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Computational estimation of pK a values
Author(s) -
Seybold Paul G.,
Shields George C.
Publication year - 2015
Publication title -
wiley interdisciplinary reviews: computational molecular science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.126
H-Index - 81
eISSN - 1759-0884
pISSN - 1759-0876
DOI - 10.1002/wcms.1218
Subject(s) - cheminformatics , quantitative structure–activity relationship , computer science , mechanism (biology) , computational model , biological system , artificial intelligence , biochemical engineering , algorithm , chemistry , computational chemistry , machine learning , engineering , biology , physics , quantum mechanics
The pK a of a compound is one of its most important properties as it defines the specific molecular forms that will prevail under different pH conditions. Accordingly, accurate means for computational estimation of this property are of particular interest. Two main techniques for this purpose have emerged: (1) a first principles approach that relies on basic physical concepts and requires high computational resources, but is independent of experimental input and (2) a linear free energy or quantitative structure–activity relationship ( QSAR ) approach that combines molecular structural and energetic descriptors with available experimental pK a data to reduce computational demand and yield good accuracy. In this overview, these methods are described and their advantages and limitations are noted. WIREs Comput Mol Sci 2015, 5:290–297. doi: 10.1002/wcms.1218 This article is categorized under: Structure and Mechanism > Molecular Structures Structure and Mechanism > Computational Biochemistry and Biophysics Computer and Information Science > Chemoinformatics