Vikas Nanda Fei Xu and Daniel Hsieh Contents

Designing Thermostable Proteins 328

Stabilizing the Native State 328

Destabilizing Unfolded and Misfolded States 330

Engineering Substrate Binding Properties 332

Designing Function 335

Catalysis 335

Fluorescence 336

Solubility 336

Conclusion 337

References 337

Proteins are malleable molecules and tolerate many mutations with marginal effects on structure and function. A limited number of three-dimensional folds are recycled repeatedly for different functions. This malleability results from surviving hundreds of millions of years of mutation and recombination. Natural proteins thus provide a gold mine of starting materials for those interested in modifying proteins to suit their needs. Unlike nature, however, protein engineers try to evolve molecules on a much shorter time scale. To that end, combinatorial gene synthesis and in vitro evolution methods (Stemmer 1994; Giver et al. 1998) have been developed to accelerate the mutation and selection process with impressive results. Rational protein engineering is another approach that applies our knowledge of intermolecular forces and protein structure toward the identification of mutations that confer the desired properties on a target protein (Marshall et al. 2003). Computation automates much of the design process, allowing larger, more complex targets to be rationally engineered.

This chapter reviews the recent progress in computational protein engineering, with a focus on how knowledge of protein folding and function is applied to modulate the "intrinsic" properties of proteins (e.g., stability, substrate binding, and catalysis). Each of these properties presents unique technical and conceptual challenges. Some may be overcome simply by brute force. For example, as computational costs become cheaper, larger computational tasks become accessible to average protein designers. Other challenges require the development of more sophisticated computational methods or efficient optimization algorithms. We will see several examples of both throughout this chapter. The field of computational protein design continues to advance, and the examples presented here represent only a snapshot of what is possible. Computational methods combined with in vitro evolution will give protein engineers increasing control over the design process.

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