Генеративная нейронная сеть на основе модели гетероэнкодера для de novo дизайна потенциальных противоопухолевых препаратов: применение к Bcr-Abl тирозинкиназе
Цели. Решается задача разработки генеративной модели гетероэнкодера для компьютерного дизайна потенциальных ингибиторов Bcr-Abl тирозинкиназы - фермента, активность которого является патофизиологической причиной хронического миелоидного лейкоза.Методы. На основе рекуррентных и полносвязных нейронных сетей прямого распространения создана генеративная модель гетероэнкодера. Проведены обучение и тестирование этой модели на наборе химических соединений, которые содержат 2-ариламинопиримид, присутствующий в качестве основного фармакофора в структурах многих низкомолекулярных ингибиторов протеинкиназ.Результаты. Разработанная нейронная сеть апробирована в процессе генерации широкого набора новых молекул и последующего анализа их химического сродства к Bcr-Abl тирозинкиназе методами молекулярного докинга.Заключение. Показано, что разработанная нейронная сеть представляет собой перспективную математическую модель для de novo дизайна малых молекул, которые потенциально активны против Bcr-Abl тирозинкиназы и могут быть использованы для разработки эффективных противоопухолевых препаратов широкого спектра действия.
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