Year: 2021
Type: editorial
Abstract: Experiments and Simulations: A Pas de Deux to Unravel Biological FunctionUnderstanding the molecular mechanisms used by biological systems to perform their functions is often essential to rationally target associated diseases.In many cases, the determination of the threedimensional structure of these systems provides precious insights.However, it is more often the interplay between structural and dynamical properties that determines the behavior of complex systems (Henzler-Wildman and Kern, 2007;Orozco, 2014).While both experimental and computational methods are invaluable tools to study protein structure and dynamics, limitations in each individual technique can hamper their predictive capabilities (Schneidman-Duhovny et al., 2014).On one hand, determining structural models solely from experimental data is challenging as these data often come from time and ensemble-averaged measurements over conformationally heterogeneous states, provide sparse and sometimes ambiguous information, and are always subject to random and systematic errors.On the other hand, structural models determined by computational approaches such as protein structure prediction methods and/or molecular dynamics (MD) are limited by the inaccuracies of the force fields used as well as by the challenge of exhaustively sampling the conformational landscape of complex systems (Bonomi et al., 2017).Combining experiments and simulations is therefore a successful strategy to overcome the limitations of the individual approaches and to accurately characterize the behavior of biological systems (Bottaro and Lindorff-Larsen, 2018;Rout and Sali, 2019).The goal of this Research Topic is to present some representative examples of synergistic use of experimental and computational techniques aimed at accurately characterizing the structure, dynamics, and ultimately function of biological systems.This Research Topic of 14 articles explores different areas of experimental-computational integration: the use of computational approaches to assist the interpretation of existing experimental data or to predict the outcome of new measurements, the experimental validation of computational predictions, and the incorporation of experimental data to drive and/or refine molecular simulations.A wide spatial spectrum of systems will be covered, encompassing ordered and disordered peptides and proteins, small-molecules interacting with proteins, protein complexes, nucleic acids, and entire cells.The integration of molecular simulations with different types of experimental data will be illustrated, including cryo-electron microscopy (cryo-EM) and tomography, super-resolution microscopy, Nuclear Magnetic Resonance (NMR) spectroscopy, biochemical, and Small Angle X-ray Scattering (SAXS) data.
Institutions: Leibniz Institute of Virology (LIV), University Medical Center Hamburg-Eppendorf, Centre for Structural Systems Biology, King's College London, University College London, Washington University in St. Louis, Centre National de la Recherche Scientifique, Institut Pasteur, Biologie Moléculaire Structurale et Processus Infectieux
Language: French
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,950
OpenAlex ID: W3215499439