Reinvent 4: Modern AI–driven generative molecule design
Most Cited Paper
in Computational Drug Discovery Methods
18 Months Post-Publication
Class of 2026
“Reinvent 4: Modern AI–driven generative molecule design”
A research intelligence initiative by Pepkio
pri.pepkio.com/top-papers/computational-drug-discovery-methods/2026/
Topics
REINVENT 4 · generative AI · Computational drug design · recurrent neural networks · Transformer · transfer learning · reinforcement learning · curriculum learning · De novo molecular design · R-group replacement · Library design · Linker design · Scaffold hopping · Molecular optimization · TOML configuration · JSON configuration · Drug discovery · Open-source framework · Apache 2.0 license
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Pepkio Research Index (PRI). Topics and Trends in Most Cited Computational Drug Discovery Methods Papers, Class of 2026. https://pri.pepkio.com/top-papers/computational-drug-discovery-methods/2026. Accessed 2026-07-22. Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459