Background:Glaucoma is an optical neuropathy affecting over 67 million people in the world.Efficiency of current active molecules,as travoprost(hydrophobic)is limited when administered by ophthalmic drops.Indeed,more ...Background:Glaucoma is an optical neuropathy affecting over 67 million people in the world.Efficiency of current active molecules,as travoprost(hydrophobic)is limited when administered by ophthalmic drops.Indeed,more than 99.9%is discarded due to multiple factors including lacrimal drainage.Low retention time of drugs at the cornea leads to their poor penetration.The aim of the project is to develop a drug delivery system allowing the drug penetration through biological barriers.Our hypothesis is that a drug delivery system based on gold nanoparticles should enhance the efficiency of the drugs.The main objective is to study the encapsulation ability of gold nanoparticles towards travoprost.The specific objectives are(I)the synthesis and characterizations of gold nanoparticles;(II)the establishment of the encapsulation protocol;(III)the method development of the separation of free and encapsulated drugs and;(IV)the quantification of the encapsulated drugs.Methods:Gold nanoparticles were synthesized by a new method developed in our laboratory.An encapsulation protocol was settled using aqueous conditions at 37℃.The separation of free and encapsulated drugs was performed with magnetic beads.The quantification of the encapsulated drugs was then performed by high performance liquid chromatography and confirmed by UV-visible spectroscopy.Results:Gold nanoparticles of 28±1 nm were synthesized and purified according to our new experimental conditions.The encapsulation protocol lasts 5 days in the optimised conditions.The separation method involving magnetic beads was optimized to get rid of non-specific interactions.The travoprost was incubated with the nanoparticles until the reach of equilibrium in solution.Conclusions:We showed that active molecules used for glaucoma therapy,as travoprost,can be encapsulated in gold nanoparticles.Further analysis will allow identifying the encapsulation properties of various gold nanoparticles,differing by their size,shape and chemical surface.These data suggest the possible improvements.展开更多
The purpose of this study was to develop a quantitative structure–property relationship(QSPR) model based on the enhanced replacement method(ERM) and support vector machine(SVM) to predict the blood-to-brain barrier ...The purpose of this study was to develop a quantitative structure–property relationship(QSPR) model based on the enhanced replacement method(ERM) and support vector machine(SVM) to predict the blood-to-brain barrier partitioning behavior(log BB) of various drugs and organic compounds. Different molecular descriptors were calculated using a dragon package to represent the molecular structures of the compounds studied. The enhanced replacement method(ERM) was used to select the variables and construct the SVM model. The correlation coefficient, R^2, between experimental results and predicted log BB was 0.878 and 0.986, respectively. The results obtained demonstrated that, for all compounds, the log BB values estimated by SVM agreed with the experimental data, demonstrating that SVM is an effective method for model development, and can be used as a powerful chemometric tool in QSPR studies.展开更多
A novel three-dimensional holographic vector of atomic interaction field（3D-HoVAIF） was used to describe the chemical structures of 23 benzoxazinone derivatives as antithrombotic drugs.Here a quantitative structure ...A novel three-dimensional holographic vector of atomic interaction field（3D-HoVAIF） was used to describe the chemical structures of 23 benzoxazinone derivatives as antithrombotic drugs.Here a quantitative structure activity relationship（QSAR） model was built by partial least-squares（PLS） regression.The estimation stability and prediction ability of the model were strictly analyzed by both internal and external validations.The correlation coefficients of established PLS model,leave-one-out（LOO） cross-validation,and predicted values versus experimental ones of external samples were R2=0.899,RCV2=0.854 and Qext2=0.868,respectively.These values indicated that the built PLS model had both favorable estimation stability and good prediction capabilities.Furthermore,the satisfactory results showed that 3D-HoVAIF could preferably express the information related to the biological activity of benzoxazinone derivatives.展开更多
Identification of the drug-binding residues on the surface of proteins is a vital step in drug discovery and it is important for understanding protein function. Most previous researches are based on the structural inf...Identification of the drug-binding residues on the surface of proteins is a vital step in drug discovery and it is important for understanding protein function. Most previous researches are based on the structural information of proteins, but the structures of most proteins are not available. So in this article, a sequence-based method was proposed by combining the support vector machine (SVM)-based ensemble learning and the improved position specific scoring matrix (PSSM). In order to take the local environment information of a drug-binding site into account, an improved PSSM profile scaled by the sliding window and smoothing window was used to improve the prediction result. In addition, a new SVM-based ensemble learning method was developed to deal with the imbalanced data classification problem that commonly exists in the binding site predictions. When performed on the dataset of 985 drug-binding residues, the method achieved a very promising prediction result with the area under the curve (AUC) of 0.9264. Furthermore, an independent dataset of 349 drug- binding residues was used to evaluate the pre- diction model and the prediction accuracy is 84.68%. These results suggest that our method is effective for predicting the drug-binding sites in proteins. The code and all datasets used in this article are freely available at http://cic.scu.edu.cn/bioinformatics/Ensem_DBS.zip.展开更多
