephropathy, we have attempted to discover novel ACE inhibitors through ligand-based virtual screening. Molecular docking method and rigorously validated model was utilized to search a natural compounds database. Finally, 36 compounds were randomly selected and subjected to in vitro ACE kinase inhibitory assay using fluorescence assays method. The results showed that three compounds (Licochalcone A, Echinatin and EGCG) have strong potential to be developed as a new class of ACE inhibitors. Further chemical modification via fragment modifications guided by structure and ligand-based computational methodologies can lead to discover better agents as potential clinical candidates.

[Effects of ginkgolide A, B and K on platelet aggregation].

To investigate the effects of ginkgolide A (GA), ginkgolide B (GB) and ginkgolide K (GK) on platelet aggregation in rabbits, and compare the similarities and differences among these three components. The effects of different doses of ginkgolide A, B and K on platelet aggregation induced by platelet activating factor (PAF) were observed by using in vitro experiment. The results showed that three compounds could inhibit platelet aggregation induced by PAF in vitro, and the intensity was GK> GB> GA. It was further found that all of them can mobilize [Ca2+]i and enhance intracellular c-AMP level in a dose-dependent manner, which was consistent to the ability to antagonize PAF receptor. These findings indicated that GK was highly selective for PAF receptor, and may inhibit platelet aggregation by activating cAMP signaling pathway and inhibiting intracellular [Ca2+]i mobilization; GB and GA also had strong antagonism to PAF receptor, but the effect was weaker than that of GK.

[Cerebral vascular protective effect of ginkgo diterpene lactone meglumine injection].

The left middle cerebral artery occlusion (MCAO) model was made by inserting the nylon thread plug into the internal carotid artery. The behavioral score, cerebral infarction area, brain water content, ethidium bromide (EB) spillover, coagulation four indices, occludin and MMP-9 expression in brain tissues were detected after 14 days of administration, to investigate whether the protective effect of ginkgo diterpene lactone meglumine injection (GDLMI) which had obvious protective effect on cerebral ischemic injury in the previous experiment was related to reducing the permeability of the blood-brain barrier (BBB) and reducing the risk of bleeding, and to explore its possible mechanism of action. The results showed that GDLMI could effectively alleviate the behavioral changes caused by MCAO at 24 h, reduce the behavioral score, improve the edema of brain tissue, reduce the EB overflow rate, reduce the bleeding tendency caused by long-term administration, significantly reduce the occlusion deficiency in ischemic brain tissue of model rats, and down-regulate MMP-9 expression. The above results indicate that GDLMI has obvious effect on cerebral ischemia, and the therapeutic effect of GDLMI may mainly depend on lowering the permeability of blood-brain barrier to improve brain edema.

Luteoloside Acts as 3C Protease Inhibitor of Enterovirus 71 In Vitro.

Luteoloside is a member of the flavonoids family that exhibits several bioactivities including anti-microbial and anti-cancer activities. However, the antiviral activity of luteoloside against enterovirus 71 (EV71) and the potential mechanism(s) responsible for this effect remain unknown. In this study, the antiviral potency of luteoloside against EV71 and its inhibitory effects on 3C protease activity were evaluated. First, we investigated the cytotoxicity of luteoloside against rhabdomyosarcoma (RD) cells, which was the cell line selected for an in vitro infection model. In a subsequent antiviral assay, the cytopathic effect of EV71 was significantly and dose-dependently relieved by the administration of luteoloside (EC50 = 0.43 mM, selection index = 5.3). Using a plaque reduction assay, we administered luteoloside at various time points and found that the compound reduced EV71 viability in RD cells rather than increasing defensive mobilization or viral absorption. Moreover, biochemical studies focused on VP1 (a key structural protein of EV71) mRNA transcript and protein levels also revealed the inhibitory effects of luteoloside on the EV71 viral yield. Finally, we performed inhibition assays using luteoloside to evaluate its effect on recombinant 3C protease activity. Our results demonstrated that luteoloside blocked 3C protease enzymatic activity in a dose-dependent manner (IC50 = 0.36 mM) that was similar to the effect of rutin, which is a well-known C3 protease inhibitor. Collectively, the results from this study indicate that luteoloside can block 3C protease activity and subsequently inhibit EV71 production in vitro.

Drug discovery of neurodegenerative disease through network pharmacology approach in herbs.

