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- W22376704 abstract "Macromolecular interactions play a key role in all life processes. The constructionand annotation of protein interaction networks is pivotal for theunderstanding of these processes, and how their perturbation leads to disease.However the extent of the human interactome and the limitations ofthe experimental techniques which can be brought to bear upon it necessitatetheoretical approaches. Presented here are computational investigationsinto the interactions between biological macromolecules, focusing on thestructural prediction of interactions, docking, and their kinetic and thermodynamiccharacterisation via empirical functions. Firstly, the use of normalmodes in docking is investigated. Vibrational analysis of proteins are shownto indicate the motions which proteins are intrinsically disposed to undertake,and the use of this information to model flexible deformations uponprotein-protein binding is evaluated. Subsequently SwarmDock, a dockingalgorithm which models flexibility as a linear combination of normal modes,is presented and benchmarked on a wide variety of test cases. This algorithmutilises state of the art energy functions and metaheuristics to navigate thefree energy landscape. Information derived from Langevin dynamics simulationsof encounter complex formation in the crowded cytosolic environmentcan be incorporated into SwarmDock and enhances its performance.Finally, a benchmark of binding free energies derived from the literature ispresented. For this benchmark, a large number of molecular descriptors arederived. Machine learning methods are then applied to these in order toderive empirical binding free energy, association rate and dissociation ratefunctions which take account of the conformational changes which occurupon complexation." @default.
- W22376704 created "2016-06-24" @default.
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- W22376704 date "2011-10-28" @default.
- W22376704 modified "2023-09-23" @default.
- W22376704 title "Predicting and characterising protein-protein complexes" @default.
- W22376704 hasPublicationYear "2011" @default.
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