Web: http://arxiv.org/abs/2106.02190

Jan. 26, 2022, 2:11 a.m. | Yulun Wu, Nicholas Choma, Andrew Chen, Mikaela Cashman, Érica T. Prates, Verónica G. Melesse Vergara, Manesh Shah, Austin Clyde, Thomas S. B

cs.LG updates on arXiv.org arxiv.org

We developed Distilled Graph Attention Policy Network (DGAPN), a
reinforcement learning model to generate novel graph-structured chemical
representations that optimize user-defined objectives by efficiently navigating
a physically constrained domain. The framework is examined on the task of
generating molecules that are designed to bind, noncovalently, to functional
sites of SARS-CoV-2 proteins. We present a spatial Graph Attention (sGAT)
mechanism that leverages self-attention over both node and edge attributes as
well as encoding the spatial structure -- this capability is of …

arxiv attention discovery drug discovery graph policy

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