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.

A density functional theory (DFT) calculation of the geometry and vibrational spectrum of natural product, ginkgolide B

Abstract: A quantum chemistry calculation at DFT-B3LYP/6-31G ∗ level on the geometry and IR spectrum of ginkgolide B was performed. The fully optimised geometry of ginkgolide B was found to be consistent with X-ray crystal structure. In addition, some important thermodynamic parameters were provided. The predicted vibrational bands of ginkgolide B scaled by a scaling factor of 0.945 were perfectly aligned to the experimental IR spectrum. Normal mode analysis on all 156 predicted bands showed that the stretching of O–H bonds of alcohol hydroxyl groups correspond to modes 156, 155 and 154 (from 3501 to 3443 cm −1 ). The stretching of C O bonds of carbonyl groups result in modes 132, 131 and 130 (from 1788 to 1764 cm −1 ). These assigned results were in accordance with what had been assigned in experiment based on IR spectroscopy. However, our normal mode analyses on the bands below 1192 cm −1 (mode 97) showed that none of these bands could be simply assigned to the stretching of a C–O bond. These bands are the results of coupling between the breathing of condensed ring structure and some other vibrations, such as the stretching of C–O bond or the rocking of C–H bond. Some of the bands that had been assigned to the stretching of C–O bond in experiment could be partly contributed by the vibration of C–O bonds. Furthermore, this study result showed that the stretching of C–H bond, and the rocking of t -Bu, methyl and methenyl groups can be located at the bands around 2900 and 1460 cm −1 , respectively.

Discovering the distinct inhibitory effects between C4-epimeric glycosyl amino acids: new insight into the development of protein tyrosine phosphatase inhibitors.

Abstract: There has been increasing interest in the development of drug candidates based on sugar templates that possess rich structural and, especially, configurational diversities We disclose herein that the epimeric identity between methyl 3,4-bis-phenylalanyl/tyrosinyl triazolyl-alpha-D-galactopyranoside and glucopyranoside may lead to their distinct inhibitory effects on specific protein tyrosine phosphatases (PTPs) Subsequently performed molecular docking study elucidated the plausible binding behaviors of the more potent galactosyl inhibitors with their primary PTP target, ie Cell Division Cycle 25B (CDC25B) phosphatase

A common intermediate for prebiotic synthesis of proteins and nucleosides: a density functional theory (DFT) study on the formation of penta-coordinate phosphorus carboxylic–phosphoric mixed anhydride from N-phosphoryl amino acids

Abstract: N -phosphoryl amino acids (PAA) are a unique chemical species with many chemical reactivities and properties, including the ability to self-assemble into oligopeptides. Because of their chemical characteristics, they have been proposed as the common origin for both nucleic acids and proteins. In this paper, we discussed six intramolecular mixed carboxylic–phosphoric anhydrides (IMCPAs) as possible intermediates for the prebiotic synthesis of biopolymers from PAA. We also investigated the role of water molecules in the formation of IMCPA using density functional theory B3LYP quantum mechanical calculations at the 6-31G** and 6-311+G** levels. Our results showed that the energy barrier of IMCPA formation was reduced from 19.5 kcal mol −1 to 9.9 kcal mol −1 when water participation and solvent effects were considered. Thus, the direct participation of one water molecule and the bulk solvent effects both play important roles in the formation of IMCPA.

Review of the Ethnopharmacology, Phytochemistry, and Pharmacology of the Genus Veronica.

Abstract: Veronica is the largest genus in the flowering plant family Plantaginaceae and comprises approximately 500 species. The genus was formerly placed in the Scrophulariaceae family, some species of whi...

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.