Simulations Pave the Way for Exploring New Frontiers in the

Editorial pubs.acs.org/JPCL

Simulations Pave the Way for Exploring New Frontiers in the Biological Sciences

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his issue of JPC Letters presents three Perspectives, each featuring a different outlook on how computational approaches can be applied to the study of biological processes. These Perspectives reflect the wide range of computational models (coarse-grained, atomistic, or mesoscopic) and simulations methodologies (from conventional molecular dynamics to enhanced sampling metadynamics) available and the importance of a strong synergy between computation and experiment. The Perspective by Balazs and co-workers presents a stimulating review of the role of simulations in the design of artificial, biologically inspired devices (Balazs, A. C.; Bhattacharya, A.; Tripathi, A.; Shum, H. Designing Bioinspired Artificial Cilia to Regulate Particle−Surface Interactions. J. Phys. Chem. Lett. 2014, 5, 1691−1700). Their Perspective focuses on cilia, hair-like filaments capable of controlling the motion of microscopic particles.1 These organelles play vital roles in a range of organisms, from the smallest unicellular organisms (locomotion) to humans (expulsion of small particles from the respiratory tract). The mechanism of cilia action is mechanical rather than chemical, suggesting an overarching mechanism that can be harnessed in synthetic cilia.2 Using both analytical models as well as simulations in which the cilia are represented as a tethered chain of beads, immersed in a fluid evolving following the lattice Boltzmann method,3 Balazs and coworkers convincingly demonstrate that actuated artificial cilia can perform the same roles as biological cilia. A particularly important result for the design of novel artificial cilia is the observation that tuning cilia flexibility and interaction strength with particulates can lead to distinct properties. One set of parameters led to repulsion of the particles from the cilia (this feature has applications for controlling fouling in microarrays), and for another, it led to cilia-induced size separation of microparticles (a property that has applications for sorting biological cells).4 The Perspective by Loverde focuses on computational models to study membrane−solute interactions (Loverde, S. M. Molecular Simulation of the Transport of Drugs across Model Membranes. J. Phys. Chem. Lett. 2014, 5, 1659−1665). This field of research is particularly important from a biomedical perspective as these models can shed new light into the interaction of drugs with cell membranes. Loverde presents a hierarchy of models, from mean-field, to coarsegrained, to atomistic, each probing processes occurring at different time and length scales. The mean-field models can be used to study solubility and diffusion of hydrophobic or hydrophilic solutes in the membrane, as well as the effect of solute partitioning on membrane curvature.5 Coarse-grained models offer more detailed insights into the mechanism of solute−membrane interactions, on biologically relevant time and length scales.6 The challenge lies in choosing the appropriate resolution of the coarse-grained model, as well as in developing transferable coarse-grained solute parameters.7 Finally, atomistic simulations can provide information at a © 2014 American Chemical Society

resolution at times exceeding what can be achieved experimentally; however, the challenge now lies in accessing time scales that are biologically meaningful.8 Indeed, the rate of diffusion of a solute through a membrane is slow (on the order of 10−8 cm2/s), making it necessary to use enhanced sampling techniques in order to obtain free-energy profiles of solutes across membranes. The author highlights how improvements in coarse-grained and atomistic force fields and the development of efficient sampling techniques are quickly making simulations an indispensable complement to experiment for the design and characterization of novel drugs and their delivery mechanisms. Finally, Sponer and co-workers present a refreshingly honest Perspective on the current state of atomistic simulations of nucleic acids (Šponer, J.; Banás,̌ P.; Jurečka, P.; Zgarbová, M.; Kührová, P.; Havrila, M.; Krepl, M.; Stadlbauer, P.; Otyepka, M. Molecular Dynamics Simulations of Nucleic Acids. From Tetranucleotides to the Ribosome. J. Phys. Chem. Lett. 2014, 5, 1771−1782). The authors present a critical assessment of the strengths and limitations of current molecular mechanics (MM) force fields and the challenges involved in their parametrization.9 They present eye-opening examples in which MM simulations fail to reproduce experimental observations or show deviations in energy up to an order of magnitude compared to quantum mechanical calculations.10 The authors (much as Loverde did in her Perspective) also highlight the difficulties in accessing relevant time scales and the need for enhanced sampling protocols.11 The overall message of the Perspective remains nonetheless upbeat. The authors illustrate how perfect accuracy of force fields is not always required in order for simulations to provide important new insights into RNA structure and dynamics. They also point to new developments in sampling protocols and force field developments (notably polarizable force fields12) that are paving the way for simulations to rival experiments as a means to study nucleic acids. Taken together, the three Perspectives paint a bright future for an ever-increasing role of simulations in exploring new frontiers in the biological sciences.

