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Epitope-Paratope Recognition by Knowledge Based Correlation Mapping using Hopfield Network

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Abstract:

The knowledge based correlation mapping (KBCM) is devised here as a unified measure of the information on antigen-antibody complexes available in the Protein Data Banks. This mapping is estimated from a random training sample using a Hopfield Network while representing the epitope and paratope in a complex as 3-dimensional attributed graphs. Identification of paratopes on immunoglobulins against given epitopes is carried out using pattern matching on Hopfield Network with the help of the KBCM.

Keywords: EPITOPE-PARATOPE; Epitope; Paratope; immunoglobulins; knowledge based correlation mapping (KBCM)

Document Type: Review Article

DOI: https://doi.org/10.2174/0929866013409418

Publication date: 2001-08-01

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  • Protein & Peptide Letters publishes short papers in all important aspects of protein and peptide research, including structural studies, recombinant expression, function, synthesis, enzymology, immunology, molecular modeling, drug design etc. Manuscripts must have a significant element of novelty, timeliness and urgency that merit rapid publication. Reports of crystallisation, and preliminary structure determinations of biologically important proteins are acceptable. Purely theoretical papers are also acceptable provided they provide new insight into the principles of protein/peptide structure and function.
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