A Brief Review of Machine Learning-Based Bioactive Compound Research

Bioactive compounds are often used as initial substances for many therapeutic agents. In recent years, both theoretical and practical innovations in hardware-assisted fast-evolving machine learning (ML) have made it possible to identify desired bioactive chemical spaces, such those natural products (NPs). This review introduces how approaches can be the identification evaluation of compounds. It also provides an overview research trends learning-based prediction by listing real-world examples along with various input data. addition, several ML-based specific cardiovascular metabolic diseases described. Overall, these important discovery novel provide new insights into basis traditional applications compound-related research.