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Kaixian Chen

Researcher at Chinese Academy of Sciences

Publications -  403
Citations -  11476

Kaixian Chen is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Virtual screening & Chemistry. 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.

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

TL;DR: New datasets specific for CPI prediction are constructed, a novel transformer neural network named TransformerCPI is proposed, and a more rigorous label reversal experiment is introduced to test whether a model learns true interaction features.
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The nucleocapsid protein of SARS coronavirus has a high binding affinity to the human cellular heterogeneous nuclear ribonucleoprotein A1

TL;DR: The determined results showed that SARS_N protein has only one binding domain for interacting with human hnRNP A1, which is different from the mouse hepatitis virus (MHV) binding case where the nucleocapsid protein of MHV was found to have two binding domains involved in the MHV_N/hnR NP A1 interaction.
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Virtual Screening on Natural Products for Discovering Active Compounds and Target Information

TL;DR: This review focuses on the strategy of virtual screening based on molecular docking and illustrates the efficiency of virtual Screening in discovering active compounds from natural products using natural products as the probes.
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A Simple and Convenient Copper-Catalyzed Tandem Synthesis of Quinoline-2-carboxylates at Room Temperature

TL;DR: A simple and convenient copper-catalyzed method for the synthesis of quinoline-2-carboxylate derivatives through sequential intermolecular addition of alkynes onto imines and subsequent intramolecular ring closure by arylation is developed.
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Fluorogenic Probing of Specific Recognitions between Sugar Ligands and Glycoprotein Receptors on Cancer Cells by an Economic Graphene Nanocomposite

TL;DR: Economical nanocomposites based on π-stacking of N-acetyl glycosyl rhodamine B to graphene oxide (GO) are simply prepared and proven to be admirable for the fluorogenic recognition of specific intercellular sugar-based ligand-glycoprotein receptor interactions of interest.