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Structure-Based Drug Discovery

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Attention for Chapter 14: Structure-Based Drug Discovery
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Chapter title
Structure-Based Drug Discovery
Chapter number 14
Book title
Structure-Based Drug Discovery
Published in
Methods in molecular biology, January 2012
DOI 10.1007/978-1-61779-520-6_14
Pubmed ID
Book ISBNs
978-1-61779-519-0, 978-1-61779-520-6
Authors

Gary L. Gilliland, Jinquan Luo, Omid Vafa, Juan Carlos Almagro, Gilliland, Gary L., Luo, Jinquan, Vafa, Omid, Almagro, Juan Carlos

Abstract

Antibodies make up the largest, growing segment of protein therapeutics in the pharmaceutical and biotechnology industries. The development or engineering of therapeutic antibodies is based to a large extent on our knowledge of antibody structure and requires sophisticated methods that continue to evolve. In this chapter, after a review of what is known about the structure and functional properties of antibodies, the current, state-of-the-art antibody engineering methods are described. These methods include antibody humanization, antigen-affinity optimization, Fc engineering for modulated effector function and extended half-life, and engineering for improved stability and biophysical properties. X-ray crystallographic structures of antibody fragments and their complexes can play a critical role in guiding and, in some cases, accelerating these processes. These approaches represent guidelines for developing antibody therapeutics with the desired affinity, effector function, and biophysical properties.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 38 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 31%
Student > Master 4 10%
Student > Bachelor 4 10%
Other 3 8%
Student > Ph. D. Student 3 8%
Other 7 18%
Unknown 6 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 31%
Biochemistry, Genetics and Molecular Biology 10 26%
Chemical Engineering 2 5%
Computer Science 2 5%
Medicine and Dentistry 2 5%
Other 3 8%
Unknown 8 21%