G-RMSD: Root Mean Square Deviation Based Method for Three-dimensional Molecular Similarity Determination

05 March 2020, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

We present the Generalized Root Mean Square Deviation (G-RMSD) method. G-RMSD is an optimization method to calculate the minimal RMSD value of two atomic structures by optimal superimposition. The method is not restricted to systems with an equal number of atoms or a unique atom matching and can handle any type of chemical structure, including transition states and non-valence bond structures. It requires only Cartesian coordinates for the structures, but can also include further information, i.e. atom and bond types. Applications of G-RMSD to the classification of alpha-D-glucose conformers and 3D partial structure search using a dataset containing equilibrium (EQ), dissociation channel (DC), and transition state (TS) structures are demonstrated. We find that G-RMSD allows for a successful classification and mapping for a wide variety of molecular structures.

Keywords

Optimal superimposition for minimum RMSD
3D-molecular similarity
3D-database search
Transition states
Non-valence structures

Supplementary materials

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Description
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aDglucose-GRRM-RHF631G
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CH2OH-anion-B3LYP631Gd
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CH2OH-cation-B3LYP631Gd
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CH3-anion-B3LYP631Gd
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CH3-cation-B3LYP631Gd
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H4C2O2-GRRM-B3LYP631Gd
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Supplementary weblinks

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