Метод машинного навчання для створення нових лікарських речовин із заданими властивостями

Автор(и)

DOI:

https://doi.org/10.24144/2616-7700.2022.40(1).126-145

Ключові слова:

біологічно активні речовини, нейронна мережа, молекула, машинне навчання, молекулярна структура, молекулярний дескриптор

Анотація

Створення нових біологічно активних речовин є однією із найважливіших проблем фармацевтичної галузі. У цій статті запропоновано метод, у якому поєднуються кілька глибоких нейронних мереж для генерування унікальних молекул із заданими властивостями. Генерування доповнюється виправленням хімічної будови молекул із помилками за допомогою рекурентної нейронної мережі з механізмом уваги. Для створених молекулярних структур проведено аналіз хімічних властивостей та оцінку схожості на лікарські речовини. Запропонований ансамбль дозволяє створювати нові унікальні лікарські речовини, контролюючи ступінь розчинності та інші молекулярні дескриптори.

Посилання

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2022-05-12

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Гурбич, О. (2022). Метод машинного навчання для створення нових лікарських речовин із заданими властивостями. Науковий вісник Ужгородського університету. Серія «Математика і інформатика», 40(1), 126–145. https://doi.org/10.24144/2616-7700.2022.40(1).126-145

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Iнформатика, комп’ютернi науки та прикладна математика