HLA-DRB1 ALLELLARINI STRUKTUR VA FUNKSIONAL FAOLLIGINI BAHOLASHDA BIOINFORMASION YONDOSHUVLAR AHAMIYATI
Keywords:
HLA-DRB1, bioinformatika, molekulyar modeling, immunogenlik, polimorfizm, T-hujayra epitoplari, struktura-funksional tahlil, allelik tafovutAbstract
Insonning immun javobini tartibga solishda HLA-DRB1 genining roli beqiyosdir. Uning turli allellari immun tizimning antigenlarni tanib olishiga sezilarli darajada ta’sir ko‘rsatadi. Mazkur maqolada HLA-DRB1 genining struktur va funksional xususiyatlarini baholashda bioinformatik vositalarning o‘rni yoritiladi. Molekulyar modeling, SNP analiz, T-hujayra epitoplarini bashorat qilish kabi yondoshuvlar orqali ushbu genning immunologik ahamiyati va klinik qo‘llanilishi bo‘yicha tahlillar keltirilgan. Bu metodlar personalizatsiyalashgan tibbiyotda, ayniqsa, autoimmun kasalliklar va transplantatsiya muammolarini hal qilishda dolzarbdir.
References
1. Robinson, J., Barker, D. J., Georgiou, X., Cooper, M. A., Flicek, P., & Marsh, S. G. (2020). The IPD-IMGT/HLA Database. Nucleic Acids Research, 48(D1), D948–D955. https://doi.org/10.1093/nar/gkz950
2. Nguyen, A., David, J. K., Maden, S. K., Wood, M. A., Weeder, B. R., Nellore, A., & Thompson, R. F. (2020). Human Leukocyte Antigen (HLA) Susceptibility Map for SARS-CoV-2. Journal of Virology, 94(13), e00510-20. https://doi.org/10.1128/JVI.00510-20
3. Zhang, H., Lund, O., Nielsen, M., & Lundegaard, C. (2022). Structural insights into peptide presentation by HLA-DR molecules. Frontiers in Immunology, 13, 893561. https://doi.org/10.3389/fimmu.2022.893561
4. Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., ... & Sunyaev, S. R. (2010). A method and server for predicting damaging missense mutations. Nature Methods, 7(4), 248–249. https://doi.org/10.1038/nmeth0410-248
5. Ng, P. C., & Henikoff, S. (2003). SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Research, 31(13), 3812–3814. https://doi.org/10.1093/nar/gkg509
6. Jensen, K. K., Andreatta, M., Marcatili, P., Buus, S., Greenbaum, J. A., Yan, Z., ... & Nielsen, M. (2018). Improved methods for predicting peptide binding
7. affinity to MHC class II molecules. Immunology, 154(3), 394–406. https://doi.org/10.1111/imm.12889
8. Vita, R., Mahajan, S., Overton, J. A., Dhanda, S. K., Martini, S., Cantrell, J. R., ... & Peters, B. (2019). The Immune Epitope Database (IEDB): 2018 update. Nucleic Acids Research, 47(D1), D339–D343. https://doi.org/10.1093/nar/gky1006
