Artificial Intelligence Drug Design
Artificial Intelligence Drug Design (AIDD) refers to the integration of artificial intelligence technologies into innovative drug discovery, leveraging big data for precise drug design to enable faster and more cost-effective development of new therapeutics.
In 2021, DeepMind released AlphaFold2, an algorithm capable of predicting protein 3D structures with near-experimental accuracy. This achievement has been regarded as one of the most significant scientific breakthroughs of the 21st century. In 2024, the release of AlphaFold3 further advanced the field by enabling the prediction of structures and interactions of nearly all biomolecules, including proteins, DNA, RNA, and small molecules. These developments have greatly accelerated life sciences research and propelled artificial intelligence into the forefront of biopharmaceutical innovation.
Also in 2024, David Baker, a Nobel Laureate in Chemistry, made groundbreaking contributions to computational protein design. Using the RoseTT series of software, his team successfully designed entirely novel proteins not found in nature, opening up transformative possibilities in drug discovery and vaccine development.
While AI has already achieved remarkable progress in protein structure prediction and design, the future of AI-driven drug discovery extends far beyond these areas. It plays a crucial role in lead compound screening, molecular dynamics simulations, and more. TargetMol leverages its proprietary deep learning algorithm PLANET to search for drug-like molecules within an ultra-large compound database of up to 6 billion entries (Topscience Database). In addition, its microsecond-scale long-timescale molecular dynamics simulation platform enables rapid insights into protein–ligand interactions, significantly accelerating the advancement of innovative drug research.