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• W2938187418 abstract "One of the molecular properties most intuitive to the human perception is the geometrical shape. However, when exploring a large chemical space the determination of shape needs to be automated. We present a fast and simple approach to identify a molecule as linear, planar, cube, cuboid, disk, elliptical disk, spheroid and sphere which is more fine grained than existing approaches. The method is applied to more than one billion molecules ranging from small organic molecules to whole proteins. The results show that current chemistry research is biased towards planar geometries. Moreover, we demonstrate that our molecular shape classification correlates with sought-after properties like the band gap, dipole moment, and heat capacity. This allows to increase the efficiency of molecular design studies by driving high-throughput-screening efforts towards desired values of molecular properties." @default.
• W2938187418 created "2019-04-25" @default.
• W2938187418 creator A5065581694 @default.
• W2938187418 date "2019-04-15" @default.
• W2938187418 modified "2023-09-27" @default.
• W2938187418 title "Molecular shape as a (useful) bias in chemistry" @default.
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• W2938187418 hasPublicationYear "2019" @default.
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