Proteinler içindeki iletişim ağını ve ligand bağlama, mutasyon ve çeviri sonrası değişiklikler üzerindeki dinamiklerindeki değişimi inceleyen hesaplamalı bir çalışma

The thesis analyses the dynamic and structure changes in biomolecules upon ligand or protein binding, mutation and post translational modifications such as phosphorylation or methylation by using computational methods. The computational methods utilized throughout this study are biophysics based; harmonic interaction and molecular dynamics (MD)-based approaches. The entropy transfer concept is used to detect allosteric communication network in proteins in first chapter and the driver-driven relationships between residue pairs are introduced, by using Molecular Dynamics based and Gaussian Network Model based approaches. In second chapter, a special derivative of antibodies produced by camelids named as nanobodies are optimized for humans and specific design criteria and methods are introduced to optimize a given nanobody to a specific antigen. Longer simulations must be conducted in order to get reliable results from a Molecular dynamics simulation. To enhance sampling by running several short MD simulations, most important motions must be filtered out by removing the noise in the simulations by a Latent Semantic Indexing analysis. This method is used to enhance conformational sampling quality from three short MD simulations of MEK1 protein and residue fluctuations of the filtered and unfiltered trajectories are compared. In the following chapter the activation mechanism of MEK1 protein upon Raf binding and following phosphorylation are investigated. The effect of ligand binding and mutation on MEK1 dynamics are revealed and the effects of these events on MEK1 and dual phosphorylated MEK1 are compared. In the final chapter the effect of DNA methylation on methyl binding protein affinities are investigated and the effect of hydration of the binding site is explained. MeCP2 and MBD2 proteins are used to investigate these effects and the binding affinities are compared by using Steered Molecular Dynamics simulations. Biology adapted itself to computer and computational methods makes biological concepts easily testable. With the integration of mathematics, physics, statistics and computational methods the ideas will shape into hypotheses and large amount of data produced by computational methods will direct and shape experimental studies.