Web services for the prediction of ADMET parameters relevant to the design of neuroprotective drugs

Perkin, V.O.; Antonyan, G.V.; Radchenko, E.V.; Palyulin, V.A.

Авторы: Perkin Valentin O., Antonyan Grigory V., Radchenko Eugene V., Palyulin Vladimir A.
Сборник: Computational Modeling of Drugs Against Alzheimer’s Disease Second Edition
Серия: Neuromethods
Том: 203
Глава в коллективной монографии
Год издания: 2023
Издательство: Springer Science+Business Media
Местоположение издательства: New York, United States
Первая страница: 465
Последняя страница: 485
DOI: 10.1007/978-1-0716-3311-3_16
Аннотация: The ADMET properties (absorption, distribution, metabolism, excretion, and toxicity) of a compound are key factors in its success as a drug. While many experimental approaches to their measurement are available, the computational approaches are in high demand due to their cost-and time-efficiency. Some ADMET properties are especially relevant for Alzheimer’s disease treatments and other neuroprotective compounds. This review provides an overview of 13 online tools that can be used to predict the ADMET profile of a compound, with a special focus on the properties such as lipophilicity, aqueous solubility, hERG inhibition, blood–brain barrier permeability, Caco-2 permeability, human intestinal absorption, and Ames mutagenic-ity. The functionality of different tools is compared, and the correlations of their predictions with one another and with the available experimental data are analyzed.
Добавил в систему: Радченко Евгений Валерьевич

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Web services for the prediction of ADMET parameters relevant to the design of neuroprotective drugsстатья

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