4.6 Review Book Chapter

Theoretical and Computational Protein Design

Journal

ANNUAL REVIEW OF PHYSICAL CHEMISTRY, VOL 62
Volume 62, Issue -, Pages 129-149

Publisher

ANNUAL REVIEWS
DOI: 10.1146/annurev-physchem-032210-103509

Keywords

de novo protein design; energy landscape theory; negative design; probabilistic protein design; artificial enzymes; nonbiological cofactors; membrane proteins

Funding

  1. NHLBI NIH HHS [R01 HL-085303] Funding Source: Medline
  2. NIGMS NIH HHS [P01 GM55876] Funding Source: Medline
  3. NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [R01HL085303] Funding Source: NIH RePORTER
  4. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [P01GM055876] Funding Source: NIH RePORTER

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From exponentially large numbers of possible sequences, protein design seeks to identify the properties of those that fold to predetermined structures and have targeted structural and functional properties. The interactions that confer structure and function involve intermolecular forces and large numbers of interacting amino acids. As a result, the identification of sequences can be subtle and complex. Sophisticated methods for characterizing sequences consistent with a particular structure have been developed, assisting the design of novel proteins. Developments in such computational protein design are discussed, along with recent accomplishments, ranging from the redesign of existing proteins to the design of new functionalities and nonbiological applications.

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