Abstract
High accuracy protein modeling from its sequence information is an important step toward revealing the sequence–structure–function relationship of proteins and nowadays it becomes increasingly more useful for practical purposes such as in drug discovery and in protein design. We have developed a protocol for protein structure prediction that can generate highly accurate protein models in terms of backbone structure, side-chain orientation, hydrogen bonding, and binding sites of ligands. To obtain accurate protein models, we have combined a powerful global optimization method with traditional homology modeling procedures such as multiple sequence alignment, chain building, and side-chain remodeling. We have built a series of specific score functions for these steps, and optimized them by utilizing conformational space annealing, which is one of the most successful combinatorial optimization algorithms currently available.
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Acknowledgments
This work was supported by Creative Research Initiatives (Center for in silico Protein Science, 2009-0063610) of MEST/KOSEF. We thank KIAS Center for Advanced Computation for providing computing resources.
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Joo, K., Lee, J., Lee, J. (2011). Methods for Accurate Homology Modeling by Global Optimization. In: Orry, A., Abagyan, R. (eds) Homology Modeling. Methods in Molecular Biology, vol 857. Humana Press. https://doi.org/10.1007/978-1-61779-588-6_7
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DOI: https://doi.org/10.1007/978-1-61779-588-6_7
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