Molecular dynamics simulations of large macromolecular complexes

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Highlights

  • Advances in MD and imaging enable structural determination of large complexes.

  • Large-scale MD is essential to the atomic level description of cell-scale processes.

  • MD enables the study of local and global dynamics of multi-million atom complexes.

Connecting dynamics to structural data from diverse experimental sources, molecular dynamics simulations permit the exploration of biological phenomena in unparalleled detail. Advances in simulations are moving the atomic resolution descriptions of biological systems into the million-to-billion atom regime, in which numerous cell functions reside. In this opinion, we review the progress, driven by large-scale molecular dynamics simulations, in the study of viruses, ribosomes, bioenergetic systems, and other diverse applications. These examples highlight the utility of molecular dynamics simulations in the critical task of relating atomic detail to the function of supramolecular complexes, a task that cannot be achieved by smaller-scale simulations or existing experimental approaches alone.

Introduction

The essential conundrum of modern biology, namely the question of how life emerges from myriad molecules whose behavior is governed by physical law alone, is embodied within a single cell — the quantum of life. As illustrated in Figure 1, the rise of scientific supercomputing has allowed for the study of the living cell in unparalleled detail, from the scale of the atom 1••, 2 to a whole organism 3, 4, 5 and at all levels in between [6]. In particular, the past three decades have witnessed the evolution of molecular dynamics (MD) simulations as a ‘computational microscope’ [7], which has provided a unique framework for the study of the phenomena of cell biology in atomic (or near-atomic) detail.

Now, in the era of petascale computing, high-performance MD software packages such as NAMD [8], GROMACS [9], and LAMMPS [10] are being optimized for scaling to an ever-increasing number of cores on cutting-edge computing hardware 2, 11, 10, enabling the investigation of previously unfathomable biological phenomena through the use of large-scale atomistic simulations. Moreover, the development of computational tools such as molecular dynamics flexible fitting (MDFF) 12, 13 are forging an intimate connection between experiment and theory, informing the construction of atomic-level models of large-scale, supramolecular complexes through a synthesis of multi-scale experimental data from cryo-EM, NMR spectroscopy, and X-ray crystallography. Complementary to all-atom MD simulations, the development of force fields for coarse-grained MD (CGMD) simulations continues to be a popular source of techniques which favor computational efficiency over atomic and chemical accuracy, permitting simulations on even larger time and length scales [14].

This opinion will focus on the ways in which large-scale MD simulations are having a profound impact in numerous diverse scientific endeavors. From the treatment of disease and development of drugs 15•, 16• to the fabrication of novel biomaterials [17] and creation of bio-based renewable energy sources [18], large-scale MD simulations are helping to achieve a fundamental understanding of living organisms. Taken together, the work reviewed here demonstrates the maturity of the MD apparatus as a tool to progress basic science and the investigation of the molecular makeup of life.

Section snippets

Large-scale MD simulations of viruses

Viruses are parasitic life-forms that replicate by hijacking resources present in the cells they infect. Because of their small size compared to cells (20–1500 nm scale), observation of the viral particle during different stages of the replication cycle is mostly limited to electron microscopy. Yet, virus particles are large in size for all-atom simulations (see Figure 2) and as a result most studies at the atomic level have been limited to isolated virus proteins or subfragments of a viral

Large-scale MD simulation of ribosomes

As another important pharmaceutical target, the ribosome is the most ubiquitous and complex molecular machine in living cells, responsible for decoding the genetic code into functional proteins. MD simulation has been successfully applied to ribosomal translation [48]. Here, we review the most recent advances in large simulations involving complete ribosome structures.

Simulations of the ribosome have advanced greatly in recent years. A key subject of such studies has been the process of

Large-scale MD simulations of bioenergy systems

Development of new pharmaceuticals is not the only target of large simulations, indeed, biotechnological applications related to bioenergy are also been studied by multi-million atom MD simulations. Applications range from studies of energy conversion by complex interlocking mechanisms of several proteins in photosynthetic systems, to production of biofuels out of agricultural waste.

Diverse applicability of large-scale simulations

Besides the aforementioned prominent applications to pharmaceutically relevant systems and energy conversion, MD simulations have been successfully employed to study a wide variety of large and complex systems. The scope ranges from fundamental biological processes like cell motility or essential membrane processes to biotechnological applications like biomaterial development.

Conclusion

Through the combination of state-of-the-art computing hardware and advanced software development 11, 99 a true computational microscope has emerged [7]. Molecular dynamics simulation has established itself as a reliable tool to view the structure and dynamics of large protein complexes within realistic cellular environments. While all-atom MD remains the gold standard for MD simulations, CGMD approaches present a complementary technique to probe extended time and length scales [14], applicable

Conflict of interest

None declared.

References and recommended reading

Papers of particular interest, published within the period of review, have been highlighted as:

  • • of special interest

  • •• of outstanding interest

Acknowledgements

We thank Dr Yanxin Liu for providing the figure of the RHDV virus. The authors gratefully acknowledge funding from the National Institutes of Health (NIH, 9P41GM104601, P01-GM067887, U54 GM087519), the National Science Foundation (NSF, MCB-1157615, PHY1430124), and Energy Biosciences Institute (EBI, 231 UCB BP 2014OO4J01). TR is supported by the Alexander von Humboldt Foundation.

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