title: Challenges in structural approaches to cell modeling.
abstract: Computational modeling is essential for structural characterization of biomolecular mechanisms across the broad spectrum of scales. Adequate understanding of biomolecular mechanisms inherently involves our ability to model them. Structural modeling of individual biomolecules and their interactions has been rapidly progressing. However, in terms of the broader picture, the focus is shifting toward larger systems, up to the level of a cell. Such modeling involves a more dynamic and realistic representation of the interactomes in vivo, in a crowded cellular environment, as well as membranes and membrane proteins, and other cellular components. Structural modeling of a cell complements computational approaches to cellular mechanisms based on differential equations, graph models, and other techniques to model biological networks, imaging data, etc. Structural modeling along with other computational and experimental approaches will provide a fundamental understanding of life at the molecular level and lead to important applications to biology and medicine. A cross section of diverse approaches presented in this review illustrates the developing shift from the structural modeling of individual molecules to that of cell biology. Studies in several related areas are covered: biological networks; automated construction of three-dimensional cell models using experimental data; modeling of protein complexes; prediction of non-specific and transient protein interactions; thermodynamic and kinetic effects of crowding; cellular membrane modeling; and modeling of chromosomes. The review presents an expert opinion on the current state-of-the-art in these various aspects of structural modeling in cellular biology, and the prospects of future developments in this emerging field.
authors.affiliation: Center for Computational Biology and Department of Molecular Biosciences, The University of Kansas, Lawrence, KS 66047, United States. Electronic address: wonpil@ku.edu.
authors.forename: Wonpil
authors.initials: W
authors.lastname: Im
authors.affiliation: Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, United States. Electronic address: jliang@uic.edu.
authors.forename: Jie
authors.initials: J
authors.lastname: Liang
authors.affiliation: Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, United States. Electronic address: olson@scripps.edu.
authors.forename: Arthur
authors.initials: A
authors.lastname: Olson
authors.affiliation: Department of Physics and Institute of Molecular Biophysics, Florida State University, Tallahassee, FL 32306, United States. Electronic address: hzhou4@fsu.edu.
authors.forename: Huan-Xiang
authors.initials: HX
authors.lastname: Zhou
authors.affiliation: Department of Biomedical Engineering, Boston University, Boston, MA 02215, United States. Electronic address: vajda@bu.edu.
authors.forename: Sandor
authors.initials: S
authors.lastname: Vajda
authors.affiliation: Center for Computational Biology and Department of Molecular Biosciences, The University of Kansas, Lawrence, KS 66047, United States. Electronic address: vakser@ku.edu.
authors.forename: Ilya A
authors.initials: IA
authors.lastname: Vakser
mesh_terms: D002462:Cell Membrane / Q000648:ultrastructure*; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D008565:Membrane Proteins / Q000378:metabolism; D008954:Models, Biological; D008958:Models, Molecular; D013816:Thermodynamics
chemical_list: D008565:Membrane Proteins
keywords: cellular membranes; chromosome modeling; macromolecular crowding; modeling of biological mesoscale; protein interactions