Computer-aided drug discovery has been around for decades, although the past few years
have seen a tectonic shift towards embracing computational technologies in both academia …

Research in chemistry increasingly requires interdisciplinary work prompted by, among
other things, advances in computing, machine learning, and artificial intelligence. Everyone …

This chapter comprehensively explores the pivotal role of artificial intelligence (AI) in drug
discovery and development, encapsulating its potentials, methodologies, real-world …

Introduction: Artificial intelligence (AI) has inspired computer-aided drug discovery. The
widespread adoption of machine learning, in particular deep learning, in multiple scientific …

The application of artificial intelligence (AI) to chemistry has grown tremendously in recent
years. In this Review, we studied the growth and distribution of AI-related chemistry …

Abstract Machine learning (ML) promises to tackle the grand challenges in chemistry and
speed up the generation, improvement and/or ordering of research hypotheses. Despite the …

Recent advances and accomplishments of artificial intelligence (AI) and deep generative
models have established their usefulness in medicinal applications, especially in drug …

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 …

The case for a renewed focus on Nature in drug discovery is reviewed; not in terms of
natural product screening, but how and why biomimetic molecules, especially those …

Highlights•Drug discovery data and data from other sources are different in quantity and
characteristics.•This article underlines the difference of data from different domains.•In order …