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A dsDNA-lighted fluorophore for monitoring protein-ligand interaction through binding-mediated DNA protection

Science China Chemistry 2018年第12期61卷 1630-1636页

作者： Zhihe Qing Lixuan Zhu Lina Hou Zhen Zou Sheng Yang Ronghua Yang Hunan Provincial Key Laboratory of Materials Protection for Electric Power and Transportation Hunan Provincial Engineering Research Center for Food Processing of Aquatic Biotic Resources School of Chemistry and Biological Engineering Changsha University of Science and Technology

Because of their important roles in cellular functions, life activities, drug screening, and disease treatment, the development of efficient methods for monitoring protein-ligand interaction is essential. In this study, inspired by our previous studies on DNA conformation-selective fluorescent indicators, we developed a new sensing platform for monitoring protein-ligand interaction and detecting protein activity based on binding-mediated DNA protection and the dsDNA-lighted fluorophore, ethyl-4-[3,6-bis(1-methyl-4-vinylpyridium iodine)-9 H-carbazol-9-yl)] butanoate(EBCB). The ligand was purposefully linked to the 3?-terminal of a hairpin DNA probe to selectively bind with the target protein and protect the DNA from cleavage by exonuclease III. By virtue of EBCB's outstanding capacity to discriminate DNA conformation, the protein-ligand interaction could be effectively monitored through a fluorescence change in EBCB. A high fluorescence signal was detected when the hairpin DNA was protected in the presence of the target protein, whereas a much lower signal was observed in the presence of nontarget *** results demonstrated that the proposed strategy had high potential, such as high selectivity and relatively high sensitivity, for monitoring protein-ligand interaction and detecting protein activity. We believe these results will pave the way for applying dsDNA-lighted fluorophore EBCB as an effective signal transducer for DNA conformation transformation-mediated biochemical sensing.

关键词： dsDNA-lighted fluorophore protein-ligand interaction DNA protection fluorescence detection

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Interaction Entropy for protein-ligand hot spot predicition

Interaction Entropy for protein-ligand hot spot predicition

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第十三届全国量子化学会议

作者： Xiao Liu Yu N.Yan John Z.H.Zhang State Key Laboratory for Precision Spectroscopy School of Chemistry and Molecular EngineeringEast China Normal University Department of Chemistry New York University

The theoretical calculation of protein-ligand binding free energy is a grand challenge in computational *** prediction of critical residues along with their specific and quantitative contributions to protein-ligand binding free energy is extremely helpful to reveal binding mechanisms and identify drug-like molecules that alter protein-ligand *** this paper,we propose an interaction entropy approach combined with the MM/GBSA method for solvation to compute residue-specific protein-ligand binding free *** the current approach,the entropic loss in binding free energy of individual residues is explicitly computed from MD simulation by using the interaction entropy *** this approach the entropic contribution to binding free energy is determined from fluctuation of the interaction in MD *** for an extensive set of ALK protein-ligand interaction systems showed that by including the entropic contribution,we can clearly find the hot spot residues,it is helpful for new drug design.

关键词： interaction entropy hot spot protein-ligand

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Screen efficiency comparisons of decision tree and neural network algorithms in machine learning assisted drug design

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Science China Chemistry 2019年第4期62卷 506-514页

作者： Qiumei Pu Yinghao Li Hong Zhang Haodong Yao Bo Zhang Bingji Hou Lin Li Yuliang Zhao Lina Zhao CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Institute of High Energy Physics Chinese Academy of Sciences School of Information Engineering Minzu University of China University of Chinese Academy of Sciences School of Computer Beijing Institute of Technology

In view of huge search space in drug design, machine learning has become a powerful method to predict the affinity between small molecular drug and targeting protein with the development of artificial intelligence technology. However, various machine learning algorithms including massive different parameters make the prediction framework choice to be quite difficult. In this work, we took a recent drug design competition(from XtalPi company on the DataCastle platform) as the typical case to find the optimized parameters for different machines learning algorithms and the most effective algorithm. After the parameter optimizations, we compared the typical machine learning methods as decision tree(XGBoost, LightGBM) and artificial neural network(MLP, CNN) with root-mean-square error(RMSE) and coefficient of determination(R^2) evaluation. As a result, decision tree is more effective than the neural network as LightGBM>XGBoost>CNN>MLP in the affinity prediction of the specific drug design problem with ～160000 samples. For a much larger screening task in a more complicated drug design study, the sophisticated neural network model may go beyond the decision tree algorithm after generalization enhancing and overfitting reducing. The advanced machine learning methods could extract more information of protein-ligand bindings than traditional ones and improve the screen efficiency of drug design up to 200–1000 times.

关键词： drug design affinity prediction protein-ligand binding machine learning

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Binding of naturally occurring hydroxycinnamic acids to bovine serum albumin

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Natural Science 2010年第6期2卷 563-570页

作者： Lucie Trnkova Iva Bousova Vladimir Kubicek Jaroslav Drsata Charles University in Prague Faculty of Pharmacy Hradec Králové Czech Republic Charles University in Prague Faculty of Pharmacy Hradec Králové Czech Republic University of Hradec Králové Faculty of Education Hradec Králové Czech Republic

Hydroxycinnamic acids (HCAs) possess numer- ous biological effects including antioxidant, antiallergic, antimicrobial, and immunomodulatory activities and due to these properties are widely used in folk medicine. Nevertheless, they can interact with protein molecules and cause some structural and functional changes. The possib- ility of HCAs binding to bovine serum albumin (BSA) under physiological conditions was inve- stigated by the UV-VIS absorption spectroscopy and fluorescence quenching method. Apart from rosmarinic acid, all tested HCAs quenched tryptophan fluorescence of BSA in the studied range of concentrations (0-20 μM) mainly by static quenching mechanism (formation of non- fluorescent HCA-BSA complexes). The binding constants, number of binding sites and free energy changes were determined. The binding affinities of HCAs were ranked in the order: chlorogenic acid > sinapic acid ≥ caffeic acid > ferulic acid > o-coumaric acid > p-coumaric acid ≥ m-coumaric acid, which was confirmed by spectral overlaps of BSA emission spectrum with absorption spectrum of HCA. All free energy changes possessed negative sign indicating the spontaneity of HCA-BSA interaction.

关键词： Bovine Serum Albumin Hydroxycinnamic Acid Fluorescence Quenching protein-ligand Binding

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The PDBbind Database:A Comprehensive Collection of the Binding Data for the Biomolecular Complexes in the protein Data Bank

The PDBbind Database:A Comprehensive Collection of the Bindi...

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第一届全国生物物理化学会议暨生物物理化学发展战略研讨会

作者： Zhihai Liu,Jie Li,Jiajie Li,Xun Li,Yan Li,Renxiao Wang~* State Key Laboratory of Bioorganic Chemistry,Shanghai Institute of Organic Chemistry,Chinese Academy of Sciences,Shanghai,P.R.China

＜正＞The PDBbind database is created to provide a comprehensive collection of the binding data for the biomolecular complexes deposited in the protein Data Bank（PDB）.It thus provides a link between energetic and structural information of biomolecular complexes,which is of great value for various studies on molecular recognition occurred in biological *** entire

关键词： PDBbind database protein-ligand Binding Affinity

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