Publications by authors named "Xiaoqin Tan"

19 Publications

  • Page 1 of 1

Isoorientin Affects Markers of Alzheimer's Disease via Effects on the Oral and Gut Microbiota in APP/PS1 Mice.

J Nutr 2021 Oct 12. Epub 2021 Oct 12.

Beijing Agro-Biotechnology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China.

Background: There is growing evidence of strong associations between the pathogenesis of Alzheimer's disease (AD) and dysbiotic oral and gut microbiota. Recent studies demonstrated that isoorientin (ISO) is anti-inflammatory and alleviates markers of AD, which were hypothesized to be mediated by the oral and gut microbiota.

Objectives: We studied the effects of oral administration of ISO on AD-related markers and the oral and gut microbiota in mice.

Methods: Eight-month-old amyloid precursor protein/presenilin-1 (AP) transgenic male mice were randomly allocated to 3 groups of 15 mice each: vehicle (AP) alone or with a low dose of ISO (AP + ISO-L; 25 mg/kg) or a high dose of ISO (AP + ISO-H; 50 mg/kg). Age-matched wild-type (WT) C57BL/6 male littermates were used as controls. The 4 groups were treated intragastrically with ISO or sterilized ultrapure water for 2 months. AD-related markers in the brain, serum, colon, and liver were analyzed with immunohistochemical and histochemical staining, Western blotting, and ELISA. Oral and gut microbiotas were analyzed using 16S ribosomal RNA gene sequencing.

Results: The high-dose ISO treatment significantly decreased amyloid beta 42-positive deposition by 38.1% and 45.2% in the cortex and hippocampus, respectively, of AP mice (P < 0.05). Compared with the AP group, both ISO treatments reduced brain phospho-Tau, phosphor-p65, phosphor-inhibitor of NF-κB, and brain and serum LPS and TNF-α by 17.9%-72.5% and increased brain and serum IL-4 and IL-10 by 130%-210% in the AP + ISO-L and AP + ISO-H groups (P < 0.05). Abundances of 26, 25, and 23 microbial taxa in oral, fecal and cecal samples, respectively, were increased in both the AP + ISO-L and AP + ISO-H groups relative to the AP group [linear discriminant analysis (LDA) >3.0; P < 0.05]. Gram-negative bacteria, Alteromonas, Campylobacterales, and uncultured Bacteroidales bacterium were positively correlated (rho = 0.28-0.59; P < 0.05) with the LPS levels and responses of inflammatory cytokines.

Conclusions: The microbiota-gut-brain axis is a potential mechanism by which ISO reduces AD-related markers in AP mice.
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http://dx.doi.org/10.1093/jn/nxab328DOI Listing
October 2021

Generative Models for De Novo Drug Design.

J Med Chem 2021 Oct 17;64(19):14011-14027. Epub 2021 Sep 17.

Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.

Artificial intelligence (AI) is booming. Among various AI approaches, generative models have received much attention in recent years. Inspired by these successes, researchers are now applying generative model techniques to de novo drug design, which has been considered as the "holy grail" of drug discovery. In this Perspective, we first focus on describing models such as recurrent neural network, autoencoder, generative adversarial network, transformer, and hybrid models with reinforcement learning. Next, we summarize the applications of generative models to drug design, including generating various compounds to expand the compound library and designing compounds with specific properties, and we also list a few publicly available molecular design tools based on generative models which can be used directly to generate molecules. In addition, we also introduce current benchmarks and metrics frequently used for generative models. Finally, we discuss the challenges and prospects of using generative models to aid drug design.
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http://dx.doi.org/10.1021/acs.jmedchem.1c00927DOI Listing
October 2021

Isoorientin Inhibits Inflammation in Macrophages and Endotoxemia Mice by Regulating Glycogen Synthase Kinase 3.

Mediators Inflamm 2020 27;2020:8704146. Epub 2020 Oct 27.

Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, China.

