scispace - formally typeset
K

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.

Papers
More filters
Journal Article

Building three-dimensional structures of HIV-1 coreceptor CCR5 and its interaction with antagonist TAK779 by comparative molecular modeling.

TL;DR: The model constructed and the interaction mode reported in the present study are useful in further understanding the molecular mechanism of receptor-virus recognition and designing new inhibitors of HIV-1 infection.
Journal ArticleDOI

‘Pungent’ Copper Surface Resists Acid Corrosion in Strong HCl Solutions

TL;DR: Piperine, the major pungent component of peppers, has the best corrosion inhibitive efficiency for copper in HCl among four analogous amide alkaloids isolated from a traditional Chinese medicine as mentioned in this paper.
Journal ArticleDOI

Palladium-catalyzed [4 + 3] dearomatizing cycloaddition reaction of N-iminoquinolinium ylides

TL;DR: A palladium-catalyzed [4 + 3] dearomatizing cycloaddition of N-iminoquinolinium ylides has been developed for the construction of saturated seven-membered ring in good yields and features mild reaction conditions and good functional group tolerance.
Journal ArticleDOI

Function-Oriented Synthesis of Marine Phidianidine Derivatives as Potential PTP1B Inhibitors with Specific Selectivity.

TL;DR: A series of phidianidine derivatives were designed and rapidly synthesized with a function-oriented synthesis (FOS) strategy, and several compounds displayed significant inhibitory potency and specific selectivity over PTP1B.
Journal ArticleDOI

Solution-Phase DNA-Compatible Pictet-Spengler Reaction Aided by Machine Learning Building Block Filtering.

TL;DR: A machine learning algorithm has been developed that predicts the conversion rate for the DNA-compatible reaction of a building block with a model DNA-conjugate, allowing for a challenging reaction, with an otherwise very low building block pass rate in the test reaction, to still be used in DEL synthesis.