Prediction of chemical bioactivity and physical properties has been one of the most
important applications of statistical and more recently, machine learning and artificial …

Drug discovery and development pipelines are long, complex and depend on numerous
factors. Machine learning (ML) approaches provide a set of tools that can improve discovery …

Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …

SARS-CoV-2 virus which caused the global pandemic the Coronavirus Disease-2019
(COVID-2019) has infected about 1,203,959 patients and brought forth death rate about …

Highlights•Artificial Intelligence (AI) has transformed many areas such as speech and image
recognition, but not yet drug discovery.•Approaches to AI in drug discovery need to take in …

Peptide-protein interactions are involved in various fundamental cellular functions and their
identification is crucial for designing efficacious peptide therapeutics. Recently, a number of …

Natural products (NPs) are primarily recognized as privileged structures to interact with
protein drug targets. Their unique characteristics and structural diversity continue to marvel …

Highlights•Chemical graph theory and descriptors in drug discovery.•Chemical fingerprint
and similarity analysis.•Machine learning models for virtual screening.•Future challenges …

Abstract Since December 2019 the Severe Acute Respiratory Syndrome Coronavirus 2
(SARS-CoV-2) has produced an outbreak of pulmonary disease which has soon become a …

The task of predicting the interactions between drugs and targets plays a key role in the
process of drug discovery. There is a need to develop novel and efficient prediction …