Isoorientin has anti-inflammatory effects; however, the mechanism remains unclear. We previously found isoorientin is an inhibitor of glycogen synthase kinase 3 (GSK3) . Overactivation of GSK3 is associated with inflammatory responses. GSK3 is inactivated by phosphorylation at Ser9 (i.e., p-GSK3). Lithium chloride (LiCl) inhibits GSK3 and also increases p-GSK3 (Ser9). The present study investigated the anti-inflammatory effect and mechanism of isoorientin via GSK3 regulation in lipopolysaccharide- (LPS-) induced RAW264.7 murine macrophage-like cells and endotoxemia mice. LiCl was used as a control. While AKT phosphorylates GSK3, MK-2206, a selective AKT inhibitor, was used to activate GSK3 via AKT inhibition (i.e., not phosphorylate GSK3 at Ser9). The proinflammatory cytokines TNF-, IL-6, and IL-1 were detected by ELISA or quantitative real-time PCR, while COX-2 by Western blotting. The p-GSK3 and GSK3 downstream signal molecules, including NF-B, ERK, Nrf2, and HO-1, as well as the tight junction proteins ZO-1 and occludin were measured by Western blotting. The results showed that isoorientin decreased the production of TNF-, IL-6, and IL-1 and increased the expression of p-GSK3 and , similar to LiCl. Coadministration of isoorientin and LiCl showed antagonistic effects. Isoorientin decreased the expression of COX-2, inhibited the activation of ERK and NF-B, and increased the activation of Nrf2/HO-1 in LPS-induced RAW264.7 cells. Isoorientin increased the expressions of occludin and ZO-1 in the brain of endotoxemia mice. In summary, isoorientin can inhibit GSK3 by increasing p-GSK3 and regulate the downstream signal molecules to inhibit inflammation and protect the integrity of the blood-brain barrier and the homeostasis in the brain.
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http://dx.doi.org/10.1155/2020/8704146DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7641714PMC
September 2021

DrugSpaceX: a large screenable and synthetically tractable database extending drug space.

Nucleic Acids Res 2021 01;49(D1):D1170-D1178

Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.

One of the most prominent topics in drug discovery is efficient exploration of the vast drug-like chemical space to find synthesizable and novel chemical structures with desired biological properties. To address this challenge, we created the DrugSpaceX (https://drugspacex.simm.ac.cn/) database based on expert-defined transformations of approved drug molecules. The current version of DrugSpaceX contains >100 million transformed chemical products for virtual screening, with outstanding characteristics in terms of structural novelty, diversity and large three-dimensional chemical space coverage. To illustrate its practical application in drug discovery, we used a case study of discoidin domain receptor 1 (DDR1), a kinase target implicated in fibrosis and other diseases, to show DrugSpaceX performing a quick search of initial hit compounds. Additionally, for ligand identification and optimization purposes, DrugSpaceX also provides several subsets for download, including a 10% diversity subset, an extended drug-like subset, a drug-like subset, a lead-like subset, and a fragment-like subset. In addition to chemical properties and transformation instructions, DrugSpaceX can locate the position of transformation, which will enable medicinal chemists to easily integrate strategy planning and protection design.
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http://dx.doi.org/10.1093/nar/gkaa920DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778939PMC
January 2021

Isoorientin, a GSK-3β inhibitor, rescues synaptic dysfunction, spatial memory deficits and attenuates pathological progression in APP/PS1 model mice.

Behav Brain Res 2021 02 16;398:112968. Epub 2020 Oct 16.

Department of Molecular Biosciences and Bioengineering, University of Hawaii at Manoa, 1955 East-West Road, Honolulu, HI 96822, United States. Electronic address:

β-Amyloid (Aβ) elevation, tau hyperphosphorylation, and neuroinflammation are major hallmarks of Alzheimer's disease (AD). Glycogen synthase kinase-3β (GSK-3β) is a key protein kinase implicated in the pathogenesis of AD. Blockade of GSK-3β is an attractive therapeutic strategy for AD. Isoorientin, a 6-C-glycosylflavone, was previously shown to be a highly selective inhibitor of GSK-3β, while exerting neuroprotective effects in neuronal models of AD. In the present study, we evaluated the in vivo effects of isoorientin on GSK-3β, tau phosphorylation, Aβ deposition, neuroinflammatory response, long-term potentiation, and spatial memory in amyloid precursor protein/presenilin 1 (APP/PS1) transgenic mice using biochemical, electrophysiological, and behavioral tests. Chronic oral administration of isoorientin to APP/PS1 mice at 8 months of age attenuated multiple AD pathogenic hallmarks in the brains, including GSK-3β overactivation, tau hyperphosphorylation, Aβ deposition, and neuroinflammation. For neuroinflammation, isoorientin treatment reduced the number of activated microglia associated with Aβ-positive plaques, and in parallel reduced the levels of pro-inflammatory factors in the brains of APP/PS1 mice. Strikingly, isoorientin reversed deficits in synaptic long-term potentiation and spatial memory relevant to cognitive functions. Together, the findings suggest that isoorientin is a brain neuroprotector and may be a promising drug lead for treatment of AD and related neurodegenerative disorders.
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http://dx.doi.org/10.1016/j.bbr.2020.112968DOI Listing
February 2021

