AspirinCode/papers-for-molecular-design-using-DL

Curated repository organizing papers on generative AI and deep learning approaches for molecular/drug design and conformation generation, spanning architectures including diffusion models, VAEs, GANs, transformers, and reinforcement learning. Covers specialized applications across ligand-based, structure-based, fragment-based, and multi-objective design paradigms, plus material design and spectral data-driven generation. Includes complementary resources on datasets, benchmarks, evaluation metrics (QED, SAscore, RAscore), and molecular validation frameworks.

925 stars. Actively maintained with 12 commits in the last 30 days.