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.

Design and Synthesis of Marine Phidianidine Derivatives as Potential Immunosuppressive Agents.

Abstract: A series of novel marine phidianidine derivatives were designed, synthesized, and evaluated for their immunosuppressive activities during our search of potential immunosuppressive agents with high efficacy and low toxicity from marine sources. These compounds were tested for their inhibitory activity on Con A-induced T cell and lipopolysaccharide-induced B cell proliferation. Compounds 14a and 18c, displaying the most promising inhibitory effects and low toxicities, were further found to possess immune-regulatory activities upon cross-linking of T cell receptor (TCR) and B cell receptor (BCR) on purified T and B cells, respectively.

Trimer procyanidin oligomers contribute to the protective effects of cinnamon extracts on pancreatic β-cells in vitro.

Abstract: Cinnamon extracts rich in procyanidin oligomers have shown to improve pancreatic β-cell function in diabetic db/db mice. The aim of this study was to identify the active compounds in extracts from two species of cinnamon responsible for the pancreatic β-cell protection in vitro. Cinnamon extracts were prepared from Cinnamomum tamala (CT-E) and Cinnamomum cassia (CC-E). Six compounds procyanidin B2 (cpd1), (−)-epicatechin (cpd2), cinnamtannin B1 (cpd3), procyanidin C1 (cpd4), parameritannin A1 (cpd5) and cinnamtannin D1 (cpd6) were isolated from the extracts. INS-1 pancreatic β-cells were exposed to palmitic acid (PA) or H2O2 to induce lipotoxicity and oxidative stress. Cell viability and apoptosis as well as ROS levels were assessed. Glucose-stimulated insulin secretion was examined in PA-treated β-cells and murine islets. CT-E, CC-E as well as the compounds, except cpd5, did not cause cytotoxicity in the β-cells up to the maximum dosage using in this experiment. CT-E and CC-E (12.5–50 μg/mL) dose-dependently increased cell viability in both PA- and H2O2-treated β-cells, and decreased ROS accumulation in H2O2-treated β-cells. CT-E caused more prominent β-cell protection than CC-E. Furthermore, CT-E (25 and 50 μg/mL) dose-dependently increased glucose-stimulated insulin secretion in PA-treated β-cells and murine islets, but CC-E had little effect. Among the 6 compounds, trimer procyanidins cpd3, cpd4 and cpd6 (12.5–50 μmol/L) dose-dependently increased the cell viability and decreased ROS accumulation in H2O2-treated β-cells. The trimer procyanidins also increased glucose-stimulated insulin secretion in PA-treated β-cells. Trimer procyanidins in the cinnamon extracts contribute to the pancreatic β-cell protection, thus to the anti-diabetic activity.

Identification of probable genomic packaging signal sequence from SARS-CoV genome by bioinformatics analysis.

Abstract: AIM: To predict the probable genomic packaging signal of SARS-CoV by bioinformatics analysis. The derived packaging signal may be used to design antisense RNA and RNA interfere (RNAi) drugs treating SARS. METHODS: Based on the studies about the genomic packaging signals of MHV and BCoV, especially the information about primary and secondary structures, the putative genomic packaging signal of SARS-CoV were analyzed by using bioinformatic tools. Multi-alignment for the genomic sequences was performed among SARS-CoV, MHV, BCoV, PEDV and HCoV 229E. Secondary structures of RNA sequences were also predicted for the identification of the possible genomic packaging signals. Meanwhile, the N and M proteins of all five viruses were analyzed to study the evolutionary relationship with genomic packaging signals. RESULTS: The putative genomic packaging signal of SARS-CoV locates at the 3' end of ORF1b near that of MHV and BCoV, where is the most variable region of this gene. The RNA secondary structure of SARS-CoV genomic packaging signal is very similar to that of MHV and BCoV. The same result was also obtained in studying the genomic packaging signals of PEDV and HCoV 229E. Further more, the genomic sequence multi-alignment indicated that the locations of packaging signals of SARS-CoV, PEDV, and HCoV overlaped each other. It seems that the mutation rate of packaging signal sequences is much higher than the N protein, while only subtle variations for the M protein. CONCLUSIONS: The probable genomic packaging signal of SARS-CoV is analogous to that of MHV and BCoV, with the corresponding secondary RNA structure locating at the similar region of ORF1b. The positions where genomic packaging signals exist have suffered rounds of mutations, which may influence the primary structures of the N and M proteins consequently.

Thermodynamics calculation of protein–ligand interactions by QM/MM polarizable charge parameters

Abstract: The calculation of protein–ligand binding free energy (ΔG) is of great importance for virtual screening and drug design. Molecular dynamics (MD) simulation has been an attractive tool to investigat...

Pattern Recognition and Machine Learning

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.

“Bioinformatics” 특집을 내면서

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.

Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors

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.

New Substructure Filters for Removal of Pan Assay Interference Compounds (PAINS) from Screening Libraries and for Their Exclusion in Bioassays

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.