Highlights•The deep learning method could effectively represent the molecular structure and
predict molecular property through diversified models.•One, two, and three-dimensional …

Abstract Structure-based virtual screening (SBVS) via docking has been used to discover
active molecules for a range of therapeutic targets. Chemical and protein data sets that …

Molecular docking computationally predicts the conformation of a small molecule when
binding to a receptor. Scoring functions are a vital piece of any molecular docking pipeline …

Artificial intelligence (AI) has been applied widely in our daily lives in a variety of ways with
numerous success stories. AI has also contributed to dealing with the coronavirus disease …

The ability of molecular property prediction is of great significance to drug discovery, human
health, and environmental protection. Despite considerable efforts, quantitative prediction of …

Drug discovery is a cost and time-intensive process that is often assisted by computational
methods, such as virtual screening, to speed up and guide the design of new compounds …

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 …

Topological deep learning (TDL) is a rapidly evolving field that uses topological features to
understand and design deep learning models. This paper posits that TDL is the new frontier …

Molecular descriptors are essential to not only quantitative structure-activity relationship
(QSAR) models but also machine learning–based material, chemical, and biological data …

Accelerated materials development with machine learning (ML) assisted screening and high
throughput experimentation for new photovoltaic materials holds the key to addressing our …