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Kaixian Chen

Bio: Kaixian Chen is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Virtual screening & Docking (molecular). The author has an hindex of 47, co-authored 380 publications receiving 9209 citations. Previous affiliations of Kaixian Chen include Shanghai University & East China University of Science and Technology.


Papers
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Journal Article
TL;DR: The ligand-receptor interaction model should be helpful for rational design of novel analgesic and investigate the action mechanism of ohmefentanyl on the receptor.
Abstract: "AIM: To build up the structure model of mu opioid receptor, then combined with the receptor model, to investigate the action mechanism of ohmefentanyl on the receptor. METHODS: Using the three-dimensional structure of bacteriorhodopsin as a template, we constructed mu opioid receptor model on computer. Ohmefentanyl was then docked into the supposed receptor binding sites. RESULTS: A good ligand-receptor interaction model was achieved. The possible binding sites were found to be Asp147 and His319. The protonated N atom of ohmefentanyl form potent electrostatic and hydrogen-bonding interactions with residue Asp147 of the receptor, the O atom of the carbonyl group form weak electrostatic and hydrogen-bonding interactions with residue His319, and the two phenyl groups form pi-pi interactions with some aryl residues of the receptor around ligand. CONCLUSION: The ligand-receptor interaction model should be helpful for rational design of novel analgesic. "

16 citations

Journal ArticleDOI
TL;DR: B-type procyanidin, component of cinnamon extract, stimulate pre-adipocytes differentiation and act as a potential insulin action enhancer through the AKT-eNOS pathway in mature adipocytes are identified.
Abstract: Natural products are one of the main sources for discovering new lead compounds. We previously reported that cinnamon extract has a promising effect in regulating lipid tissue volume and insulin sensitivity in vivo. However, its effective component and the underlying mechanism are not known. In the present study, we analyzed the effect of different components of cinnamon on regulating insulin sensitivity in 3T3-L1 adipocytes. Functional assay revealed that, of the six major components of cinnamon extracts, the B-type procyanidin, procyanidin C1, improves the differentiation of 3T3-L1 cells (TG content: 1.10 ± 0.09 mM at a dosage of 25 μM vs 0.67 ± 0.02 mM in vehicle group, p < 0.001) and promotes insulin-induced glucose uptake (8.58 ± 1.43 at a dosage of 25 μM vs 3.05 ± 1.24 in vehicle group, p < 0.001). Mechanism studies further suggested that procyanidin C1 activates the AKT-eNOS pathway, thus up-regulating glucose uptake and enhancing insulin sensitivity in mature adipocytes. Taken together, our study identified B-type procyanidin C1, a component of cinnamon extract, that stimulates preadipocyte differentiation and acts as a potential insulin action enhancer through the AKT-eNOS pathway in mature adipocytes.

16 citations

Journal ArticleDOI
TL;DR: A fluorescence polarization (FP)-based HTS system for the discovery of EZH2-EED interaction inhibitors was developed and the minimal sequence requirement was determined by using this system.
Abstract: Aberrant activity of enhancer of zeste homolog 2 (EZH2) is associated with a wide range of human cancers. The interaction of EZH2 with embryonic ectoderm development (EED) is required for EZH2's catalytic activity. Inhibition of the EZH2-EED complex thus represents a novel strategy for interfering with the oncogenic potentials of EZH2 by targeting both its catalytic and non-catalytic functions. To date, there have been no reported high-throughput screening (HTS) assays for inhibitors acting at the EZH2-EED interface. In this study, we developed a fluorescence polarization (FP)-based HTS system for the discovery of EZH2-EED interaction inhibitors. The tracer peptide sequences, positions of fluorescein labeling, and a variety of physicochemical conditions were optimized. The high Z' factors (>0.9) at a variety of DMSO concentrations suggested that this system is robust and suitable for HTS. The minimal sequence requirement for the EZH2-EED interaction was determined by using this system. A pilot screening of an in-house compound library containing 1600 FDA-approved drugs identified four compounds (apomorphine hydrochloride, oxyphenbutazone, nifedipine and ergonovine maleate) as potential EZH2-EED interaction inhibitors.

16 citations

Journal ArticleDOI
TL;DR: The DrugSpaceX database, based on expert-defined transformations of approved drug molecules, can locate the position of transformation, which will enable medicinal chemists to easily integrate strategy planning and protection design.
Abstract: 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.

16 citations

Journal ArticleDOI
TL;DR: A preliminary optical study of two hydroxyl-free glucoside-based TBGs indicates that these compounds are strongly fluorescent in pure water, implying their potential for ion detections in aqueous media.

16 citations


Cited by
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Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations

01 Aug 2000
TL;DR: Assessment of medical technology in the context of commercialization with Bioentrepreneur course, which addresses many issues unique to biomedical products.
Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

4,833 citations

Journal ArticleDOI
TL;DR: This review covers the literature published in 2014 for marine natural products, with 1116 citations referring to compounds isolated from marine microorganisms and phytoplankton, green, brown and red algae, sponges, cnidarians, bryozoans, molluscs, tunicates, echinoderms, mangroves and other intertidal plants and microorganisms.

4,649 citations

Journal ArticleDOI
11 Jun 2020-Nature
TL;DR: A programme of structure-assisted drug design and high-throughput screening identifies six compounds that inhibit the main protease of SARS-CoV-2, demonstrating the ability of this strategy to isolate drug leads with clinical potential.
Abstract: A new coronavirus, known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is the aetiological agent responsible for the 2019–2020 viral pneumonia outbreak of coronavirus disease 2019 (COVID-19)1–4. Currently, there are no targeted therapeutic agents for the treatment of this disease, and effective treatment options remain very limited. Here we describe the results of a programme that aimed to rapidly discover lead compounds for clinical use, by combining structure-assisted drug design, virtual drug screening and high-throughput screening. This programme focused on identifying drug leads that target main protease (Mpro) of SARS-CoV-2: Mpro is a key enzyme of coronaviruses and has a pivotal role in mediating viral replication and transcription, making it an attractive drug target for SARS-CoV-25,6. We identified a mechanism-based inhibitor (N3) by computer-aided drug design, and then determined the crystal structure of Mpro of SARS-CoV-2 in complex with this compound. Through a combination of structure-based virtual and high-throughput screening, we assayed more than 10,000 compounds—including approved drugs, drug candidates in clinical trials and other pharmacologically active compounds—as inhibitors of Mpro. Six of these compounds inhibited Mpro, showing half-maximal inhibitory concentration values that ranged from 0.67 to 21.4 μM. One of these compounds (ebselen) also exhibited promising antiviral activity in cell-based assays. Our results demonstrate the efficacy of our screening strategy, which can lead to the rapid discovery of drug leads with clinical potential in response to new infectious diseases for which no specific drugs or vaccines are available. A programme of structure-assisted drug design and high-throughput screening identifies six compounds that inhibit the main protease of SARS-CoV-2, demonstrating the ability of this strategy to isolate drug leads with clinical potential.

2,845 citations

Journal ArticleDOI
TL;DR: A number of substructural features which can help to identify compounds that appear as frequent hitters (promiscuous compounds) in many biochemical high throughput screens are described.
Abstract: This report describes a number of substructural features which can help to identify compounds that appear as frequent hitters (promiscuous compounds) in many biochemical high throughput screens. The compounds identified by such substructural features are not recognized by filters commonly used to identify reactive compounds. Even though these substructural features were identified using only one assay detection technology, such compounds have been reported to be active from many different assays. In fact, these compounds are increasingly prevalent in the literature as potential starting points for further exploration, whereas they may not be.

2,791 citations