At present, structural biology of biopolymers has made substantial progress on the way to understanding the spatial structure of proteins, predicting their functions, interactions between proteins and small molecules, and cellular localization. The development of such basic instruments of structural biology as X-ray crystallography and nuclear magnetic resonance and the exponential growth in the number of recognized protein structures accumulated in the Protein Data Bank has led to new methods of mathematical modeling for both the three-dimensional structures themselves and their specific properties, in particular, conformational motion and function and interaction predictions.
The ability to change conformations is essential for proteins. Studying protein molecule dynamics in time can help one answer questions regarding the order in which protein conformations follow each other, regarding molecular motion trajectories across stable states and therefore regarding their functions.
It is known that many protein functions are actually implemented in motion, and relations between protein dynamics and function have been studied for a long time. Obviously, this is due to the fact that during such conformational motion different active centers (hot spots) may become exposed at the molecular surface. If we suppose that a protein molecule has several active centers responsible for interaction with different substances, which has already been shown for intrinsically disordered proteins, then modeling the motion of these proteins may give us the key to predicting their functions. Functional properties of such proteins with hidden or temporarily closed active centers may remain unclear if the structures are static and only show up in conformational motion modeling. This is extremely important for both theoretical metabolomic and signaling studies and applied drug design, as a way to predict, for instance, side effects of new active substances. This, in turn, may help us understand how proteins behave and search for the regulators of their functions; these regulators may be crucial for safe correction of various pathological processes.
Thus, to a large extent, the progress in understanding protein functions is due to new methods of modeling their conformational motion.
The aim of this special issue is to foster state-of-the-art research in the area of structural bioniformatics of proteins. This special issue focuses on advances in computational prediction of structure, motion or function of proteins. It will also serve as a landmark source for structural computational biology and its applications.