Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …

Geometric deep learning (GDL) is based on neural network architectures that incorporate
and process symmetry information. GDL bears promise for molecular modelling applications …

Predicting how a drug-like molecule binds to a specific protein target is a core problem in
drug discovery. An extremely fast computational binding method would enable key …

Illuminating interactions between proteins and small drug molecules is a long-standing
challenge in the field of drug discovery. Despite the importance of understanding these …

Conventional wet laboratory testing, validations, and synthetic procedures are costly and
time-consuming for drug discovery. Advancements in artificial intelligence (AI) techniques …

Traditional Chinese medicine (TCM) is a precious treasure of the Chinese nation and has
unique advantages in the prevention and treatment of diseases. The holistic view of TCM …

The COVID-19 pandemic has emphasized the need for novel drug discovery process.
However, the journey from conceptualizing a drug to its eventual implementation in clinical …

Artificial intelligence (AI) is often presented as a new Industrial Revolution. Many domains
use AI, including molecular simulation for drug discovery. In this review, we provide an …

Drug development based on target proteins has been a successful approach in recent
decades. However, the conventional structure-based drug design (SBDD) pipeline is a …

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