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The Primary Data Structures Used in Cheminformatics to Depict Chemical Structures in Chemical Graphs

Nidhi Singh

Abstract


A branch of mathematical science called chemical graph theory uses the basic principles of graph theory to study chemical phenomena and objects. The primary data types used in cheminformatics to represent chemical characteristics are chemical graphs. A key area of cheminformatics is the prediction (number) of structure activities and structure property. This is made possible by the computable properties of graphs. It is the foundation of contemporary fields like cheminformatics and bioinformatics and has historical relevance for natural sciences like chemistry, biochemistry, and biology. This paper first discusses the background of chemical science graph, next offers an overview of the several methods and computer-aided structure elucidation (CASE) applications it can be used for, and lastly highlights contemporary CASE tools that use chemical graph theory. The geometrical layout of chemicals can be modelled by a number of topological indices that come from graph theory.
The vapor pressure estimates for alkanes containing 1–12 carbon molecules are built using a number of these metaheuristic algorithms. An assortment of alkanes containing 13–22 carbon atoms have their boiling points predicted using models. For a family of alkanes with 10–20 carbon atoms and just one methyl group, melting temperature models are also taken into account. These methyl-substituted alkanes are particularly crucial for the manufacturing of jet and diesel fuels because they allow for a reduced saturation pressure for the final synthetic fuels. The physical properties of molecules for which there are no experimental data may be predicted using any model created in this way.

 


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