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ISSN 2313-1748 (Online)

Гибридная стратегия биоинформатического моделирования (in silico) для изучения биологически активных пептидов молочного белка

Аннотация
Методы биоинформатического анализа – вспомогательный инструмент в проведении предварительного этапа исследований процесса биокаталитической конверсии белков с прогнозируемым высвобождением биологически активных пептидов. Однако существует ряд факторов, не учитывающихся в современных стратегиях при проектировании биологически активных пептидов, что препятствует полномасштабному прогнозированию их биологических свойств. Это обуславливает актуальность выбранной цели исследования – разработку гибридной стратегии биоинформатического моделирования для изучения биологически активных пептидов молочного белка с учетом ранжирования ключевых критериев на основе высокопроизводительных алгоритмов протеомных баз данных.
Объектом исследования является научная литература, касающаяся методов in silico биологически активных пептидов. Применялись современные таксонометрические методы поиска информации с использованием баз данных РИНЦ, Scopus и Web of Science.
Сформирован и поэтапно описан оптимальный алгоритм гибридной стратегии in silico изучения биологически активных пептидов молочного белка с учетом оценки безопасности всех продуктов гидролиза, их физико-химических и технологических свойств. Алгоритм стратегии сформирован исходя из аналитических данных о белковом профиле, аминокислотной последовательности белков, входящих в состав сырья с учетом их полиморфизма, и последующей идентификации биоактивных аминокислотных сайтов в структуре белка. В алгоритм включен подбор оптимальных ферментных препаратов и моделирование гидролиза с оценкой биоактивности пептидов по протеомным базам данных.
Предложенная стратегия in silico позволит на предварительном этапе проведения гидролиза белка научно прогнозировать направленное высвобождение стабильных пептидных комплексов биологически активных пептидов с доказанными биоактивностью, безопасностью и сенсорными характеристиками. Гибридный алгоритм будет способствовать аккумулированию необходимых первичных данных для сокращения временных и финансовых затрат на проведение реальных экспериментов.
Ключевые слова
Молочные белки , пептиды , база данных , биоинформатика , in silico
ФИНАНСИРОВАНИЕ
Исследование выполнено за счет гранта Российского научного фонда (РНФ) № 21-76-00044.
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Как цитировать?
Гибридная стратегия биоинформатического моделирования (<i>in silico</i>) для изучения биологически активных пептидов молочного белка. Техника и технология пищевых производств, 2022, vol. 52, no. 1, pp. 46-57
DOI
http://doi.org/10.21603/2074-9414-2022-1-46-57
Издатель
Кемеровский государственный университет
https://kemsu.ru
ISSN
2074-9414 (Print) /
2313-1748 (Online)
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