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3D Deep Learning for Biological Function Prediction from Physical Fields
In this paper, we show that deep learning can predict biological function of molecules directly from their raw 3D approximated electron density and electrostatic potential fields.
Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued images
A contact map is a compact representation of the three-dimensional structure of a protein via the pairwise contacts between the amino acid constituting the protein.
Improving contact prediction along three dimensions
Correlation patterns in multiple sequence alignments of homologous proteins can be exploited to infer information on the three-dimensional structure of their members.
Designing a Prospective COVID-19 Therapeutic with Reinforcement Learning
This suggests that combining leading protein design methods with modern deep reinforcement learning is a viable path for discovering a Covid-19 cure and may accelerate design of peptide-based therapeutics for other diseases.
