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Journal of Molecular Evolution

, Volume 43, Issue 6, pp 678–684 | Cite as

Antibody-antigen recognition: A canonical structure paradigm

  • Francisco Lara-Ochoa
  • Juan C. Almagro
  • Enrique Vargas-Madrazo
  • Michael Conrad
Articles

Abstract

The antibodies of known three-dimensional structure exhibit a definite number of conformations (canonical structures) for five of six hypervariable loops. In the present study it was found that approximately 85% of the immunoglobulin sequences analyzed fall into a small number of canonical structure combinations, representing only 3% of the total possible. These structures were classified into six distinct groups, depending on the type of antigen with which they interact.

Within each loop, the positions responsible for maintaining these canonical structures show a use frequency of amino acids that fits an inverse power law, whereas the use frequency of the amino acids responsible for the detailed antigenic specificity follows an exponential distribution. We propose an evolutionary interpretation that connects these data, using the fact that the inverse power law is generated by statistical processes of the type that yield a wealth curve and the fact that expoential distribution is generated by processes that are not biased by past history.

Key words

Canonical structures Antigen-antibody recognition Amino acid frequency analysis Immunoglobulin evolution Adaptive landscape 

Abbreviations

Igs

immunoglobulins

H1, H2, H3

first, second and third hypervariable loop of the heavy chain

L1, L2, L3

first, second, and third hypervariable loop of the light chain

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Copyright information

© Springer-Verlag New York Inc. 1996

Authors and Affiliations

  • Francisco Lara-Ochoa
    • 1
  • Juan C. Almagro
    • 1
  • Enrique Vargas-Madrazo
    • 2
  • Michael Conrad
    • 3
  1. 1.Instituto de Quimica, UNAM, Circuito ExteriorCiudad UniversitariaMexico, D.F.
  2. 2.Instituto de Investigaciones BiologicasUniversidad Veracruzana, XalapaVereracruzMexico
  3. 3.Department of Computer ScienceWayne State UniversityDetroitUSA

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