Inhibitory effect of sinomenine on lung cancer cells via negative regulation of α7 nicotinic acetylcholine receptor.

J Leukoc Biol 2021 04 29;109(4):843-852. Epub 2020 Jul 29.

Guangzhou University of Chinese Medicine, Guangzhou, P. R. China.

Lung cancer is the leading cause of cancer deaths worldwide, with a high morbidity and less than 20% survival rate. Therefore, new treatment strategies and drugs are needed to reduce the mortality of patients with lung cancer. α7 nicotinic acetylcholine receptor (α7 nAChR), as a receptor of nicotine and its metabolites, is a potential target for lung cancer treatment. Our previous studies revealed that sinomenine plays anti-inflammation roles via α7 nAChR and down-regulates the expression of this receptor, thus increasing the inflammatory response. Hence, sinomenine is possibly a natural ligand of this receptor. In the present study, the effects of sinomenine on lung cancer A549 cells and tumor-bearing mice were determined to investigate whether this alkaloid has an inhibitory effect on lung cancer via α7 nAChR. CCK-8 assay, wound-healing test, and flow cytometry were performed for cell proliferation, cell migration, and apoptosis analysis in vitro, respectively. Xenograft mice were used to evaluate the effects of sinomenine in vivo. Results showed that sinomenine decreased cell proliferation and migration abilities but increased the percentage of apoptotic cells. Tumor volume in tumor-bearing mice was significantly reduced after sinomenine treatment compared with that in the vehicle group mice (p < 0.05). Furthermore, the effects of sinomenine were abolished by the α7 nAChR antagonist mecamylamine and the allosteric modulator PNU-120596, but no change occurred when the mice were pretreated with the muscarinic acetylcholine receptor antagonist atropine. Meanwhile, sinomenine suppressed α7 nAChR expression in vitro and in vivo, as well as the related signaling molecules pERK1/2 and ERK1/2 and the transcription factors TTF-1 and SP-1. By contrast, sinomenine up-regulated the expression of another transcription factor, Egr-1. These effects were restricted by mecamylamine and PNU but not by atropine. Results suggested that sinomenine can inhibit lung cancer via α7 nAChR in a negative feedback mode.
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http://dx.doi.org/10.1002/JLB.6MA0720-344RRRDOI Listing
April 2021

Automated design and optimization of multitarget schizophrenia drug candidates by deep learning.

Eur J Med Chem 2020 Oct 12;204:112572. Epub 2020 Jul 12.

Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai, 201203, China; University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing, 100049, China; Shanghai Institute for Advanced Immunochemical Studies, And School of Life Science and Technology, ShanghaiTech University, 393 Huaxiazhong Road, Shanghai, 200031, China. Electronic address:

Complex neuropsychiatric diseases such as schizophrenia require drugs that can target multiple G protein-coupled receptors (GPCRs) to modulate complex neuropsychiatric functions. Here, we report an automated system comprising a deep recurrent neural network (RNN) and a multitask deep neural network (MTDNN) to design and optimize multitarget antipsychotic drugs. The system has successfully generated novel molecule structures with desired multiple target activities, among which high-ranking compound 3 was synthesized, and demonstrated potent activities against dopamine D, serotonin 5-HT and 5-HT receptors. Hit expansion based on the MTDNN was performed, 6 analogs of compound 3 were evaluated experimentally, among which compound 8 not only exhibited specific polypharmacology profiles but also showed antipsychotic effect in animal models with low potential for sedation and catalepsy, highlighting their suitability for further preclinical studies. The approach can be an efficient tool for designing lead compounds with multitarget profiles to achieve the desired efficacy in the treatment of complex neuropsychiatric diseases.
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http://dx.doi.org/10.1016/j.ejmech.2020.112572DOI Listing
October 2020

TransformerCPI: improving compound-protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments.

