1.Inhibition effect of China cobra venom active factor on endothelial cells and its biochemical mechanism
Liu ZHU ; Qingsheng YU ; Mu YUAN ; Xinyan LIU ; Guiping WANG ; Honge YU ; Xiaohua LOU ; Maikun TENG
Chinese Journal of Biochemical Pharmaceutics 2009;30(6):361-364
Purpose To study the effect of China cobra venom active factor(CCVAF) from China cobra venom on endothelial cells and its mechanism.Methods MTT experiment was adopted to evaluate the effect of CCVAF on bovine arteria pulmonalis vascular endothelial cells(BAVEC).The Eosin-Coomassie brillient blue and rhodamine-phalloidin method was used for actin cytoskeleton.Flow cytometry for [Ca~(2+)]_i and spectrophotometry were used for lactate dehydrogenase(LDH) and nitrogen oxide(NO) levels in cell culture supernatant.Results CCVAF(0.625-20 μg/mL) inhibited the proliferation of BAVEC in dose-dependent manner,and IC50 of CCVAF on BAVEC was 2.45 μg/mL. After CCVAF and BAVEC coincubation, it was showed that regression of intercellular conjunctions and disorder of F-actin distribution occurred. The content of [Ca~(2+)]_i, [LDH] and [NO] increased respectively.Conclusion CCVAF can inhibit BAVEC proliferation and it maybe associated with the change of cytoskeleton and increasing of [Ca~(2+)]_i,[LDH] aod [NO].
2.Defining A Global Map of Functional Group-based 3D Ligand-binding Motifs
Yang LIU ; He WEI ; Yun YUEHUI ; Gao YONGXIANG ; Zhu ZHONGLIANG ; Teng MAIKUN ; Liang ZHI ; Niu LIWEN
Genomics, Proteomics & Bioinformatics 2022;20(4):765-779
Uncovering conserved 3D protein-ligand binding patterns on the basis of functional groups(FGs)shared by a variety of small molecules can greatly expand our knowledge of protein-ligand interactions.Despite that conserved binding patterns for a few commonly used FGs have been reported in the literature,large-scale identification and evaluation of FG-based 3D binding motifs are still lacking.Here,we propose a computational method,Automatic FG-based Three-dimensional Motif Extractor(AFTME),for automatic mapping of 3D motifs to different FGs of a specific ligand.Applying our method to 233 naturally-occurring ligands,we define 481 FG-binding motifs that are highly conserved across different ligand-binding pockets.Systematic analysis further reveals four main classes of binding motifs corresponding to distinct sets of FGs.Combinations of FG-binding motifs facilitate the binding of proteins to a wide spectrum of ligands with various binding affinities.Finally,we show that our FG-motif map can be used to nominate FGs that potentially bind to specific drug targets,thus providing useful insights and guidance for rational design of small-molecule drugs.