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

In this Viewpoint, we discuss the current progress in applications of machine learning (ML)
and artificial intelligence (AI) to meet the challenges of computational drug discovery. We …

The advancement of computing and technology has invaded all the dimensions of science.
Artificial intelligence (AI) is one core branch of Computer Science, which has percolated to …

In recent years, the development of high-throughput screening (HTS) technologies and their
establishment in an industrialized environment have given scientists the possibility to test …

Drug development is expensive, time-consuming, and has a high failure rate. In recent
years, artificial intelligence (AI) has emerged as a transformative tool in drug discovery …

Highlights•Drug discovery has been advanced to a big data era with a large amount of
public data sources available.•Ten V features (volume, velocity, variety, veracity, validity …

Drug discovery is time-and resource-consuming. To this end, computational approaches that
are applied in de novo drug design play an important role to improve the efficiency and …

Introduction: Neural networks are becoming a very popular method for solving machine
learning and artificial intelligence problems. The variety of neural network types and their …

The current rise of artificial intelligence and machine learning has been significant. It has
reduced the human workload improved quality of life significantly. This article describes the …

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 …