Bioinformatics 2020 08;36(16):4406-4414

Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.

Motivation: Identifying compound-protein interaction (CPI) is a crucial task in drug discovery and chemogenomics studies, and proteins without three-dimensional structure account for a large part of potential biological targets, which requires developing methods using only protein sequence information to predict CPI. However, sequence-based CPI models may face some specific pitfalls, including using inappropriate datasets, hidden ligand bias and splitting datasets inappropriately, resulting in overestimation of their prediction performance.

Results: To address these issues, we here constructed new datasets specific for CPI prediction, proposed a novel transformer neural network named TransformerCPI, and introduced a more rigorous label reversal experiment to test whether a model learns true interaction features. TransformerCPI achieved much improved performance on the new experiments, and it can be deconvolved to highlight important interacting regions of protein sequences and compound atoms, which may contribute chemical biology studies with useful guidance for further ligand structural optimization.

Availability And Implementation: https://github.com/lifanchen-simm/transformerCPI.
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http://dx.doi.org/10.1093/bioinformatics/btaa524DOI Listing
August 2020

Ethylcellulose-based drug nano depots fabricated using a modified triaxial electrospinning.

Int J Biol Macromol 2020 Jun 22;152:68-76. Epub 2020 Feb 22.

College of Chemistry & Chemical Engineering, Wuhan Textile University, Wuhan 430200, China. Electronic address:

New strategies based on advanced technologies are highly desired for expanding the applications of biological macromolecules in the applied scientific fields. In the present study, a new kind of core-shell nano depots were designed, in which the shell section was a drug-polymer composite and the core section was a drug reservoir. With ethyl cellulose and ketoprofen as a filament-forming polymeric matrix and a model drug, respectively, a triaxial electrospinning apparatus was developed to conduct both coaxial and triaxial processes, by which monolithic nanofibers F1 and core-shell nano depots F2 were successfully prepared. Although both of them had the same double components, their different nanostructures generated considerable differences in providing drug sustained release profiles. The core-shell nanofiber depots F2 were able to provide a better zero-order drug release profile: no initial burst release, smooth sustained release effect, and smaller tailing-off release for a nice zero-order drug release kinetics. The release percentage (Q) can be linearly manipulated through the release time (t) according to the equation Q = 9.40 + 4.74 t (R = 0.9936), providing opportunity for precise administration. The developed strategy and advanced electrospinning technique exhibit a new way for constructing process-structure-performance relationships at nano scale and for expanding the potential applications of biological macromolecules in the applied fields.
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http://dx.doi.org/10.1016/j.ijbiomac.2020.02.239DOI Listing
June 2020

Discovery of novel glyceraldehyde-3-phosphate dehydrogenase inhibitor via docking-based virtual screening.

Bioorg Chem 2020 03 25;96:103620. Epub 2020 Jan 25.

Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin Second Road, Shanghai 200025, China. Electronic address:

Glycolysis is enhanced in cancer cells. Cancer cells utilize glycolysis as their primary energy source, even under aerobic conditions. This is known as the Warburg effect. Thus, effective inhibition of the glycolytic pathway is a crucial component of cancer therapy. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is an important enzyme in glycolysis and overexpresses in cancers. Therefore, targeting GAPDH to inhibit its role in glycolysis is important for GAPDH functional studies and the treatment of cancers. However, only a few GAPDH inhibitors have been reported. In our current study, we identified a GAPDH inhibitor, DC-5163, using docking-based virtual screening and biochemical and biophysical analysis. DC-5163 is a small molecule compound that inhibits GAPDH enzyme activity and cancer cell proliferation (normal cells were tolerant to it). It can inhibit glycolysis pathway partially, which was manifested by decreased glucose uptake and lactic acid production. And it also leaded to cell death through apoptotic pathways. This study reflects the pivotal role of GAPDH in cancer cells and demonstrates that DC-5163 is a useful inhibitor and can be of value in studying the role of GAPDH and the development of new clinical cancer treatments.
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http://dx.doi.org/10.1016/j.bioorg.2020.103620DOI Listing
March 2020

The Effects of Ultraviolet A/B Treatments on Anthocyanin Accumulation and Gene Expression in Dark-Purple Tea Cultivar 'Ziyan' ().