纳米技术在生物领域的渗透形成了纳米生物技术,而纳米药物载体的研究是纳米生物技术的重点和热点。纳米级药物输送系统(Nanopartiele drug delivery system,NDDS)在实现靶向性给药、缓释药物、提高难溶性药物与多肽药物的生物利用度、...纳米技术在生物领域的渗透形成了纳米生物技术,而纳米药物载体的研究是纳米生物技术的重点和热点。纳米级药物输送系统(Nanopartiele drug delivery system,NDDS)在实现靶向性给药、缓释药物、提高难溶性药物与多肽药物的生物利用度、降低药物的毒副作用等方面表现出良好的应用前景,因而也成为近年来药剂学领域的研究热点之一。本文综述了近年来出现的纳米药物载体的种类,并详细阐述了各类载体系统的特点和优点,为其进一步应用提供理论依据。展开更多
文摘Background:Glaucoma is an optical neuropathy affecting over 67 million people in the world.Efficiency of current active molecules,as travoprost(hydrophobic)is limited when administered by ophthalmic drops.Indeed,more than 99.9%is discarded due to multiple factors including lacrimal drainage.Low retention time of drugs at the cornea leads to their poor penetration.The aim of the project is to develop a drug delivery system allowing the drug penetration through biological barriers.Our hypothesis is that a drug delivery system based on gold nanoparticles should enhance the efficiency of the drugs.The main objective is to study the encapsulation ability of gold nanoparticles towards travoprost.The specific objectives are(I)the synthesis and characterizations of gold nanoparticles;(II)the establishment of the encapsulation protocol;(III)the method development of the separation of free and encapsulated drugs and;(IV)the quantification of the encapsulated drugs.Methods:Gold nanoparticles were synthesized by a new method developed in our laboratory.An encapsulation protocol was settled using aqueous conditions at 37℃.The separation of free and encapsulated drugs was performed with magnetic beads.The quantification of the encapsulated drugs was then performed by high performance liquid chromatography and confirmed by UV-visible spectroscopy.Results:Gold nanoparticles of 28±1 nm were synthesized and purified according to our new experimental conditions.The encapsulation protocol lasts 5 days in the optimised conditions.The separation method involving magnetic beads was optimized to get rid of non-specific interactions.The travoprost was incubated with the nanoparticles until the reach of equilibrium in solution.Conclusions:We showed that active molecules used for glaucoma therapy,as travoprost,can be encapsulated in gold nanoparticles.Further analysis will allow identifying the encapsulation properties of various gold nanoparticles,differing by their size,shape and chemical surface.These data suggest the possible improvements.
文摘The purpose of this study was to develop a quantitative structure–property relationship(QSPR) model based on the enhanced replacement method(ERM) and support vector machine(SVM) to predict the blood-to-brain barrier partitioning behavior(log BB) of various drugs and organic compounds. Different molecular descriptors were calculated using a dragon package to represent the molecular structures of the compounds studied. The enhanced replacement method(ERM) was used to select the variables and construct the SVM model. The correlation coefficient, R^2, between experimental results and predicted log BB was 0.878 and 0.986, respectively. The results obtained demonstrated that, for all compounds, the log BB values estimated by SVM agreed with the experimental data, demonstrating that SVM is an effective method for model development, and can be used as a powerful chemometric tool in QSPR studies.
基金supported by the Natural Science Foundation of Shaanxi Province (2009JQ2005)Foundation of Educational Commission of Shaanxi Province (09JK358) Graduate Innovation Fund of Shaanxi University of Science and Technology
文摘A novel three-dimensional holographic vector of atomic interaction field（3D-HoVAIF） was used to describe the chemical structures of 23 benzoxazinone derivatives as antithrombotic drugs.Here a quantitative structure activity relationship（QSAR） model was built by partial least-squares（PLS） regression.The estimation stability and prediction ability of the model were strictly analyzed by both internal and external validations.The correlation coefficients of established PLS model,leave-one-out（LOO） cross-validation,and predicted values versus experimental ones of external samples were R2=0.899,RCV2=0.854 and Qext2=0.868,respectively.These values indicated that the built PLS model had both favorable estimation stability and good prediction capabilities.Furthermore,the satisfactory results showed that 3D-HoVAIF could preferably express the information related to the biological activity of benzoxazinone derivatives.
文摘Identification of the drug-binding residues on the surface of proteins is a vital step in drug discovery and it is important for understanding protein function. Most previous researches are based on the structural information of proteins, but the structures of most proteins are not available. So in this article, a sequence-based method was proposed by combining the support vector machine (SVM)-based ensemble learning and the improved position specific scoring matrix (PSSM). In order to take the local environment information of a drug-binding site into account, an improved PSSM profile scaled by the sliding window and smoothing window was used to improve the prediction result. In addition, a new SVM-based ensemble learning method was developed to deal with the imbalanced data classification problem that commonly exists in the binding site predictions. When performed on the dataset of 985 drug-binding residues, the method achieved a very promising prediction result with the area under the curve (AUC) of 0.9264. Furthermore, an independent dataset of 349 drug- binding residues was used to evaluate the pre- diction model and the prediction accuracy is 84.68%. These results suggest that our method is effective for predicting the drug-binding sites in proteins. The code and all datasets used in this article are freely available at http://cic.scu.edu.cn/bioinformatics/Ensem_DBS.zip.
文摘纳米技术在生物领域的渗透形成了纳米生物技术,而纳米药物载体的研究是纳米生物技术的重点和热点。纳米级药物输送系统(Nanopartiele drug delivery system,NDDS)在实现靶向性给药、缓释药物、提高难溶性药物与多肽药物的生物利用度、降低药物的毒副作用等方面表现出良好的应用前景,因而也成为近年来药剂学领域的研究热点之一。本文综述了近年来出现的纳米药物载体的种类,并详细阐述了各类载体系统的特点和优点,为其进一步应用提供理论依据。
