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Analysis and Prediction of Protein-Protein Recognition

Betts, Matthew James; (1999) Analysis and Prediction of Protein-Protein Recognition. Doctoral thesis (Ph.D), UCL (University College London). Green open access

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Abstract

The aims of the work presented in this thesis were two-fold. Firstly, an existing protein-protein docking algorithm was re-implemented on a type of computer more available than that used originally, and its behaviour was analysed in detail. This analysis led to changes in the scoring function, a treatment of electrostatic complementarity, and side-chain truncation. The algorithm had problems with its representation of surface, but more generally it pointed to difficulties in dealing with conformational change on association. Thus such changes were the second problem studied. They were measured in thirty-nine pairs of structures of complexed and unbound proteins, averaged over interface and non-interface regions and for individual residues. The significance of the changes was evaluated by comparison with the differences seen in twelve pairs of independently solved structures of identical proteins. Just over half had some substantial overall movement. Movements involved main-chains as well as side-chains, and large changes in the interface were closely involved with complex formation, while those of exposed non-interface residues were caused by flexibility and disorder. Interface movements in enzymes were similar in extent to those of inhibitors. All eight of the complexes that had structures of both components in an unbound form available showed some significant interface movement. An algorithm that was tested on five of these complexes was seen to be successful even when some of the largest changes occurred. The situation may be different in systems other than the enzyme-inhibitors which dominate this study. Thus the general model of protein-protein recognition was found to be induced fit. However, because there is only limited conformational change in many systems, recognition can be treated as lock and key to a first approximation.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Analysis and Prediction of Protein-Protein Recognition
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Thesis digitised by ProQuest.
URI: https://discovery.ucl.ac.uk/id/eprint/10121037
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