Molecules 2020 Jan 15;25(2). Epub 2020 Jan 15.

College of Horticulture, Sichuan Agricultural University, Chengdu 611130, China.

'Ziyan' is a novel anthocyanin-rich tea cultivar with dark purple young shoots. However, how its anthocyanin accumulation is affected by environmental factors, such as ultraviolet (UV), remains unclear. In this study, we observed that UV light treatments stimulated anthocyanin accumulation in 'Ziyan' leaves, and we further analyzed the underlying mechanisms at gene expression and enzyme activity levels. In addition, the catechins and chlorophyll contents of young shoots under different light treatments were also changed. The results showed that the contents of total anthocyanins and three major anthocyanin molecules, i.e., delphinidin, cyanidin, and pelargonidin, were significantly higher in leaves under UV-A, UV-B, and UV-AB treatments than those under white light treatment alone. However, the total catechins and chlorophyll contents in these purple tea plant leaves displayed the opposite trends. The anthocyanin content was the highest under UV-A treatment, which was higher by about 66% than control. Compared with the white light treatment alone, the enzyme activities of chalcone synthase (CHS), flavonoid 3',5'-hydroxylase (F3'5'H), and anthocyanidin synthase (ANS) under UV treatments increased significantly, whereas the leucoanthocyanidin reductase (LAR) and anthocyanidin reductase (ANR) activities reduced. There was no significant difference in dihydroflavonol 4-reductase (DFR) activity under all treatments. Comparative transcriptome analyses unveiled that there were 565 differentially expressed genes (DEGs) of 29,648 genes in three pair-wise comparisons (white light versus UV-A, W vs. UV-A; white light versus UV-B, W vs. UV-A; white light versus UV-AB, W vs. UV-AB). The structural genes in anthocyanin pathway such as flavanone 3-hydroxylase ( and , and regulatory gene were upregulated under UV-A treatment; and and regulatory genes and were upregulated under UV-AB treatment. However, most structural genes involved in phenylpropanoid and flavonoid pathways were downregulated under UV-B treatment compared with control. The expression of and were repressed in all UV treatments. Our results indicated that UV-A and UV-B radiations can induce anthocyanin accumulation in tea plant 'Ziyan' by upregulating the structural and regulatory genes involved in anthocyanin biosynthesis. In addition, UV radiation repressed the expression levels of , and , resulting in reduced ANR activity and a metabolic flux shift toward anthocyanin biosynthesis.
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http://dx.doi.org/10.3390/molecules25020354DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7024295PMC
January 2020

Deep Learning Enhancing Kinome-Wide Polypharmacology Profiling: Model Construction and Experiment Validation.

J Med Chem 2020 08 15;63(16):8723-8737. Epub 2019 Aug 15.

Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.

The kinome-wide virtual profiling of small molecules with high-dimensional structure-activity data is a challenging task in drug discovery. Here, we present a virtual profiling model against a panel of 391 kinases based on large-scale bioactivity data and the multitask deep neural network algorithm. The obtained model yields excellent internal prediction capability with an auROC of 0.90 and consistently outperforms conventional single-task models on external tests, especially for kinases with insufficient activity data. Moreover, more rigorous experimental validations including 1410 kinase-compound pairs showed a high-quality average auROC of 0.75 and confirmed many novel predicted "off-target" activities. Given the verified generalizability, the model was further applied to various scenarios for depicting the kinome-wide selectivity and the association with certain diseases. Overall, the computational model enables us to create a comprehensive kinome interaction network for designing novel chemical modulators or drug repositioning and is of practical value for exploring previously less studied kinases.
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http://dx.doi.org/10.1021/acs.jmedchem.9b00855DOI Listing
August 2020

Discovery and Development of a Series of Pyrazolo[3,4-]pyridazinone Compounds as the Novel Covalent Fibroblast Growth Factor Receptor Inhibitors by the Rational Drug Design.

J Med Chem 2019 08 9;62(16):7473-7488. Epub 2019 Aug 9.

