Aditi Arvi,
- Student, Faculty of Biotechnology, University of Allahabad, Allahabad, Uttar Pradesh, India
Abstract
Structural genomics has become a groundbreaking field for understanding cellular functions by revealing the three-dimensional structures of proteins and other biomolecules. This field combines advanced methods like X-ray crystallography, nuclear magnetic resonance spectroscopy, cryo-electron microscopy, and computational modeling to explore the molecular structure and behavior of cellular components. Recent advances have significantly accelerated the pace of structure determination, bolstered by high-throughput methods and artificial intelligence tools like AlphaFold. These developments have not only expanded structural databases but have also provided deep insights into the relationship between protein structure and function, advancing our understanding of biological processes at the molecular level. One of the pivotal outcomes of structural genomics is its application in elucidating the mechanisms of disease-related proteins, offering critical insights for therapeutic development. Structural studies of membrane proteins, enzyme complexes, and transcription factors have revealed novel binding sites, guiding the rational design of drugs and inhibitors. Furthermore, the integration of structural data with omics technologies has paved the way for systems biology approaches, enabling comprehensive insights into cellular networks and pathways. This review highlights the recent breakthroughs in structural genomics, focusing on innovative methods, computational approaches, and key discoveries that have enhanced our understanding of cell function. By discussing the current challenges and future directions, it underscores the potential of structural genomics in addressing fundamental biological questions and advancing precision medicine. This field’s integration with rapidly evolving computational and experimental technologies promises to unlock further insights into the complex architecture of life.
Keywords: Genomics, proteins, cell function, membrane protein, enzymes
[This article belongs to International Journal of Cell Biology and Cellular Functions ]
Aditi Arvi. Recent Developments in Structural Genomics: Uncovering Cellular Functions. International Journal of Cell Biology and Cellular Functions. 2024; 02(02):30-35.
Aditi Arvi. Recent Developments in Structural Genomics: Uncovering Cellular Functions. International Journal of Cell Biology and Cellular Functions. 2024; 02(02):30-35. Available from: https://journals.stmjournals.com/ijcbcf/article=2024/view=190878
References
1. Zhang C, Kim SH. Overview of structural genomics: from structure to function. Curr Opin Chem Biol. 2003;7(1):28–32. doi: 10.1016/s1367-5931(02)00015-7.
2. Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, et al. Highly accurate protein structure prediction with AlphaFold. Nature. 2021;596(7873):583–9.
3. Dillard RS, Hampton CM, Strauss JD, Ke Z, Altomara D, Guerrero-Ferreira RC, et al. Biological applications at the cutting edge of cryo-electron microscopy. Microsc Microanal. 2018;24(4):406–419. doi: 10.1017/S1431927618012382.
4. Vinothkumar KR, Henderson R. Structures of membrane proteins. Q Rev Biophys. 2010;43(1):65–158. doi: 10.1017/S0033583510000041
5. Kuhlman B, Bradley P. Advances in protein structure prediction and design. Nat Rev Mol Cell Biol. 2019;20(11):681–97. doi: 10.1038/s41580-019-0163-x.
6. Liddington RC. Structural basis of protein–protein interactions. Methods Mol Biol. 2015; 1278:3–22. doi: 10.1007/978-1-4939-2425-7_1.
7. Roberts G. The role of protein dynamics in allosteric effects-introduction. Biophys Rev. 2015;7(2):161–63. doi: 10.1007/s12551-015-0174-6.
8. Sali A, Blundell TL. Comparative protein modelling by satisfaction of spatial restraints. J Mol Biol. 1993;234(3):779–815. doi: 10.10 06/jmbi.1993.1626.
9. Teichmann SA, Chothia C, Gerstein M. Advances in structural genomics. Curr Opin Struct Biol. 1999;9(3):390–9. doi: 10.1016/S0959-440X(99)80053-0.
10. Forli S, Huey R, Pique ME, Sanner MF, Goodsell DS, Olson AJ. Computational protein-ligand docking and virtual drug screening with the AutoDock suite. Nat Protoc. 2016;11(5):905–19. doi: 10.1038/nprot.2016.051.
11. Forouhar F, Kuzin A, Seetharaman J, Lee I, Zhou W, Abashidze M, et al. Functional insights from structural genomics. J Struct Funct Genomics. 2007;8(2–3):37–44. doi: 10.1007/s10969-007-9018-3.
12. Smyth MS, Martin JH. X-ray crystallography. Mol Pathol. 2000;53(1):8–14. doi: 10.1136/mp.53.1.8.
13. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, et al. The protein data bank. Nucleic Acids Res. 2000;28(1):235–42. doi: 10.1093/nar/28.1.235.
14. Zhu KF, Yuan C, Du YM, Sun KL, Zhang XK, Vogel H, et al. Applications and prospects of cryo-EM in drug discovery. Mil Med Res. 2023;10(1):10. doi: 10.1186/s40779-023-00446-y.
15. Dobson CM. The structural basis of protein folding and its links with human disease. Philos Trans R Soc Lond B Biol Sci. 2001;356(1406):133–45. doi: 10.1098/rstb.2000.0758.
16. Moore JB, Weeks ME. Proteomics and systems biology: current and future applications in the nutritional sciences. Adv Nutr. 2011;2(4):355–64. doi: 10.3945/an.111.000554.
17. Gomes PSFC, Gomes DEB, Bernardi RC. Protein structure prediction in the era of AI: challenges and limitations when applying to in silico force spectroscopy. Front Bioinform. 2022;2:983306. doi: 10.3389/fbinf.2022.983306.
18. Szymański P, Markowicz M, Mikiciuk-Olasik E. Adaptation of high-throughput screening in drug discovery-toxicological screening tests. Int J Mol Sci. 2012;13(1):427–52. doi: 10.3390/ijms13010427.
| Volume | 02 |
| Issue | 02 |
| Received | 03/11/2024 |
| Accepted | 05/12/2024 |
| Published | 26/12/2024 |
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