Literature DB >> 30840171

Automated simultaneous assignment of bond orders and formal charges.

Ivan D Welsh1,2, Jane R Allison3,4,5,6.   

Abstract

Bond orders and formal charges are fundamental chemical descriptors. In cheminformatic applications it is necessary to be able to assign these properties to a given molecular structure automatically, given minimal input information. Here we describe a method for determining the bond order and formal charge assignments from only the atom types and connectivity. Our method utilises a graph theoretical description of electron positions. Each electron position assignment is scored according to lookup tables of atomic and bond dissociation energies derived from quantum chemical calculations. We tested three different optimisation methods-local optimisation, an A* pathfinding method, and an FPT optimisation method utilising tree decompositions-for finding the best electron position assignment, from which the bond orders and formal charges are extracted. We show that our method can assign bond orders and formal charges at a high degree of accuracy across a wide range of molecules from two different databases, and that the FPT algorithm provides the best combination of speed and accuracy.

Entities:  

Keywords:  Bond order; Fixed parameter tractable; Formal charge; Graph theory

Year:  2019        PMID: 30840171      PMCID: PMC6419789          DOI: 10.1186/s13321-019-0340-0

Source DB:  PubMed          Journal:  J Cheminform        ISSN: 1758-2946            Impact factor:   5.514


  14 in total

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Journal:  J Chem Inf Model       Date:  2005 Sep-Oct       Impact factor: 4.956

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Authors:  Junmei Wang; Wei Wang; Peter A Kollman; David A Case
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9.  Automatic perception of organic molecules based on essential structural information.

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10.  Automated bond order assignment as an optimization problem.

Authors:  Anna Katharina Dehof; Alexander Rurainski; Quang Bao Anh Bui; Sebastian Böcker; Hans-Peter Lenhof; Andreas Hildebrandt
Journal:  Bioinformatics       Date:  2011-01-17       Impact factor: 6.937

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