<i>In silico</i> Target Fishing for the Potential Targets and Molecular Mechanisms of Baicalein as an Antiparkinsonian Agent: Discovery of the Protective Effects on <scp>NMDA</scp> Receptor‐Mediated Neurotoxicity

Gao, Li; Fang, Jiansong; Bai, Xiaoyu; Zhou, Dan; Wang, Ying; Liu, Ailin; Du, Guanhua

doi:10.1111/cbdd.12127

Cited by 19 publications

(11 citation statements)

References 54 publications

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“…18 The utility of these rapid and cost-effective virtual methods has been applied to elucidate the ligand–target (including unperceived off-target) interactions for synthetic therapeutics such as PRIMA-1, 20 4 H-tamoxifen, 21 torcetrapib 22 as well as organic compounds such as vitamin E, 21 catechin (a polyphenol) 23 and baicalein (a flavonoid). 24 …”

Section: Introductionmentioning

confidence: 99%

Nimbolide targets BCL2 and induces apoptosis in preclinical models of Waldenströms macroglobulinemia

Chitta

Paulus

Caulfield

et al. 2014

Blood Cancer Journal

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Neem leaf extract (NLE) has medicinal properties, which have been attributed to its limonoid content. We identified the NLE tetranorterpenoid, nimbolide, as being the key limonoid responsible for the cytotoxicity of NLE in various preclinical models of human B-lymphocyte cancer. Of the models tested, Waldenströms macroglobulinemia (WM) cells were most sensitive to nimbolide, undergoing significant mitochondrial mediated apoptosis. Notably, nimbolide toxicity was also observed in drug-resistant (bortezomib or ibrutinib) WM cells. To identify putative targets of nimbolide, relevant in WM, we used chemoinformatics-based approaches comprised of virtual in silico screening, molecular modeling and target–ligand reverse docking. In silico analysis revealed the antiapoptotic protein BCL2 was the preferential binding partner of nimbolide. The significance of this finding was further tested in vitro in RS4;11 (BCL2-dependent) tumor cells, in which nimbolide induced significantly more apoptosis compared with BCL2 mutated (Jurkat BCL2Ser70-Ala) cells. Lastly, intraperitoneal administration of nimbolide in WM tumor xenografted mice, significantly reduced tumor growth and IgM secretion in vivo, while modulating the expression of several proteins as seen on immunohistochemistry. Overall, our data demonstrate that nimbolide is highly active in WM cells, as well as other B-cell cancers, and engages BCL2 to exert its cytotoxic activity.

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Section: Introductionmentioning

confidence: 99%

Nimbolide targets BCL2 and induces apoptosis in preclinical models of Waldenströms macroglobulinemia

Chitta

Paulus

Caulfield

et al. 2014

Blood Cancer Journal

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“…Finally, one application combined all three methods for reverse screening. Gao et al used the Pharmacophore Modeling and Docking modules in Schrödinger as well as RerverseScreen3D jointly to predict molecular targets and found that baicalein (compound 16 ), an anti-Parkinson disease drug, played a protective role in the nervous system by targeting catechol-O-methyltransferase (COMT) and monoamine oxidase B (MAO-B); these targets were confirmed experimentally (Gao et al, 2013 ).…”

Section: Methodsmentioning

confidence: 99%

Reverse Screening Methods to Search for the Protein Targets of Chemopreventive Compounds

et al. 2018

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This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.

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“…The intracellular ROS level was determined using 2′,7′‐dichlorodihydrofluorescein diacetate (DCFH‐DA) fluorescent probe (Sigma‐Aldrich), as described previously . Cells were treated with various concentrations of 17‐DMAG (0.3 n m , 1 n m and 3 n m ) for 1 h, followed by incubation with 2 μ m rotenone or vehicle control for 24 h. Then, the cells were incubated with 10 μ m DCFH‐DA and 10 μ m Hoechst 33 234 for 20 min at 37 °C in the dark, and washed twice with NaCl/P i .…”

Section: Methodsmentioning

confidence: 99%

Discovery of the neuroprotective effects of alvespimycin by computational prioritization of potential anti‐parkinson agents

et al. 2014

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Based on public gene expression data, we propose a computational approach to optimize gene expression signatures for the use with Connectivity Map (CMap) to reposition drugs or discover lead compounds for Parkinson's disease. This approach integrates genetic information from the Gene Expression Omnibus (GEO) database, the Parkinson's disease gene expression database (ParkDB), the Online Mendelian Inheritance in Man (OMIM) database and the Comparative Toxicogenomics Database (CTD), with the aim of identifying a set of interesting genes for use in computational drug screening via CMap. The results showed that CMap, using the top 20 differentially expressed genes identified by our approach as a gene expression signature, outperformed the same method using all differentially expressed genes (n = 535) as a signature. Utilizing this approach, the candidate compound alvespimycin (17-DMAG) was selected for experimental evaluation in a model of rotenone-induced toxicity in human SH-SY5Y neuroblastoma cells and isolated rat brain mitochondria. The results showed that 17-DMAG significantly attenuated rotenone-induced toxicity, as reflected by the increase of cell viability, the reduction of intracellular reactive oxygen species generation and a reduction in mitochondrial respiratory dysfunction. In conclusion, this computational method provides an effective systematic approach for drug repositioning or lead compound discovery for Parkinson's disease, and the discovery of the neuroprotective effects of 17-DMAG supports the practicability of this method.

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In silico Target Fishing for the Potential Targets and Molecular Mechanisms of Baicalein as an Antiparkinsonian Agent: Discovery of the Protective Effects on NMDA Receptor‐Mediated Neurotoxicity

Cited by 19 publications

References 54 publications

Nimbolide targets BCL2 and induces apoptosis in preclinical models of Waldenströms macroglobulinemia

Nimbolide targets BCL2 and induces apoptosis in preclinical models of Waldenströms macroglobulinemia

Reverse Screening Methods to Search for the Protein Targets of Chemopreventive Compounds

Discovery of the neuroprotective effects of alvespimycin by computational prioritization of potential anti‐parkinson agents

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