University of Chinese Academy of Sciences , No. 19A Yuquan Road , Beijing 100049 , China.

Alterations of fibroblast growth factor receptors (FGFRs) play key roles in numerous cancer progression and development, which makes FGFRs attractive targets in the cancer therapy. In the present study, based on a newly devised FGFR target-specific scoring function, a novel FGFR inhibitor hit was identified through virtual screening. Hit-to-lead optimization was then performed by integrating molecular docking and site-of-metabolism predictions with an array of in vitro evaluations and X-ray cocrystal structure determination, leading to a covalent FGFR inhibitor , which showed a highly selective and potent FGFR inhibition profile. Pharmacokinetic assessment, protein kinase profiling, and hERG inhibition evaluation were also conducted, and they confirmed the value of as a lead for further investigation. Overall, this study exemplifies the importance of the integrative use of computational methods and experimental techniques in drug discovery.
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http://dx.doi.org/10.1021/acs.jmedchem.9b00510DOI Listing
August 2019

KinomeX: a web application for predicting kinome-wide polypharmacology effect of small molecules.

Bioinformatics 2019 12;35(24):5354-5356

Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.

Motivation: The large-scale kinome-wide virtual profiling for small molecules is a daunting task by experimental and traditional in silico drug design approaches. Recent advances in deep learning algorithms have brought about new opportunities in promoting this process.

Results: KinomeX is an online platform to predict kinome-wide polypharmacology effect of small molecules based solely on their chemical structures. The prediction is made by a multi-task deep neural network model trained with over 140 000 bioactivity data points for 391 kinases. Extensive computational and experimental validations have been performed. Overall, KinomeX enables users to create a comprehensive kinome interaction network for designing novel chemical modulators, and is of practical value on exploring the previously less studied or untargeted kinases.

Availability And Implementation: KinomeX is available at: https://kinome.dddc.ac.cn.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btz519DOI Listing
December 2019

Deep Neural Network Classifier for Virtual Screening Inhibitors of (S)-Adenosyl-L-Methionine (SAM)-Dependent Methyltransferase Family.

Front Chem 2019 10;7:324. Epub 2019 May 10.

State Key Laboratory of Drug Research, Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.

The (S)-adenosyl-L-methionine (SAM)-dependent methyltransferases play essential roles in post-translational modifications (PTMs) and other miscellaneous biological processes, and are implicated in the pathogenesis of various genetic disorders and cancers. Increasing efforts have been committed toward discovering novel PTM inhibitors targeting the (S)-Adenosyl-L-methionine (SAM)-binding site and the substrate-binding site of methyltransferases, among which virtual screening (VS) and structure-based drug design (SBDD) are the most frequently used strategies. Here, we report the development of a target-specific scoring model for compound VS, which predict the likelihood of the compound being a potential inhibitor for the SAM-binding pocket of a given methyltransferase. Protein-ligand interaction characterized by Fingerprinting Triplets of Interaction Pseudoatoms was used as the input feature, and a binary classifier based on deep neural networks is trained to build the scoring model. This model enhances the efficiency of the existing strategies used for discovering novel chemical modulators of methyltransferase, which is crucial for understanding and exploring the complexity of epigenetic target space.
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http://dx.doi.org/10.3389/fchem.2019.00324DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6524412PMC
May 2019

Artificial intelligence in drug design.

Sci China Life Sci 2018 Oct 18;61(10):1191-1204. Epub 2018 Jul 18.

Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.

Thanks to the fast improvement of the computing power and the rapid development of the computational chemistry and biology, the computer-aided drug design techniques have been successfully applied in almost every stage of the drug discovery and development pipeline to speed up the process of research and reduce the cost and risk related to preclinical and clinical trials. Owing to the development of machine learning theory and the accumulation of pharmacological data, the artificial intelligence (AI) technology, as a powerful data mining tool, has cut a figure in various fields of the drug design, such as virtual screening, activity scoring, quantitative structure-activity relationship (QSAR) analysis, de novo drug design, and in silico evaluation of absorption, distribution, metabolism, excretion and toxicity (ADME/T) properties. Although it is still challenging to provide a physical explanation of the AI-based models, it indeed has been acting as a great power to help manipulating the drug discovery through the versatile frameworks. Recently, due to the strong generalization ability and powerful feature extraction capability, deep learning methods have been employed in predicting the molecular properties as well as generating the desired molecules, which will further promote the application of AI technologies in the field of drug design.
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http://dx.doi.org/10.1007/s11427-018-9342-2DOI Listing
October 2018

Survey of sulfur-oxidizing bacterial community in the Pearl River water using , , and as molecular biomarkers.

