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Multistate Computational Protein Design with Backbone Ensembles

Part of the Methods in Molecular Biology book series (MIMB,volume 1529)

Abstract

The ability of computational protein design (CPD) to identify protein sequences possessing desired characteristics in vast sequence spaces makes it a highly valuable tool in the protein engineering toolbox. CPD calculations are typically performed using a single-state design (SSD) approach in which amino-acid sequences are optimized on a single protein structure. Although SSD has been successfully applied to the design of numerous protein functions and folds, the approach can lead to the incorrect rejection of desirable sequences because of the combined use of a fixed protein backbone template and a set of rigid rotamers. This fixed backbone approximation can be addressed by using multistate design (MSD) with backbone ensembles. MSD improves the quality of predicted sequences by using ensembles approximating conformational flexibility as input templates instead of a single fixed protein structure. In this chapter, we present a step-by-step guide to the implementation and analysis of MSD calculations with backbone ensembles. Specifically, we describe ensemble generation with the PertMin protocol, execution of MSD calculations for recapitulation of Streptococcal protein G domain β1 mutant stability, and analysis of computational predictions by sequence binning. Furthermore, we provide a comparison between MSD and SSD calculation results and discuss the benefits of multistate approaches to CPD.

Key words

  • Single-state design
  • Multistate analysis
  • Multistate design
  • PertMin
  • Protein stability prediction
  • Receiver operating characteristic
  • Protein G

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Correspondence to Roberto A. Chica .

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Davey, J.A., Chica, R.A. (2017). Multistate Computational Protein Design with Backbone Ensembles. In: Samish, I. (eds) Computational Protein Design. Methods in Molecular Biology, vol 1529. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6637-0_7

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  • DOI: https://doi.org/10.1007/978-1-4939-6637-0_7

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