Computational Advances in Structural Biology

Sergei Grudinin graduated from the Moscow Institute of Physics and Technology (MIPT) in 2002. He did his Master's project on MD simulations of membrane proteins in Forschungzentrum Juelich, where he continued it as a Ph.D. thesis. In 2006, after the Ph.D. defense, he extended the activities to method development, and later moved to Inria Grenoble, France, in 2007 and became a permanent CNRS scientist in 2009. During the last few years, his main research interests were the development of physics-based and data-driven algorithms for structural bioinformatics. They include novel methods for protein-protein and protein-ligand docking, including those accelerated with the Fast Fourier Transform; algorithms to study and predict symmetrical systems; algorithms to describe molecular flexibility; methods for integrative structural biology, e.g., those related to SAXS, SANS, and X-links measurements; applications of convex optimization to protein structure prediction; development of deep convolutional neural networks for structural bioinformatics; and graph- and tessellation-based geometric learning approaches.