Antibodies are capable of high specificity interactions with a virtually infinite range of substrates (antigens). This property has lead to a number of scientific and medical applications. The extreme variability is essentially confined to 6 hypervariable loops or 'CDRs' which constitute the antigen combining site. To make intelligent modifications to antibody affinity and specificity, by methods such as site directed mutagenesis, requires an understanding of the relationship between primary sequence and three dimensional structure of the combining site. A new 'combined algorithm' which makes use of both knowledge-based and ab initio (conformational search) modelling approaches is presented. It is routinely and reliably able to predict the conformation of all six CDRs and requires no arbitrary decisions by the user. All known protein structures are searched for loops of conformation similar to known antibody structures. These are positioned onto the conserved framework and the loops are processed into a form suitable for conformational search using the program CONGEN (Bruccoleri and Karplus, Macromolecules 18(1985),2767--2773). The midsection of each loop is deleted and reconstructed by conformational search. The conformations generated are screened using a solvent-modified potential and, from the low energy conformations, a final choice is made on the basis of structurally determining residues. The method presented provides a route by which to model modifications to known antibody structures or to model complete antibody combining sites - either in combination with other less computer intensive methods, or alone. The procedure has been tested by the individual modelling of the 6 CDR's of two antibodies, in the presence of the crystal structure of the other 5 loops. In addition, it has been applied to modelling CDR's which are difficult to model by other methods and to the construction of a complete antibody combining site. In all cases the algorithm performed very well.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:257962 |
| Date | January 1990 |
| Creators | Martin, Andrew R. |
| Contributors | Rees, A. R. |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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