A novel machine learning-based screening identifies statins as inhibitors of the calcium pump SERCA.

ABSTRACT: We report a novel small-molecule screening approach that combines data augmentation and machine learning to identify Food and Drug Administration (FDA)-approved drugs interacting with the calcium pump (Sarcoplasmic reticulum Ca²⁺-ATPase, SERCA) from skeletal (SERCA1a) and cardiac (SERCA2a) muscle. This approach uses information about small-molecule effectors to map and probe the chemical space of pharmacological targets, thus allowing to screen with high precision large databases of small molecules, including approved and investigational drugs. We chose SERCA because it plays a major role in the excitation-contraction-relaxation cycle in muscle and it represents a major target in both skeletal and cardiac muscle. The machine learning model predicted that SERCA1a and SERCA2a are

SUBMITTER: Cruz-Cortes C 

PROVIDER: S-EPMC10193016 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature