AlphaFold1 has revolutionized protein structure prediction by using AI and deep learning to achieve high accuracy in predicting protein structures. Its ability to predict the 3D structure of proteins with significant accuracy has been a major advancement in the field of structural biology. However, AlphaFold has limitations, particularly in predicting ligand binding sites and handling protein variants with modified sequences. Consequently, many researchers are currently working on developing plugins and integrations to expand its functionality^2,3,4.

In our modeling methodology, although more traditional, I-TASSER excels in predicting ligand binding and active site residues, offering confidence scores (C-SCORES) that help gauge the reliability of these predictions. YASARA with FoldX is essential for calculating protein stability, providing insights into structural integrity and functional efficiency under various conditions. PyMOL enables detailed visualization and analysis of the predicted structures, facilitating a thorough understanding of molecular architecture and potential functional sites. These combined tools provide a comprehensive approach to protein modeling, essential for applications like enzyme engineering and protein display on yeast surfaces.

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References

1. Abramson J, Adler J, Dunger J, Evans R, Green T, Pritzel A, Ronneberger O, Willmore L, Ballard AJ, Bambrick J, Bodenstein SW, Evans DA, Hung CC, O'Neill M, Reiman D, Tunyasuvunakool K, Wu Z, emgulyt A, Arvaniti E, Beattie C, Bertolli O, Bridgland A, Cherepanov A, Congreve M, Cowen-Rivers AI, Cowie A, Figurnov M, Fuchs FB, Gladman H, Jain R, Khan YA, Low CMR, Perlin K, Potapenko A, Savy P, Singh S, Stecula A, Thillaisundaram A, Tong C, Yakneen S, Zhong ED, Zielinski M, idek A, Bapst V, Kohli P, Jaderberg M, Hassabis D, Jumper JM. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature. 2024 May 8. doi: 10.1038/s41586-024-07487-w. Epub ahead of print. PMID: 38718835.
2. Lai B, Xu J. Accurate protein function prediction via graph attention networks with predicted structure information. Brief Bioinform. 2022 Jan 17;23(1):bbab502. doi: 10.1093/bib/bbab502. PMID: 34882195; PMCID: PMC8898000.
3. AMBER Molecular Dynamics Package Developed by: University of California, San Francisco https://ambermd.org/
4. Rosetta Molecular Modeling Suite Developed by: University of Washington https://www.rosettacommons.org/software