A Deep Learning Approach for Rational Ligand Generation with Toxicity Control

Chemistry, Medicinal Chemistry, Information Science, Artificial Intelligence, Life Sciences, Biochemistry,
deep learning   ligand generation   toxicity control   drug design   computational model   block-based generation   molecular optimization  

Latest Research on Deep Learning Applied to Target Protein Ligand Generation: Proposal and Validation of the DeepBlock Framework Background and Research Problem In the drug discovery process, finding ligand molecules that bind to specific proteins has always been a core objective. However, current virtual screening methods are often limited by the ...

Structural Basis of Antagonist Selectivity in Endothelin Receptors

Chemistry, Medicinal Chemistry, Medicine, Cardiovascular System, Life Sciences, Cell Biology, Biochemistry, Immunology,
antagonist   endothelin receptors   structural biology   drug design   vascular homeostasis  

Deciphering Antagonist Selectivity of Endothelin Receptors: Insights from Cryo-EM-Based Structural Studies Academic Background Endothelin (ET) is a potent vasoconstrictor peptide that plays a significant role in regulating cardiovascular functions. The endothelin family includes ET-1, ET-2, and ET-3, which regulate vascular tone and cardiovascular ...

Equivariant 3D Conditional Diffusion Model for Molecular Linker Design

Equivariant 3D Conditional Diffusion Model for Molecular Linker Design

Chemistry, Medicinal Chemistry, Computational Chemistry, Information Science, Artificial Intelligence, Medicine, Pharmacy,
molecular linker design   drug design   generative model  

From early drug discovery researchers face a daunting challenge – to find drug-like candidate molecules among approximately 10^60 possible molecular structures. One successful solution is to start from smaller “fragment” molecules, a strategy known as fragment-based drug design (FBDD). In the FBDD process, the first step is to computationally scree...