Neurodegenerative diseases, referring to as the progressive loss of structure and function of neurons, constitute one of the major challenges of modern medicine. Traditional Chinese herbs have been used as a major preventive and therapeutic strategy against disease for thousands years. The numerous species of medicinal herbs and Traditional Chinese Medicine (TCM) compound formulas in nervous system disease therapy make it a large chemical resource library for drug discovery. In this work, we collected 7362 kinds of herbs and 58,147 Traditional Chinese medicinal compounds (Tcmcs). The predicted active compounds in herbs have good oral bioavailability and central nervous system (CNS) permeability. The molecular docking and network analysis were employed to analyze the effects of herbs on neurodegenerative diseases. In order to evaluate the predicted efficacy of herbs, automated text mining was utilized to exhaustively search in PubMed by some related keywords. After that, receiver operator characteristic (ROC) curves was used to estimate the accuracy of predictions. Our study suggested that most herbs were distributed in family of Asteraceae, Fabaceae, Lamiaceae and Apocynaceae. The predictive model yielded good sensitivity and specificity with the AUC values above 0.800. At last, 504 kinds of herbs were obtained by using the optimal cutoff values in ROC curves. These 504 herbs would be the most potential herb resources for neurodegenerative diseases treatment. This study would give us an opportunity to use these herbs as a chemical resource library for drug discovery of anti-neurodegenerative disease.

[Study on effective substance basis and molecular mechanism of Qigui Tongfeng tablet using network pharmacology method].

Qigui Tongfeng tablet (QLTFT) is a traditional Chinese medicine with good effect for treating gout. Here, network pharmacology method and molecular similarity analysis were utilized to study the effective substance basis and molecular mechanism of the QLTFT on the gout. The similarity to the medicinal compounds is reflected in the Tanimoto coefficient that gives the structural similarity of two compounds. Operationally, similar modifiers were described as pairs of concepts with a similarity score of 0. 500. The results of the molecular similarity analysis suggested that the flavonoids in QLTFT could be new leads for gout. Furthermore, complex biological systems may be represented and analyzed as computable networks. Two important properties of a network were degree and betweenness. Nodes with high degree or high betweenness may play important roles in the overall composition of a network. And the results of network analysis showed that dongbeinine, verticinone-N-oxide, verticine N-oxide, peimine, peiminine, isobaimonidine, dongbeirine, peimisine and simi-arenol which with high degree acted on xanthine dehydrogenase/oxidase, matrix metalloproteinase-9, an arachidonate 5-lipoxygenase-activating protein, tyrosine-protein kinase and etc. Inhibition of these targets can prevent the formation of uric acid, reduce inflammation by uric acid and regulate the body's immune response. Thus, these compounds may be the main effective substance basis. The research results not only reveals its molecular mechanism, but also provide a theoretical basis for the quality control of drugs and clinical application.

[Study of effective components and molecular mechanism for Guizhi Fuling formula treatment of dysmenorrhea, pelvic inflammatory disease and uterine fibroids].

In this study, the active components and potential molecular .mechanism of Guizhi Fuling formula in treatment on dysmenorrhea, pelvic inflammation, and hysteromyoma were investigated using network pharmacological methods. Sterols and pentacyclic triterpenes, with high moleculal network degree, revealed promising effects on anti-inflammatory, analgesic, anti-tumor, and immune-regulation, according to D-T network analysis. On the other hand, the targets with high degree were involved in inflammatory, coagulation, angiopoiesis, smooth muscle contraction, and cell reproduction, which showed the novel function in anti-dysmenorrhea, pelvic inflammation, and hysteromyoma. Furthermore, the formula was indicated to play a key role in smooth muscle proliferation, inhibition of new vessels, circulation improvement, reduction of hormone secretion, alleviation of smooth muscle, block of arachidonic acid metabolism, and inflammation in uterus. Thus, the main mechanism of Guizhi Fuling formula was summarized. In conclusion, Guizhi Fuling formula was proven to alleviated dysmenorrhea, pelvic inflammation, and hysteromyoma by acting on multiple targets through several bioactive compounds, regulating 21 biological pathways.

[Monitor on influence of quality standard improvement upon Guizhi Fuling capsules efficacy].

In 2012, the preparation process and quality standard for Guizhi Fuling capsule were improved. To compare the effects and differences of capsules before (2011) and after(2012-2014) the improvement, evaluation models for intrinsic dysmenorrhea, pelvic inflammation and hysteromyoma were applied in rats. Models were induced by oxytocin, liqiud bacteria mixture and estrogen loading, respectively. The capsules (12 batchs/year, 48 bathcs in all), sampled randomly in 2011-2014, the effects were assessed using the three models. In anti-dysmenorrhea models, remarked reduction of writhing frequency, ET-1 and PGF2α content in uterus could be detected, as well as extension of writhing latency. In pelvic inflammation rats, depression of TNF-α and raise of IL-2 were induced by earh batch of capsules. In hysteromyoma model, uterine weight and smooth muscle proliferation, including E2 and P level in plasma, were lowered obviously by all batchs of capsules. Secondly, Guizhi Fuling capsules produced in 2012-2014 revealed better effectiveness than the ones manufactured in 2011. Moreover, pharmacodynamics indexes of the samples made in 2011 differed significantly between groups, which could not be observed in the ones ot 2012-2014. After tne preparation process and quality standard improvement, the effectiveness and homogeneity of Guizhi Fuling capsules were enhanced.

