Structural features of carotenoid-binding proteins
https://doi.org/10.55959/MSU0137-0952-16-80-3S-13
Abstract
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.
About the Authors
M. M. SurkovRussian Federation
1–24 Leninskie gory, 119234, Moscow
A. Yu. Litovets
Russian Federation
1–24 Leninskie gory, 119234, Moscow
A. A. Mamchur
Russian Federation
1–24 Leninskie gory, 119234, Moscow
T. B. Stanishneva-Konovalova
Russian Federation
1–73 Leninskie gory, 119234, Moscow
I. A. Yaroshevich
Russian Federation
1–24 Leninskie gory, 119234, Moscow
References
1. Yabuzaki J. Carotenoids Database: structures, chemical fingerprints and distribution among organisms. Database. 2017;2017:bax004.
2. Havaux M. Carotenoids as membrane stabilizers in chloroplasts. Trends Plant Sci. 1998;3(4):147–151.
3. Yaroshevich I.A., Krasilnikov P.M., Rubin A.B. Functional interpretation of the role of cyclic carotenoids in photosynthetic antennas via quantum chemical calculations. Comput. Theor. Chem. 2015;1070:27–32.
4. Tanumihardjo S.A., Palacios N., Pixley K.V. Provitamin A carotenoid bioavailability: What really matters? Int. J. Vitam. Nutr. Res. 2010;80(45):336–350.
5. Winterhalter P., Rouseff R.L., Eds. Carotenoid-derived aroma compounds. American Chemical Society; Distributed by Oxford University Press; 2002. 323 pp.
6. Sasamoto H., Suzuki S., Mardani-Korrani H., Sasamoto Y., Fujii Y. Allelopathic activities of three carotenoids, neoxanthin, crocin and β-carotene, assayed using protoplast co-culture method with digital image analysis. Plant Biotechnol. 2021;38(1):101–107.
7. Sharoni Y., Danilenko M., Walfisch S., Amir H., Nahum A., Ben-Dor A., Hirsch K., Khanin M., Steiner M., Agemy L., Zango G., Levy J. Role of gene regulation in the anticancer activity of carotenoids. Pure Appl. Chem. 2002;74(8):1469–1477.
8. Eid S.Y., El-Readi M.Z., Wink M. Carotenoids reverse multidrug resistance in cancer cells by interfering with ABC-transporters. Phytomedicine. 2012;19(11):977–987.
9. Piccinini L., Iacopino S., Cazzaniga S., Ballottari M., Giuntoli B., Licausi F. A synthetic switch based on orange carotenoid protein to control blue–green light responses in chloroplasts. Plant Physiol. 2022;189(2):1153–1168.
10. Maksimov E.G., Yaroshevich I.A., Tsoraev G.V., Sluchanko N.N., Slutskaya E.A., Shamborant O.G., Bobik T.V., Friedrich T., Stepanov A.V. A genetically encoded fluorescent temperature sensor derived from the photoactive Orange Carotenoid Protein. Sci. Rep. 2019;9(1):8937.
11. Britton G., Helliwell J.R. Carotenoid-Protein Interactions. Carotenoids. Eds. G. Britton, S. Liaaen-Jensen, and H. Pfander. Basel: Birkhäuser Basel; 2008:99–118.
12. Berman H.M. The Protein data bank. Nucleic Acids Res. 2000;28(1):235–242. 13. Shen S., Kai B., Ruan J., Torin Huzil J., Carpenter E., Tuszynski J.A. Probabilistic analysis of the frequencies of amino acid pairs within characterized protein sequences. Phys. A: Stat. Mech. Appl. 2006;370(2):651–662.
13. Elnaggar A., Heinzinger M., Dallago C., Rehawi G., Wang Y., Jones L., Gibbs T., Feher T., Angerer C., Steinegger M., Bhowmik D., Rost B. ProtTrans: Toward understanding the language of life through self-supervised learning. IEEE Trans. Pattern Anal. Mach. Intell. 2022;44(10):7112–7127.
14. The UniProt Consortium, Bateman A., Martin M.J., et al. UniProt: the Universal Protein Knowledgebase in 2025. Nucleic Acids Res. 2025;53(D1):D609–D617.
15. Li W., Jaroszewski L., Godzik A. Clustering of highly homologous sequences to reduce the size of large protein databases. Bioinformatics. 2001;17(3):282–283.
16. Teufel F., Gíslason M.H., Almagro Armenteros J.J., Johansen A.R., Winther O., Nielsen H. GraphPart: homology partitioning for biological sequence analysis. NAR Genom. Bioinform. 2023;5(4):lqad088.
17. Steinegger M., Söding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat. Biotechnol. 2017;35(11):1026–1028.
18. Dorogush A.V., Ershov V., Gulin A. CatBoost: gradient boosting with categorical features support [Электронный ресурс]. arXiv. 2018. URL: https://arxiv.org/abs/1810.11363 (дата обращения: 06.07.2025).
19. Shahidi F., Dissanayaka C.S. Binding of carotenoids to proteins: a review. J. Food Bioact. 2023;13–28.
20. Bandara S., Ramkumar S., Imanishi S., Thomas L.D., Sawant O.B., Imanishi Y., Von Lintig J. Aster proteins mediate carotenoid transport in mammalian cells. Proc. Natl. Acad. Sci. U.S.A. 2022;119(15):e2200068119.
21. Egorkin N.A., Aleksin A.M., Sedlov I.A., Zhiganov N.I., Bodunova D.V., Varfolomeeva L.A., Slonimskiy Y.B., Ziganshin R.H., Popov V.O., Boyko K.M., Vassilevski A.A., Maksimov E.G., Sluchanko N.N. A green dichromophoric protein enabling foliage mimicry in arthropods. Proc. Natl. Acad. Sci. U.S.A. 2025;122(23):e2502567122.
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For citations:
Surkov M.M., Litovets A.Yu., Mamchur A.A., Stanishneva-Konovalova T.B., Yaroshevich I.A. Structural features of carotenoid-binding proteins. Vestnik Moskovskogo universiteta. Seriya 16. Biologiya. 2025;80(3S):87–95. (In Russ.) https://doi.org/10.55959/MSU0137-0952-16-80-3S-13


























