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Modelling antibody side chain conformations using heuristic database search

D W Ritchie1, G J Kemp

  • 1Department of Computing Science, King's College, University of Aberdeen, UK. dritchie@csd.abdn.ac.uk

Proceedings. International Conference on Intelligent Systems for Molecular Biology
|January 1, 1997
PubMed
Summary

A new Prolog-based system models antibody variable domain side chain conformations using an object-oriented database and rotamer library. This approach accurately models ~60% of side chains, simplifying protein structure prediction.

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Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Protein Modeling

Background:

  • Accurate modeling of side chain conformations is crucial for predicting protein structure and function.
  • Existing side chain placement algorithms often face significant combinatorial complexity.
  • Antibody variable domains present unique challenges due to their structural diversity.

Purpose of the Study:

  • To develop a knowledge-based system for modeling side chain conformations in antibody Fv fragments.
  • To reduce the computational complexity associated with side chain placement.
  • To provide a foundation for improved protein structure modeling in antibodies and homologous families.

Main Methods:

  • Developed a Prolog-based knowledge system integrating an object-oriented antibody structure database and a side chain rotamer library.

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  • Utilized 3D clusters of side chain conformations from the database for direct incorporation into model structures.
  • Employed a heuristic cost function based on simplified side chain packing interactions to guide cluster placement.

    • Main Results:

    • The system successfully modeled approximately 60% of side chain conformations using pre-defined clusters.
    • The cluster-based approach significantly reduced combinatorial complexity compared to other algorithms.
    • The heuristic cost function, despite its simplicity, yielded accurate side chain conformation models.

    Conclusions:

    • The developed system offers an efficient and accurate method for modeling antibody Fv fragment side chain conformations.
    • This knowledge-based approach can improve the quality of protein structure models and provide a "smart start" for side chain placement.
    • The methodology is potentially applicable to other homologous protein families beyond antibodies.