title: A method to predict different mechanisms for blood-brain barrier permeability of CNS activity compounds in Chinese herbs using support vector machine.
abstract: The blood-brain barrier (BBB), a highly selective barrier between central nervous system (CNS) and the blood stream, restricts and regulates the penetration of compounds from the blood into the brain. Drugs that affect the CNS interact with the BBB prior to their target site, so the prediction research on BBB permeability is a fundamental and significant research direction in neuropharmacology. In this study, we combed through the available data and then with the help of support vector machine (SVM), we established an experiment process for discovering potential CNS compounds and investigating the mechanisms of BBB permeability of them to advance the research in this field four types of prediction models, referring to CNS activity, BBB permeability, passive diffusion and efflux transport, were obtained in the experiment process. The first two models were used to discover compounds which may have CNS activity and also cross the BBB at the same time; the latter two were used to elucidate the mechanism of BBB permeability of those compounds. Three optimization parameter methods, Grid Search, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), were used to optimize the SVM models. Then, four optimal models were selected with excellent evaluation indexes (the accuracy, sensitivity and specificity of each model were all above 85%). Furthermore, discrimination models were utilized to study the BBB properties of the known CNS activity compounds in Chinese herbs and this may guide the CNS drug development. With the relatively systematic and quick approach, the application rationality of traditional Chinese medicines for treating nervous system disease in the clinical practice will be improved.
authors.affiliation: 1 School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing 100102, P. R. China.
authors.forename: Ludi
authors.initials: L
authors.lastname: Jiang
authors.affiliation: 1 School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing 100102, P. R. China.
authors.forename: Jiahua
authors.initials: J
authors.lastname: Chen
authors.affiliation: 1 School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing 100102, P. R. China.
authors.forename: Yusu
authors.initials: Y
authors.lastname: He
authors.affiliation: 1 School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing 100102, P. R. China.
authors.forename: Yanling
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: 1 School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing 100102, P. R. China.
authors.forename: Gongyu
authors.initials: G
authors.lastname: Li
mesh_terms: D020168:ATP Binding Cassette Transporter, Subfamily B, Member 1 / Q000378:metabolism; D000465:Algorithms; D001812:Blood-Brain Barrier / Q000187:drug effects*; D002491:Central Nervous System Agents / Q000494:pharmacology*; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D006801:Humans; D008516:Medicine, Chinese Traditional; D008962:Models, Theoretical; D058990:Molecular Targeted Therapy / Q000379:methods; D010539:Permeability; D010946:Plants, Medicinal / Q000737:chemistry*; D015203:Reproducibility of Results; D060388:Support Vector Machine
chemical_list: D020168:ATP Binding Cassette Transporter, Subfamily B, Member 1; D002491:Central Nervous System Agents
keywords: Blood–brain barrier; central nervous system; passive diffusion, efflux transport; support vector machine