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Overcoming the Key Challenges in De Novo Protein Design: Enhancing Computational Efficiency and Incorporating True Backbone Flexibility

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Mathematical Modelling of Biosystems

Part of the book series: Applied Optimization ((APOP,volume 102))

Abstract

De novo protein design is initiated with a postulated or known flexible threedimensional protein structure and aims at identifying amino acid sequences compatible with such a structure. The problem was first denoted as the “inverse folding problem” [4, 5] since protein design has intimate links to the well-known protein folding problem [6]. While the protein folding problem aims at determining the single structure for a sequence, the de novo protein design problem exhibits a high level of degeneracy; that is, a large number of sequences are always found to share a common fold, although the sequences will vary with respect to properties such as activity and stability.

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Authors and Affiliations

  1. Department of Chemical Engineering, Princeton University, Princeton, NJ, 08544-5263

    Christodoulos A. Floudas & Ho Ki Fung

  2. Department of Bioengineering, University of California, Riverside, CA, 92521

    Dimitrios Morikis

  3. Johns Hopkins University School of Medicine, Baltimore, MD, 21205

    Martin S. Taylor

  4. Department of Chemistry, University of California, Riverside, CA, 92521

    Li Zhang

Authors
  1. Christodoulos A. Floudas
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  2. Ho Ki Fung
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  3. Dimitrios Morikis
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  4. Martin S. Taylor
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  5. Li Zhang
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Editors and Affiliations

  1. Federal University of Rio de Janeiro UFRJ-COPPE-Centre of Technology, 21.941-972-P.O. Box 68.511, Rio de Janeiro-RJ, Brazil

    Rubem P. Mondaini

  2. Center for Applied Optimization, University of Florida, 303 Weil Hall, P.O.Box 116595, Gainesville, FL, 32611-6595, USA

    Panos M. Pardalos

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Floudas, C.A., Fung, H.K., Morikis, D., Taylor, M.S., Zhang, L. (2008). Overcoming the Key Challenges in De Novo Protein Design: Enhancing Computational Efficiency and Incorporating True Backbone Flexibility. In: Mondaini, R.P., Pardalos, P.M. (eds) Mathematical Modelling of Biosystems. Applied Optimization, vol 102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76784-8_4

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