TAGMol: Target-Aware Gradient-guided Molecule Generation

arXiv:2406.01650v1 Announce Type: cross
Abstract: 3D generative models have shown significant promise in structure-based drug design (SBDD), particularly in discovering ligands tailored to specific target binding sites. Existing algorithms often focus primarily on ligand-target binding, characterized by binding affinity. Moreover, models trained solely on target-ligand distribution may fall short in addressing the broader objectives of drug discovery, such as the development of novel ligands with desired properties like drug-likeness, and synthesizability, underscoring the multifaceted nature of the drug design process. …

abstract algorithms arxiv cs.ai cs.lg design distribution drug design focus generative generative models gradient ligands q-bio.bm type