vestnik-bio-msuВестник Московского университета. Серия 16. БиологияVestnik Moskovskogo universiteta. Seriya 16. Biologiya0137-0952Lomonosov Moscow State University, School of Biology10.55959/MSU0137-0952-16-80-3S-13vestnik-bio-msu-1546Research ArticleОригинальные исследованияСтруктурные особенности каротиноид-связывающих белковStructural features of carotenoid-binding proteinshttps://orcid.org/0009-0001-5688-8753СурковМ. М.SurkovM. M.

Сурков Макар Максимович – студент магистратуры кафедры биофизики биологического факультета  

119234, г. Москва, Ленинские горы, д. 1, стр. 24 

Тел.: 8-495-939-11-16 

1–24 Leninskie gory, 119234, Moscow

macsurmak.m02@mail.ruhttps://orcid.org/0009-0000-5329-9796ЛитовецА. Ю.LitovetsA. Yu.

Литовец Андрей Юрьевич – студент кафедры биофизики биологического факультета

119234, г. Москва, Ленинские горы, д. 1, стр. 24 

Тел.: 8-495-939-11-16  

1–24 Leninskie gory, 119234, Moscow

litovetsay@my.msu.ruhttps://orcid.org/0000-0002-6025-7663МамчурА. А.MamchurA. A.

Мамчур Александра Александровна – аспирант кафедры биофизики биологического факультета 

119234, г. Москва, Ленинские горы, д. 1, стр. 24 

Тел.: 8-495-939-11-16 

1–24 Leninskie gory, 119234, Moscow

al.mam4ur@yandex.ruhttps://orcid.org/0000-0002-8427-8178Станишнева-КоноваловаТ. Б.Stanishneva-KonovalovaT. B.

Станишнева-Коновалова Татьяна Борисовна – канд. биол. наук, ст. науч. сотр. кафедры биоинженерии биологического факультета 

119234, г. Москва, Ленинские горы, д. 1, стр. 73 

 Тел.: 8-495-939-57-38 

1–73 Leninskie gory, 119234, Moscow

stanishneva-konovalova@mail.bio.msu.ruhttps://orcid.org/0000-0002-8525-5568ЯрошевичИ. А.YaroshevichI. A.

Ярошевич Игорь Александрович – канд. биол. наук., ст. науч. сотр. кафедры биофизики биологического факультета 

119234, г. Москва, Ленинские горы, д. 1, стр. 24 

Тел.: 8-495-939-11-16 

1–24 Leninskie gory, 119234, Moscow

iyapromo@gmail.comКафедра биофизики, биологический факультет, Московский государственный университет имени М.В. ЛомоносоваРоссияDepartment of Biophysics, Faculty of Biology, Lomonosov Moscow State UniversityRussian FederationКафедра биоинженерии, биологический факультет, Московский государственный университет имени М.В. ЛомоносоваРоссияDepartment of Bioengineering, Faculty of Biology, Lomonosov Moscow State UniversityRussian Federation202510112025803S87–95Copyright © Сурков М.М., Литовец А.Ю., Мамчур А.А., Станишнева-Коновалова Т.Б., Ярошевич И.А., 20252025Сурков М.М., Литовец А.Ю., Мамчур А.А., Станишнева-Коновалова Т.Б., Ярошевич И.А.Surkov M.M., Litovets A.Y., Mamchur A.A., Stanishneva-Konovalova T.B., Yaroshevich I.A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://vestnik-bio-msu.elpub.ru/jour/article/view/1546

Каротиноид-белковые комплексы участвуют в процессах фотосинтеза, фоторецепции, защиты от окислительного стресса, обмена веществ и пигментации. В данной работе проведен детальный анализ доступных структурных данных с атомарным разрешением каротиноид-содержащих белков. В ходе исследования проанализированы молекулярные особенности каротиноид-связывающих областей белков и структурные особенности связанных каротиноидов. Полученные результаты указывают на общие принципы организации белок-каротиноидных взаимодействий, необходимые для разработки новых подходов к их направленной модификации. Методом машинного обучения создана модель для прогноза каротиноид-связывающей активности по первичной структуре белка.

Carotenoid-protein complexes play a crucial role in photosynthesis, photoreception, protection against oxidative stress, metabolism, and pigmentation. This study conducts a detailed analysis of structural data with atomic resolution for carotenoid-containing proteins. The research examines molecular features of carotenoid-binding regions and structural characteristics of bound carotenoids. The findings reveal general principles of the protein-carotenoid interface organization, essential for developing new approaches to targeted modification. Additionally, a machine learning model is created to predict carotenoid-binding activity based on the primary protein structure.

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The authors declare that there are no conflicts of interest present.