Joan-Emma Shea*

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Department of Chemistry and Biochemistry and Department of Physics, University of California, Santa Barbara, California 93106-9510, United States

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Telephone: 805-893-5604. Notes

Views expressed in this Editorial are those of the author and not necessarily the views of the ACS. Published: May 15, 2014 1783

dx.doi.org/10.1021/jz5007934 | J. Phys. Chem. Lett. 2014, 5, 1783−1784

The Journal of Physical Chemistry Letters

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Editorial

REFERENCES

(1) Blake, J. R.; Sleigh, M. A. Mechanics of Ciliary Locomotion. Biol. Rev. 1974, 49, 85−125. (2) den Toonder, J. M. J.; Onck, P. R. Microfluidic Manipulation with Artificial/Bioinspired Cilia. Trends Biotechnol. 2013, 31, 85−91. (3) Ladd, A. J. C. Numerical Simulations of Particulate Suspensions via a Discretized Boltzmann-Equation. 1. Theoretical Foundation. J. Fluid Mech. 1994, 271, 285−309. (4) (a) Bhattacharya, A.; Buxton, G. A.; Usta, O. B.; Balazs, A. C. Propulsion and Trapping of Microparticles by Active Cilia Arrays. Langmuir 2012, 28, 3217−3226. (b) Bhattacharya, A.; Balazs, A. C. Stiffness-Modulated Motion of Soft Microscopic Particles over Active Adhesive Cilia. Soft Matter 2013, 9, 3945−3955. (c) Tripathi, A.; Shum, H.; Balazs, A. C. Fluid-Driven Motion of Passive Cilia Enables the Layer to Expel Sticky Particles. Soft Matter 2014, 10, 1416−1427. (d) Tripathi, A.; Bhattacharya, A.; Balazs, A. C. Size Selectivity in Artificial Cilia−Particle Interactions: Mimicking the Behavior of Suspension Feeders. Langmuir 2013, 29, 4616−4621. (5) (a) Parisio, G.; Stocchero, M.; Ferrarini, A. Passive Membrane Permeability: Beyond the Standard Solubility-Diffusion Model. J. Chem. Theory Comput. 2013, 9, 5236−5246. (b) Marqusee, J. A.; Dill, K. A. Solute Partitioning into Chain Molecule Interphases  Monolayers, Bilayer-Membranes, and Micelles. J. Chem. Phys. 1986, 85, 434−444. (6) (a) Pickholz, M.; Saiz, L.; Klein, M. L. Concentration Effects of Volatile Anesthetics on the Properties of Model Membranes: A Coarse-Grain Approach. Biophys. J. 2005, 88, 1524−1534. (b) Loverde, S. M.; Klein, M. L.; Discher, D. E. Nanoparticle Shape Improves Delivery: Rational Coarse Grain Molecular Dynamics (rCG-MD) of Taxol in Worm-Like PEG-PCL Micelles. Adv. Mater. 2012, 24, 3823− 3830. (7) Noid, W. G. Perspective: Coarse-Grained Models for Biomolecular Systems. J. Chem. Phys. 2013, 139, 090901. (8) Jambeck, J. P. M.; Lyubartsev, A. P. Exploring the Free Energy Landscape of Solutes Embedded in Lipid Bilayers. J. Phys. Chem. Lett. 2013, 4, 1781−1787. (9) Zgarbova, M.; Luque, F. J.; Sponer, J.; Cheatham, T. E.; Otyepka, M.; Jurecka, P. Toward Improved Description of DNA Backbone: Revisiting Epsilon and Zeta Torsion Force Field Parameters. J. Chem. Theory Comput. 2013, 9, 2339−2354. (10) (a) Mladek, A.; Banas, P.; Jurecka, P.; Otyepka, M.; Zgarbova, M.; Sponer, J. Energies and 2′-Hydroxyl Group Orientations of RNA Backbone Conformations. Benchmark CCSD(T)/CBS Database, Electronic Analysis, and Assessment of DFT Methods and MD Simulations. J. Chem. Theory Comput. 2014, 10, 463−480. (b) Sponer, J.; Mladek, A.; Spackova, N.; Cang, X. H.; Cheatham, T. E.; Grimme, S. Relative Stability of Different DNA Guanine Quadruplex Stem Topologies Derived Using Large-Scale Quantum-Chemical Computations. J. Am. Chem. Soc. 2013, 135, 9785−9796. (11) (a) Sugita, Y.; Okamoto, Y. Replica-Exchange Molecular Dynamics Method for Protein Folding. Chem. Phys. Lett. 1999, 314, 141−151. (b) Laio, A.; Parrinello, M. Escaping Free-Energy Minima. Proc. Natl. Acad. Sci. U.S.A. 2002, 99, 12562−12566. (12) Lopes, P. E. M.; Huang, J.; Shim, J.; Luo, Y.; Li, H.; Roux, B.; MacKerell, A. D. Polarizable Force Field for Peptides and Proteins Based on the Classical Drude Oscillator. J. Chem. Theory Comput. 2013, 9, 5430−5449.

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