Application of deep learning techniques for de novo generation of molecules, termed as
inverse molecular design, has been gaining enormous traction in drug design. The …

Artificial intelligence (AI) is booming. Among various AI approaches, generative models
have received much attention in recent years. Inspired by these successes, researchers are …

Drug discovery based on artificial intelligence has been in the spotlight recently as it
significantly reduces the time and cost required for developing novel drugs. With the …

Anti-cancer drug design has been acknowledged as a complicated, expensive, time-
consuming, and challenging task. How to reduce the research costs and speed up the …

Accurate and reliable prediction of the optical and photophysical properties of organic
compounds is important in various research fields. Here, we developed deep learning (DL) …

From the perspective of historical review, the methodology of economics develops from
qualitative to quantitative, from a small sampling of data to a vast amount of data. Because of …

Photoswitches are molecular systems that are chemically transformed subsequent to
interaction with light and they find potential application in many new technologies. The …

Conventional drug discovery is long and costly, and suffers from high attrition rates, often
leaving patients with limited or expensive treatment options. Recognizing the overwhelming …

A grand challenge in polymer science lies in the predictive design of new polymeric
materials with targeted functionality. However, de novo design of functional polymers is …

We address the problem of generating novel molecules with desired interaction properties
as a multi-objective optimization problem. Interaction binding models are learned from …