Prediction of kinase inhibitors binding modes with machine learning and reduced descriptor sets.

ABSTRACT: Protein kinases are receiving wide research interest, from drug perspective, due to their important roles in human body. Available kinase-inhibitor data, including crystallized structures, revealed many details about the mechanism of inhibition and binding modes. The understanding and analysis of these binding modes are expected to support the discovery of kinase-targeting drugs. The huge amounts of data made it possible to utilize computational techniques, including machine learning, to help in the discovery of kinase-targeting drugs. Machine learning gave reasonable predictions when applied to differentiate between the binding modes of kinase inhibitors, promoting a wider application in that domain. In this study, we applied machine learning supported by feature selection techniques to c

SUBMITTER: Abdelbaky I 

PROVIDER: S-EPMC7804204 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature