Molecular docking has become an important component of the drug discovery process.
Since first being developed in the 1980s, advancements in the power of computer hardware …

Drug development is time‐consuming and expensive. Repurposing existing drugs for new
therapies is an attractive solution that accelerates drug development at reduced …

Highlights•Metabolomics has become a widely applied tool in drug development.•
Metabolomics plays a key role for the identification of physiological response markers.• …

Drug repurposing involves the identification of new applications for existing drugs at a lower
cost and in a shorter time. There are different computational drug-repurposing strategies and …

Conventional drug discovery and development is tedious and time-taking process; because
of which it has failed to keep the required pace to mitigate threats and cater demands of viral …

Introduction: Drug repurposing provides a cost-effective strategy to re-use approved drugs
for new medical indications. Several machine learning (ML) and artificial intelligence (AI) …

Cancer management is major concern of health organizations and viral cancers account for
approximately 15.4% of all known human cancers. Due to large number of patients, efficient …

Drug discovery and development is a complex and costly process. Machine learning
approaches are being investigated to help improve the effectiveness and speed of multiple …

Highlights•Inactivity data is helpful.•Structure-Inactivity Relationships (SIRs) are valuable in
drug discovery.•Machine and deep learning benefit from SIRs.•The inactivity data gap in the …

The interplay between life sciences and advancing technology drives a continuous cycle of
chemical data growth; these data are most often stored in open or partially open databases …