Berlin 2018 – scientific programme

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BP: Fachverband Biologische Physik

BP 15: Postersession III

BP 15.55: Poster

Tuesday, March 13, 2018, 14:00–16:00, Poster B

De Novo Protein Structure Prediciton by Integration of Coevolutionary Data into Replica Exchange Simulations — •Arthur Voronin¹ and Alexander Schug² — ¹Physics Department, Karlsruhe Institute of Technology, Karlsruhe, Germany — ²John von Neumann Institute for Computing, Jülich Supercomputer Centre, Jülich, Germany

Proteins perform important tasks in every living organism and are an essential part of life. Studying the structure of proteins helps to understand interactions in a biological system which can be applied to other fields, such as improving drug design. Despite incredible progress in experimental techniques, protein structure determination is arduous. Here, we suggest a complementary method of de novo protein structure prediction. Direct coupling analysis (DCA) quantifies coevolution of amino acid pairs in large sequence alignments, where high scoring pairs can be interpreted as spatially adjacent. Regular molecular dynamics (MD) simulations are computationally too costly to identify the native conformation in straightforward simulations. One reason is entrapment in one of the many local minima. By integrating DCA-derived contacts as constraints into MD simulations we smoothen the energy landscape and guide structure prediction. Additionally, any residual entrapment will be overcome by replica exchange. With this combination of techniques, it should be possible to predict the native structure de novo, i.e. without prior knowledge of structural elements, in a single simulation run. To study our methods performance we investigate small proteins using various numbers and quality of constraints.