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Structure-based drug design involves finding ligand molecules that exhibit structural and chemical complementarity to protein pockets.
“Grammar variational autoencoder”
Matt Kusner, Brooks Paige and José Hernández-Lobato · 1954
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“SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules”
David Weininger · 1988
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“Distance geometry in molecular modeling”
Jeffrey Blaney and J Dixon · 1994
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“Deep Generative Models for 3D Linker Design”
Fergus Imrie, Anthony Bradley, Mihaela van Schaar and Charlotte Deane · 1995
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“Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings”
Christopher Lipinski, Franco Lombardo, Beryl Dominy and Paul Feeney · 1997
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“Virtual screening of chemical libraries”
Brian Shoichet · 2004
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“The PDBbind database: Collection of binding affinities for protein- ligand complexes with known three-dimensional structures”
Renxiao Wang, Xueliang Fang, Yipin Lu and Shaomeng Wang · 2004
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“Computer-based de novo design of drug-like molecules”
Gisbert Schneider and Uli Fechner · 2005
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“The cost of drug development: a systematic review”
Steve Morgan, Paul Grootendorst, Joel Lexchin, Colleen Cunningham and Devon Greyson · 2011
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“Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking”
Michael Mysinger, Michael Carchia, John Irwin and Brian Shoichet · 2012
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“Developability assessment as an early de-risking tool for biopharmaceutical development”
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Diederik Kingma and Max Welling · 2013
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“A generative model for molecular distance geometry”
Gregor Simm and José Hernández-Lobato · 2019
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“Utilizing graph machine learning within drug discovery and development”
Thomas Gaudelet, Ben Day, Arian Jamasb, Jyothish Soman, Cristian Regep, Gertrude Liu, Jeremy Hayter, Richard Vickers, Charles Roberts, Jian Tang, David Roblin, Tom Blundell, Michael Bronstein and Jake Taylor-King · 2021
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