Designing molecules with certain physicochemical features can promote the discovery and
optimization of lead compounds. However, most molecular generation models optimize only …

Recent achievements in large-scale pre-trained models like GPT-3 and PanGu-α showed
amazing performances in many downstream tasks, which makes AI friendlier toward …

Optimization techniques play a pivotal role in advancing drug development, serving as the
foundation of numerous generative methods tailored to efficiently design optimized …

Artificial intelligence and multiobjective optimization represent promising solutions to bridge
chemical and biological landscapes by addressing the automated de novo design of …

Drug discovery and development is a complex, lengthy process, and failure of a candidate
molecule can occur as a result of a combination of reasons, such as poor pharmacokinetics …

In polypharmacology drugs are required to bind to multiple specific targets, for example to
enhance efficacy or to reduce resistance formation. Although deep learning has achieved a …

Computer aided drug design is a promising approach to reduce the tremendous costs, ie
time and resources, for developing new medicinal drugs. It finds application in aiding the …

Solid tumors must recruit new blood vessels for growth and maintenance. Discovering drugs
that block tumor-induced development of new blood vessels (angiogenesis) is an important …

Background: Drug design is a challenging and important task that requires the generation of
novel and effective molecules that can bind to specific protein targets. Artificial intelligence …

Drug discovery and development is a complex, lengthy process and failure of a candidate
molecule can occur as a result of a combination of reasons, such as poor pharmacokinetics …