Advances in molecular biology and computer science may soon lead to a three-dimensional computer model of a cell, heralding a new era for biological research, medical science, and human and animal health, according to the authors of a paper recently published in the Journal of Molecular Biology.
“Cells are the foundation of life,” said Ilya Vakser, professor of computational biology and molecular biosciences and director of the Center for Computational Biology at the University of Kansas, one of the paper’s co-authors. “Recently, there has been tremendous progress in biomolecular modeling and advances at understanding life at the molecular level.
“Now, the focus is shifting to larger systems — up to the level of the entire cell. We’re trying to capture this emerging milestone development in computational structural biology, which is the tectonic shift from modeling individual biomolecular processes to modeling the entire cell.”
The study surveys a range of methodologies for simulating a whole 3-D cell, including studies of biological networks, automated construction of 3-D cell models with experimental data, modeling of protein complexes, prediction of protein interactions, thermodynamic and kinetic effects of crowding cellular membrane modeling, and modeling of chromosomes.
“There are two major benefits,” Vakser said. “One is our fundamental understanding of how a cell works. You can’t claim you understand a phenomenon if you can’t model it. So this gives us insight into basic fundamentals of life at the scale of an entire cell.
“On the practical side, it will give us an improved grasp of the underlying mechanisms of diseases and also the ability to understand mechanisms of drug action, which will be a tremendous boost to our efforts at drug design. It will help us create better drug candidates, which will potentially shorten the path to new drugs.”
As an example, he said a working 3-D molecular cell model could help to replace or augment phases of time-consuming and expensive drug development protocols required today to bring drug therapies from the scientist’s bench to the marketplace.
The paper’s other co-authors are Wonpil Im of Lehigh University, Jie Liang of the University of Illinois at Chicago, Sandor Vajda of Boston University, Arthur Olson of The Scripps Research Institute, and Huan-Xiang Zhou of Florida State University.
Abstract of Challenges in structural approaches to cell modeling
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.
The article originally appeared at Kurzweil.net
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