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Achievements and Challenges in Computational Protein Design

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

Abstract

Computational protein design (CPD), a yet evolving field, includes computer-aided engineering for partial or full de novo designs of proteins of interest. Designs are defined by a requested structure, function, or working environment. This chapter describes the birth and maturation of the field by presenting 101 CPD examples in a chronological order emphasizing achievements and pending challenges. Integrating these aspects presents the plethora of CPD approaches with the hope of providing a “CPD 101”. These reflect on the broader structural bioinformatics and computational biophysics field and include: (1) integration of knowledge-based and energy-based methods, (2) hierarchical designated approach towards local, regional, and global motifs and the integration of high- and low-resolution design schemes that fit each such region, (3) systematic differential approaches towards different protein regions, (4) identification of key hot-spot residues and the relative effect of remote regions, (5) assessment of shape-complementarity, electrostatics and solvation effects, (6) integration of thermal plasticity and functional dynamics, (7) negative design, (8) systematic integration of experimental approaches, (9) objective cross-assessment of methods, and (10) successful ranking of potential designs. Future challenges also include dissemination of CPD software to the general use of life-sciences researchers and the emphasis of success within an in vivo milieu. CPD increases our understanding of protein structure and function and the relationships between the two along with the application of such know-how for the benefit of mankind. Applied aspects range from biological drugs, via healthier and tastier food products to nanotechnology and environmentally friendly enzymes replacing toxic chemicals utilized in the industry.

Key words

  • Computational protein design
  • Inverse folding problem
  • De novo design
  • Directed evolution
  • Rational design
  • Synthetic biology
  • Negative design
  • Enzyme design
  • Protein–protein interaction

“The abundance of substances of which animals and plants are composed of, the remarkable processes whereby they are formed and then broken down again claimed the attention of mankind, and hence from the early days they also persistently captivated the interest of chemists. … To determine the structure of the molecule the chemist proceeds in a similar way to the anatomist. By chemical actions he breaks the system down into its components and continues with this division until familiar substances emerge. Where this decomposition has taken different directions, the structure of the original system can be inferred from the decomposition products. Usually, however, the structure will only be finally elucidated by the reverse method, by building up the molecule from the decomposition products or similar substances, i.e. by what is termed synthesis. Nevertheless, the chemical enigma of Life will not be solved until organic chemistry has mastered another, even more difficult subject, the proteins, in the same way as it has mastered the carbohydrates. It is hence understandable that the organic and physiological chemists are increasingly turning their attention to it. …”

Emil Fischer, Nobel Lecture, December, 12th 1902

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Samish, I. (2017). Achievements and Challenges in Computational Protein Design. 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_2

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  • DOI: https://doi.org/10.1007/978-1-4939-6637-0_2

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