3 Biotech 2018 Jan 13;8(1):73. Epub 2018 Jan 13.

Guangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006 People's Republic of China.

In this study, we surveyed the abundance and diversity of three sulfur oxidation genes (, and ) using quantitative assays and Miseq high-throughput sequencing. The quantitative assays revealed that is more abundant than and and is the main contributor to sulfur oxidation. In the diversity analysis, the SOB community mainly comprised the classes , , , and . The genera , , , , , and were abundant in the communities for ; , , , , and were abundant in communities for ; , , and were abundant in communities for . This study presented a high diversity of SOB species and functional sulfur-oxidizing genes in Pearl River via high-throughput sequencing, suggesting that the aquatic ecosystem has great potential to scavenge the sulfur pollutants by itself.
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http://dx.doi.org/10.1007/s13205-017-1077-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5766448PMC
January 2018

Computational chemical biology and drug design: Facilitating protein structure, function, and modulation studies.

Med Res Rev 2018 05 11;38(3):914-950. Epub 2018 Jan 11.

State Key Laboratory of Drug Research, Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.

Over the past quarter of a century, there has been rapid development in structural biology, which now can provide solid evidence for understanding the functions of proteins. Concurrently, computational approaches with particular relevance to the chemical biology and drug design (CBDD) field have also incrementally and steadily improved. Today, these methods help elucidate detailed working mechanisms and accelerate the discovery of new chemical modulators of proteins. In recent years, integrating computational simulations and predictions with experimental validation has allowed for more effective explorations of the structure, function and modulation of important therapeutic targets. In this review, we summarize the main advancements in computational methodology development, which are then illustrated by several successful applications in CBDD. Finally, we conclude with a discussion of the current major challenges and future directions in the field.
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http://dx.doi.org/10.1002/med.21483DOI Listing
May 2018

Melatonin attenuates hippocampal neuron apoptosis and oxidative stress during chronic intermittent hypoxia via up-regulating B-cell lymphoma-2 and down-regulating B-cell lymphoma-2-associated X protein.

Saudi Med J 2013 Jul;34(7):701-8

Wuhan Brain Hospital, General Hospital of the Yangtze River Shipping, Wuhan, China.

Objective: To investigate the neuroprotective effect of melatonin against chronic intermittent hypoxia (CIH), the major pathophysiologic features of obstructive sleep apnea syndrome.

Methods: This study was conducted between January 2011 and September 2012 in Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China. Thirty 8-week Wistar rats were randomly divided into 3 groups (10 each): a control group, a vehicle-treated CIH group; and a melatonin-treated (10 mg/kg) CIH group. Rats were exposed to either intermittent hypoxia (IH) (oxygen concentration changing periodically from 21.78+/-0.65 to 6.57+/-0.57%), or air-air cycling at a rate of 30 cycles/hour, 8 hour/day for 4 weeks.

Results: The CIH exposure led to a significant decrease in superoxide dismutase (SOD) activity and anti-apoptotic protein B-cell lymphoma-2 (BCL-2) expression in the hippocampus of CIH group rats compared with that of the control group and melatonin-treated CIH group. In contrast, hippocampal neuronal apoptosis increased significantly in parallel to an augment in 3,4-methylenedioxyamphetamine (MDA) content and pro-apoptotic protein Bcl-2-associated X protein (BAX) expression in CIH group than the other 2 groups. Melatonin administration abrogated the increase in MDA activity, as well as BAX expression, and restored SOD activity and BCL-2 expression to nearly their normal levels.

Conclusion: These results indicate melatonin can inhibit hippocampal neuron apoptosis following CIH by scavenging reactive oxygen species, up-regulating anti-apoptotic protein BCL-2 and down-regulating pro-apoptotic protein BAX, and thus, alleviate CIH-induced oxidative stress injury and produce neuroprotection effects.
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July 2013
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