New and Original pK a Prediction Method Using Grid Molecular Interaction Fields

One of the most important physicochemical properties of a molecule is pK a. It is known that two parameters imperative in ADME profiling, solubility, and lipophilicity are governed by pK a, and receptor binding can be influenced by pK a. Because most drugs are ionized in physiological conditions, pK...

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Bibliographic Details
Published in:Journal of chemical information and modeling 2007-11, Vol.47 (6), p.2172-2181
Main Authors: Milletti, Francesca, Storchi, Loriano, Sforna, Gianluca, Cruciani, Gabriele
Format: Article
Language:English
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Summary:One of the most important physicochemical properties of a molecule is pK a. It is known that two parameters imperative in ADME profiling, solubility, and lipophilicity are governed by pK a, and receptor binding can be influenced by pK a. Because most drugs are ionized in physiological conditions, pK a is particularly relevant to medicinal chemistry. Despite the numerous advances in high-throughput measurements, in silico determination is still the fastest and cheapest way of obtaining pK a. This paper presents a new original computational method for pK a prediction of organic compounds. Descriptors were generated using the program GRID, and these descriptors are based on molecular interaction fields precomputed on a set of molecular fragments. The new method was developed, trained, and cross-validated by using a large and diverse data set of 24 617 pK a values. This paper presents the results for a class of 421 acidic nitrogen compounds (RMSE = 0.41, r 2 = 0.97, q 2 = 0.87) and for a class of 947 six-membered N-heterocyclic bases (RMSE = 0.60, r 2 = 0.93, q 2 = 0.85). For external validation 28 novel compounds were selected that covered nine different ionizable groups, and 39 pK a values could be experimentally determined by spectral gradient analysis (SGA). Comparison of experimental pK a with calculated pK a demonstrated that the predictive ability of the method is good (external set, r 2 = 0.85, RMSE = 0.90).
ISSN:1549-9596
1549-960X
DOI:10.1021/ci700018y