Parallelizable Strategy for the Estimation of the 3D Structure of Biological Macromolecules

Abstract

We present a parallelizzable, multilevel algorithm for the study of three-dimensional structure of biological macromolecules, applied to two fundamental topics: the 3D reconstruction of Chromatin and the elaboration of motion of proteins. For Chromatin, starting from contact data obtained through Chromosome Conformation Capture techniques, our method first subdivides the data matrix in biologically relevant blocks, and then treats them separately, at several levels, depending on the initial data resolution. The result is a family of configurations for the entire fiber, each one compatible with both experimental data and prior knowledge about specific genomes. For Proteins, the method is conceived as a solution for the problem of identifying motion and alternative conformations to the deposited structures. The algorithm, using quaternions, processes the main chain and the aminoacid side chian independently; it then exploits a Monte Carlo method for selection of biologically acceptable conformations, based on energy evaluation, and finally returns a family of conformations and of trajectories at single atom resolution.