The project deals with the development, analysis and application of coarse-grained models for the study of macromolecules of biological importance. The size and operational time scale of these molecules often prevent a direct application of more detailed calculations and descriptions, and requires the development of computationally efficient, yet physically sound, coarse grained models. Since biological macromolecules operate in an aqueous environment characterized by a huge thermal noise, these models are stochastic in nature and constitute a challenge for the field of non-equilibrium statistical physics.
The project is divided into three research objectives. In the research objective 1, I propose a rigorous study of the kinetics of motor proteins with the help of methods of statistical physics. The generalization of these theories is important for a number of problems of biological relevance, as polymer translocation and DNA/RNA packing in viruses. The characterization of equilibrium properties of polymers of arbitrary stiffness in confined geometries constitutes the main focus of the research objective 2. Analytical methods and Monte Carlo computer simulations are used to calculate probability distribution functions and entropic forces with a number of different boundary conditions. Applications are foreseen in biophysical studies of F-actin, DNA, microtubules and other protein filaments.
The research objective 3 aims at the conceivement and application of computationally efficient coarse-grained models for the investigation of protein structures of considerable size. A considerable part of the project is dedicated to the introduction of the electrostatic interaction in Go models, an essential step to address the study of the function of proteins, given their structure. The validity of the proposed models will be assessed through a comparison with more detailed calculations for a number of target biomolecules of small size.
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