Side-Chain Structure Prediction Based on Dead-End Elimination: Single Split DEE-criterion Implementation and Elimination Power

  • Jan A. Spriet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2812)


The three-dimensional structure of a protein is a very fundamental piece of knowledge. Part of the problem of obtaining that knowledge is modeling the side-chain spatial positions. Dead-End Elimination (DEE) is a powerful philosophy concerning search in the abstract conformational space, meant to yield the optimal side-chain orientations, fixed on the given protein backbone. The approach permits the formulation of several DEE-criteria, which differ in quality and computational efficiency for the abstract optimization problem that is rooted in and framed by the macromolecular architectural aspects of the protein universe. The present work investigates time complexity, elimination power and optimized implementation of the recently proposed Single Split DEE- criterion for protein side-chain placement or prediction. Properly inserted in a suitable DEE-cycle, the criterion is found to follow the classic cost bound and is proven to be worthwhile. On a test set of sixty proteins, the elimination power is 17.7%, in addition to the combined pruning effect of the standard criteria. It is also found that algorithm implementation can be optimized using the efficacy – ”Magic Bullet Character”, of the side-chain residue types.


Packing Problem Conformational Space Integer Programming Problem Elimination Capacity Amino Acid Type 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Jan A. Spriet
    • 1
  1. 1.Katholieke UniversiteitKortrijkBelgium

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