Exploring chemical space for drug discovery using the chemical universe database.

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EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction (2022, background): “Worse, there are 10 60 possible drug-like molecules (Reymond & Awale, 2012), going far beyond current experimental capabilities.”
A perspective on conventional high-temperature superconductors at high pressure: Methods and materials (2019, background): “The estimated chemical space for drug discovery is quantitatively of the order of several millions of structures and compositions [472].”
QM7-X: A comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules (2020, background): “, for a methane (CH4) molecule, ’atNUM’ is a 1D array of N = 5 elements ([6,1,1,1,1]) while ’atXYZ’ is a 2D array comprised of N = 5 rows and three columns (x,y,z coordinates).”
Generic Strategies for Chemical Space Exploration (2013, background): “Atom types are given as vertex labels, while edges represent bond types.”