An efficient multistep ligand-based virtual screening approach for GPR40 agonists.

G protein-coupled receptor 40/free fatty acid receptor 1 (GPR40/FFAR1) is a member of the GPCR superfamily, and GPR40 agonists have therapeutic potential for type 2 diabetes. With the crystal structure of GPR40 currently unavailable, various ligand-based virtual screening approaches can be applied to identify novel agonists of GPR40. It is known that each ligand-based method has its own advantages and limitations. To improve the efficiency of individual ligand-based methods, an efficient multistep ligand-based virtual screening approach is presented in this study, including the pharmacophore-based screening, physicochemical property filtering, protein-ligand interaction fingerprint similarity analysis, and 2D-fingerprint structural similarity search. A focused decoy library was generated and used to evaluate the efficiency of this virtual screening protocol. This multistep workflow not only significantly improved the hit rate compared with each individual ligand-based method, but also identified diverse known actives from decoys. This protocol may serve as an efficient virtual screening tool for the targets without crystal structures available to discover novel active compounds.

An integrated virtual screening approach for VEGFR-2 inhibitors.

In recent years, various virtual screening (VS) tools have been developed, and many successful screening campaigns have been showcased. However, whether by conventional molecular docking or pharmacophore screening, the selection of virtual hits is based on the ranking of compounds by scoring functions or fit values, which remains the bottleneck of VS due to insufficient accuracy. As the limitations of individual methods persist, a comprehensive comparison and integration of different methods may provide insights into selecting suitable methods for VS. Here, we evaluated the performance of molecular docking, fingerprint-based 2D similarity and multicomplex pharmacophore in an individual and a combined manner, through a retrospective VS study on VEGFR-2 inhibitors. An integrated two-layer workflow was developed and validated through VS of VEGFR-2 inhibitors against the DUD-E database, which demonstrated improved VS performance through a ligand-based method ECFP_4, followed by molecular docking, and then a strict multicomplex pharmacophore. Through a retrospective comparison with six published papers, this integrated approach outperformed 43 out of 45 methods, indicating a great effectiveness. This kind of integrated VS approach can be extended to other targets for the screening and discovery of inhibitors.

Fragment-based strategy for structural optimization in combination with 3D-QSAR.

Fragment-based drug design has emerged as an important methodology for lead discovery and drug design. Different with other studies focused on fragment library design and active fragment identification, a fragment-based strategy was developed in combination with three-dimensional quantitative structure-activity relationship (3D-QSAR) for structural optimization in this study. Based on a validated scaffold or fragment hit, a series of structural optimization was conducted to convert it to lead compounds, including 3D-QSAR modelling, active site analysis, fragment-based structural optimization and evaluation of new molecules. 3D-QSAR models and active site analysis provided sufficient information for confirming the SAR and pharmacophoric features for fragments. This strategy was evaluated through the structural optimization on a c-Met inhibitor scaffold 5H-benzo[4,5]cyclohepta[1,2-b]pyridin-5-one, which resulted in an c-Met inhibitor with high inhibitory activity. Our study suggested the effectiveness of this fragment-based strategy and the druggability of our newly explored active region. The reliability of this strategy indicated it could also be applied to facilitate lead optimization of other targets.

De novo design of N-(pyridin-4-ylmethyl)aniline derivatives as KDR inhibitors: 3D-QSAR, molecular fragment replacement, protein-ligand interaction fingerprint, and ADMET prediction.

Vascular endothelial growth factor (VEGF) and its receptor tyrosine kinase VEGFR-2 or kinase insert domain receptor (KDR) have been identified as promising targets for novel anticancer agents. To achieve new potent inhibitors of KDR, we conducted molecular fragment replacement (MFR) studies for the understanding of 3D-QSAR modeling and the docking investigation of arylphthalazines and 2-((1H-Azol-1-yl)methyl)-N-arylbenzamides-based KDR inhibitors. Two favorable 3D-QSAR models (CoMFA with q(2), 0.671; r(2), 0.969; CoMSIA with q(2), 0.608; r(2), 0.936) have been developed to predict the biological activity of new compounds. The new molecular database generated by MFR was virtually screened using Glide (docking) and further evaluated with CoMFA prediction, protein-ligand interaction fingerprint (PLIF) and ADMET analysis. 44 N-(pyridin-4-ylmethyl)aniline derivatives as novel potential KDR inhibitors were finally obtained. In this paper, the work flow developed could be applied to de novo drug design and virtual screening potential KDR inhibitors, and use hit compounds to further optimize and design new potential KDR inhibitors.