Virtual screening of DrugBank database for hERG blockers using topological Laplacian-assisted AI models.

ABSTRACT: The human ether-a-go-go (hERG) potassium channel (K_v11.1) plays a critical role in mediating cardiac action potential. The blockade of this ion channel can potentially lead fatal disorder and/or long QT syndrome. Many drugs have been withdrawn because of their serious hERG-cardiotoxicity. It is crucial to assess the hERG blockade activity in the early stage of drug discovery. We are particularly interested in the hERG-cardiotoxicity of compounds collected in the DrugBank database considering that many DrugBank compounds have been approved for therapeutic treatments or have high potential to become drugs. Machine learning-based in silico tools offer a rapid and economical platform to virtually screen DrugBank compounds. We design accurate and robust classifiers for blockers/non-b

SUBMITTER: Feng H 

PROVIDER: S-EPMC10120853 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature