Preface

Proteins possess a broad range of structural and functional properties that are unmatched by any other class of biological molecules. Amazingly, nature has arranged simple atoms and chemical bonds in such a way to facilitate complex biological processes like molecular recognition and catalysis. Nature has also inspired many scientists and engineers to design and create their own customized proteins. These engineered proteins can serve as novel molecular tools for scientific, medical, and industrial applications, thus addressing many needs unmet by naturally occurring proteins.

Protein engineering requires identification of particular amino acid sequences that will result in desired structural and functional properties. Despite recent advances in the field, however, protein engineering remains as much an art as it is a science. Engineering an arbitrary protein structure or function remains a formidable challenge, because the rules defining sequence-structure-function relationships are still not well understood. Even with refined quantitative models, the large degrees of freedom present in a typical protein do not easily allow identification of optimal sequences using currently available computational techniques. Furthermore, the complexity of proteins present engineering challenges whose solutions will most likely require a combination of experimental and computational approaches.

This book discusses two general strategies commonly used to engineer new proteins: diversity-oriented protein engineering and computational protein design. Diversity-oriented protein engineering, or directed evolution, identifies protein variants with desired properties from a large pool of mutants. As such, its success depends on generating sufficient sequence diversity and employing sensitive high-throughput assays. Computational protein design, on the other hand, generates and screens protein sequences in silico before synthesizing them in the laboratory. This is still an unfamiliar concept to many, so an important goal of this book is to demystify the subject by describing its development and current implementations. Structure-based protein engineering similarly uses computation to facilitate the discovery of interesting protein sequences. However, computational protein design places emphasis on both engineering new, useful proteins and on testing sequence-structure relationships. In this regard, it shares a deep philosophical root with protein folding, which similarly seeks to understand the relationship between protein sequence and tertiary structure.

The book is organized into two sections. The first half of the book discusses experimental approaches to protein engineering and starts by describing several high-throughput protein engineering platforms (Chapters 1-3). This is followed by a chapter on key techniques used for diversity generation (Chapter 4). The next few chapters present examples of therapeutics, enzymes, biomaterials, and other molecules that were engineered by rational or combinatorial-based approaches (Chapter 5-8). The section finishes with a chapter on the use of unnatural amino acids in protein engineering (Chapter 9).

The second half of the book introduces computational protein design, which designs new sequences by quantitatively modeling sequence-structure relationships. Despite their unique approaches, protein engineering and design are increasingly developing a synergistic relationship. To that end, more and more experimentalists are recognizing computation as an important molecular tool for protein engineering, and vice versa. These days, it is routine for those planning a protein engineering project to first perform sequence analysis and to visualize protein structures in a molecular viewer. It is thus appropriate to start this section with a chapter on the common use of computers and informatics in protein engineering (Chapter 10). Examples of heuristic protein design are described in Chapter 11, before the core components of computational protein design are discussed in detail in Chapters 12-14. Subsequent chapters present examples of computationally designed proteins that played critical roles in advancing the use of computers in protein engineering (Chapters 15-17). The field has not yet fully matured and there are difficulties that remain to be resolved; these challenges are discussed in the last chapter of the book (Chapter 18).

Modern biology has provided a deep understanding of the molecular nature of biological processes. In particular, we now have a variety of tools that can be used to analyze and control key biological processes with molecular precision. Protein engineering and design are attempts to accomplish exactly these goals. As examples throughout the book show, certain categories of problems have attracted attention from scientists and engineers with a diverse range of technical expertise. We hope these studies will help the reader identify potential opportunities to bridge experimental protein engineering and computational protein design and will lead to exciting breakthroughs in biotechnology and medicine.

Sheldon J. Park Jennifer R. Cochran

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