Use this URL to cite or link to this record in EThOS:
Title: The application of multiobjective optimisation to protein-ligand docking
Author: Mardikian, Sally
ISNI:       0000 0001 3618 8357
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2008
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Restricted access.
Access from Institution:
Despite the intense efforts that have been devoted to the development of scoring functions for protein-ligand docking, they are still limited in their ability to identify the correct binding pose of a ligand within a protein binding site. A deeper understanding of the intricacies of scoring functions is therefore essential in order to develop these effectively. The aim of the work described in this thesis is to analyse the individual interaction energy types which form the individual components of a force field-based scoring function. To do this, & protein-ligand docking algorithm that is based on multiobjective optimisation has been developed. Multiobjective optimisation allows for the optimisation of several objectives simultaneously and this has been applied to the individual interaction energy types of the GRID scoring function. Traditionally these interaction energy types are summed together and the total energy is used to guide the search. By using individual energy types during optimisation, their roles can be better understood. The interaction energy types that have been used here are the electrostatic and hydrogen bond interactions combined, and van der Waals interactions. The algorithm is first tested on two datasets containing twenty complexes. The results show that the different interaction energy types have varying influences when it comes to successfully docking certain complexes, and that it is important to fmd the right balance of interaction energy types so as to find correct solutions. Ofthe twenty complexes, the algorithm found correct solutions for fifteen. To improve the performance of the algorithm, a few enhancements were introduced. This includes a simplex minimisation process with a Lamarckian element. The algorithm was retested on the twenty complexes, and the newer version was found to outperform the original version, finding correct solutions for seventeen of the twenty complexes. To extensively study the capabilities of the algorithm, it was tested on varied datasets, including the FlexX dataset. The algoritlun's performance was also compared to a single-objective docking tool, Q-fit. The comparison betw~en the multiobjective and single-objective methodologies revealed that single-objective methods can sometimes fail at finding correct docked solutions because they are unable to correctly balance the interaction energy types comprising a scoring function. The study also showed that a multiobjective optimisation method can reveal the reasons why a given docking algorithm may fail at fmding a correct solution. Finally, the algorithm was extended to incorporate desolvation energy as a third objective. Though these results are preliminary, they revealed some interesting relationships between the different objectives.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available