Small GTPases are important proteins that affect many cellular processes. In my work I compare the five most important protein families of small GTPases - Arf, Rab, Ran, Ras and Rho to identify amino acids responsible for major functional differences between different protein families. To compare them, I have used the structural data from the PDB database and sequences from the UniProt database. I have discovered previously undescribed groups of amino acids specific for each protein family of small GTPases with the help of programs ConSurf and Sca5. I also carried out a pilot study of the applicability of B-factors as indicators of bond strength in the protein structure on the example of small GTPases. The first results are not entirely conclusive, but they do not exclude the applicability of B-factors as indicators of bond strength either. Powered by TCPDF (www.tcpdf.org)

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In general, this dissertation is concerned with modeling of mechanical behavior of protein molecules. In particular, we focus on coarse-grained models, which bridge the gap in time and length scale between the atomistic simulation and biological processes. The dissertation presents three independent studies involving such models. The first study is concerned with a rigorous coarse-graining method for dynamics of linear systems. In this method, as usual, the conformational space of the original atomistic system is divided into master and slave degrees of freedom. Under the assumption that the characteristic timescales of the masters are slower than those of the slaves, the method results in Langevin-type equations of motion governed by an effective potential of mean force. In addition, coarse-graining introduces hydrodynamic-like coupling among the masters as well as non-trivial inertial effects. Application of our method to the long-timescale part of the relaxation spectra of proteins shows that such dynamic coupling is essential for reproducing their relaxation rates and modes. The second study is concerned with calibration of elastic network models based on the so-called B-factors, obtained from x-ray crystallographic measurements. We show that a proper calibration procedure must account for rigid-body motion and constraints imposed by the crystalline environment on the protein. These fundamental aspects of protein dynamics in crystals are often ignored in currently used elastic network models, leading to potentially erroneous network parameters. We develop an elastic network model that properly takes rigid-body motion and crystalline constraints into account. This model reveals that B-factors are dominated by rigid-body motion rather than deformation, and therefore B-factors are poorly suited for identifying elastic properties of protein molecules. Furthermore, it turns out that B-factors for a benchmark set of three hundred and thirty protein molecules can be well approximated by assuming that the protein molecules are rigid. The third study is concerned with the polymer mediated interaction between two planar surfaces. In particular, we consider the case where a thin polymer layer bridges two parallel plates. We consider two models of monodisperse and polydisperse for the polymer layer and obtain an analytical expression for the force-distance relationship of the two plates. / text

Protein structure models obtained from X-ray crystallography are subject to radiation damage. The resulting specific alterations to protein structures can be mistaken for biological features, or may obscure actual protein mechanisms, leading to misidentification or obscuration of biological insight. The radiation chemistry behind this site-specific damage is not well understood. Radiation damage processes progress in proportion to the dose absorbed by the crystal in the diffraction experiment. Doses can be estimated using existing software, but these assume idealised experimental conditions. To simulate complex diffraction experiments, including treatment of imperfect X-ray beam profiles and inhomogeneous dose distributions, a new program, RADDOSE-3D, was developed. RADDOSE-3D can be integrated into beamline software to provide convenient, more accurate, comparative, and publishable dose figures, also facilitating informed data collection decisions. There is currently no method to automatically detect specific radiation damage in protein structure models in the absence of an 'undamaged' reference model. Radiation damage research therefore generally relies on detailed observation of a few model proteins. A new metric, B_Damage, is designed and used to identify and quantify specific radiation damage in the first large-scale statistical survey of 2,704 published protein models, which are examined for the effects of local environments on site-specific radiation damage susceptibility. A significant positive correlation between susceptibility and solvent accessibility is identified. Current understanding of radiation damage progression is mostly based on a few consecutive structure model 'snapshots' at coarse dose intervals. The low sampling rate considerably limits the ability to identify varying site susceptibility and its causes. Real space electron density data are obtained for crystals of different mutants of a RhoGDI protein with very high sequence identity, to determine sensitising and stabilising factors for radiation induced structural changes. Utilising a newly developed data collection and analysis protocol, these changes could be tracked with unprecedented time resolution.