MOTIVATION: Efficient assessment of the blood-brain barrier (BBB) penetration ability of a drug compound is one of the major hurdles in central nervous system drug discovery since experimental methods are costly and time-consuming. To advance and elevate the success rate of neurotherapeutic drug discovery, it is essential to develop an accurate computational quantitative model to determine the absolute logBB value (a logarithmic ratio of the concentration of a drug in the brain to its concentration in the blood) of a drug candidate. RESULTS: Here, we developed a quantitative model (LogBB_Pred) capable of predicting a logBB value of a query compound. The model achieved an R2 of 0.61 on an independent test dataset and outperformed other publicly available quantitative models. When compared with the available qualitative (classification) models that only classified whether a compound is BBB-permeable or not, our model achieved the same accuracy (0.85) with the best qualitative model and far-outperformed other qualitative models (accuracies between 0.64 and 0.70). For further evaluation, our model, quantitative models, and the qualitative models were evaluated on a real-world central nervous system drug screening library. Our model showed an accuracy of 0.97 while the other models showed an accuracy in the range of 0.29-0.83. Consequently, our model can accurately classify BBB-permeable compounds as well as predict the absolute logBB values of drug candidates. AVAILABILITY AND IMPLEMENTATION: Web server is freely available on the web at http://ssbio.cau.ac.kr/software/logbb_pred/. The data used in this study are available to download at http://ssbio.cau.ac.kr/software/logbb_pred/dataset.zip.

An application framework is a reusable "skeleton" application that can be specialized to develop custom applications.As microservices become more popular in the software industry, the importance of methodologies for designing microservices-oriented frameworks is increasing.However, the existing methodologies for designing application frameworks, which were developed for the monolithic environment, do not fit the microservice architecture well.To address this issue, this study extends Schmid's systematic generalization approach to enable the design of microservice-oriented application frameworks.The methodology introduces communication spots, which define the execution orders among services, and communication styles, which define the communication relationship among services, to capture the communication characteristics in microservice environments.The methodology also proposes the strategies in microservice generalization and the usage of integration patterns in transforming a microservice-oriented application into a microservice-oriented framework.The new methodology can facilitate a developer to systematically design a microserviceoriented application framework by generalizing from a microservice application.A case study is used to demonstrate how to apply the proposed methodology to design a microservice frauddetection framework.