A new framework to automate, augment, and accelerate steps in computer‐aided molecular
design is presented. The problem is tackled in three stages:(1) composition design,(2) …

Multi‐parameter optimization (MPO) is a major challenge in new chemical entity (NCE) drug
discovery. Recently, promising results were reported for deep learning generative models …

Highlights•Quantum computing and its use for computer-aided product design is discussed
and perspectives for several types of problems are provided.•Hybrid QC methods are likely …

Materials discovery is decisive for tackling urgent challenges related to energy, the
environment, health care, and many others. In chemistry, conventional methodologies for …

This article provides an introduction to and review of the field of computer-aided molecular
design (CAMD). It is intended to be approachable for the absolute beginner as well as useful …

De novo drug design aims to generate novel chemical compounds with desirable chemical
and pharmacological properties from scratch using computer-based methods. Recently …

In this review, we highlight recent developments in the application of machine learning for
molecular modeling and simulation. After giving a brief overview of the foundations …

During the last decade, modern machine learning has found its way into synthetic chemistry.
Some long‐standing challenges, such as computer‐aided synthesis planning (CASP), have …

The need for more efficient catalytic processes is ever-growing, and so are the costs
associated with experimentally searching chemical space to find new promising catalysts …

Deep generative models have shown the ability to devise both valid and novel chemistry,
which could significantly accelerate the identification of bioactive compounds. Many current …