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Docta Complutense
Article . 2010
Data sources: Docta Complutense
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Trends in Biotechnology
Article . 2010 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Multivalent antibodies: when design surpasses evolution

Authors: Cuesta Martínez, Ángel; Sainz-Pastor, Noelia; Bonet, Jaume; Oliva, Baldomero; Álvarez-Vallina, Luis;

Multivalent antibodies: when design surpasses evolution

Abstract

Evolutionary pressure has selected antibodies as key immune molecules acting against foreign pathogens. The development of monoclonal antibody technology has allowed their widespread use in research, real-time diagnosis and treatment of multiple diseases, including cancer. However, compared with hematologic malignancies, solid tumors have often proven to be relatively resistant to antibody-based therapies. In an attempt to improve the tumor-targeting efficacy of antibodies, new formats with modified, multivalent properties have been generated. Initially, these formats imitated the structure of native IgG, creating mostly monospecific, bivalent antibodies. Recently, novel trivalent antibodies have been developed to maximize tumor targeting capabilities through enhanced biodistribution and functional affinity. We review recent advances in the engineering of multivalent antibodies and further discuss their promise as agents for in vivo diagnostics and therapy.

Country
Spain
Keywords

612.017, 24 Ciencias de la Vida, Protein Engineering, Antibodies, Recombinant Proteins, Drug Delivery Systems, Ciencias Biomédicas, Neoplasms, Directed Molecular Evolution, Protein Multimerization

  • BIP!
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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    176
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
176
Top 1%
Top 10%
Top 1%
Related to Research communities
Cancer Research
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