Application of computational biology and artificial intelligence in drug design
Traditional drug design requires a great amount of research time and developmental
expense. Booming computational approaches, including computational biology, computer …
expense. Booming computational approaches, including computational biology, computer …
Diffusion models in bioinformatics and computational biology
Denoising diffusion models embody a type of generative artificial intelligence that can be
applied in computer vision, natural language processing and bioinformatics. In this Review …
applied in computer vision, natural language processing and bioinformatics. In this Review …
Accurate structure prediction of biomolecular interactions with AlphaFold 3
The introduction of AlphaFold 21 has spurred a revolution in modelling the structure of
proteins and their interactions, enabling a huge range of applications in protein modelling …
proteins and their interactions, enabling a huge range of applications in protein modelling …
Diffdock: Diffusion steps, twists, and turns for molecular docking
Predicting the binding structure of a small molecule ligand to a protein--a task known as
molecular docking--is critical to drug design. Recent deep learning methods that treat …
molecular docking--is critical to drug design. Recent deep learning methods that treat …
Structure-based drug design with equivariant diffusion models
Abstract Structure-based drug design (SBDD) aims to design small-molecule ligands that
bind with high affinity and specificity to pre-determined protein targets. Generative SBDD …
bind with high affinity and specificity to pre-determined protein targets. Generative SBDD …
An artificial intelligence accelerated virtual screening platform for drug discovery
Abstract Structure-based virtual screening is a key tool in early drug discovery, with growing
interest in the screening of multi-billion chemical compound libraries. However, the success …
interest in the screening of multi-billion chemical compound libraries. However, the success …
ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling
Most molecular generative models based on artificial intelligence for de novo drug design
are ligand-centric and do not consider the detailed three-dimensional geometries of protein …
are ligand-centric and do not consider the detailed three-dimensional geometries of protein …
DynamicBind: Predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model
While significant advances have been made in predicting static protein structures, the
inherent dynamics of proteins, modulated by ligands, are crucial for understanding protein …
inherent dynamics of proteins, modulated by ligands, are crucial for understanding protein …
Efficient and accurate large library ligand docking with KarmaDock
Ligand docking is one of the core technologies in structure-based virtual screening for drug
discovery. However, conventional docking tools and existing deep learning tools may suffer …
discovery. However, conventional docking tools and existing deep learning tools may suffer …
Calibrated geometric deep learning improves kinase–drug binding predictions
Protein kinases regulate various cellular functions and hold significant pharmacological
promise in cancer and other diseases. Although kinase inhibitors are one of the largest …
promise in cancer and other diseases. Although kinase inhibitors are one of the largest …