The article begins with a dramatic introduction:
Recent dramatic methodological advances have made all-atom molecular dynamics (MD) simulations an ever more useful partner to experiment because MD simulations capture the atomic resolution behavior of biological systems on timescales spanning 12 orders of magnitude, covering a spatiotemporal domain where experimental characterization is often difficult if not impossible.The motivation for this:
Computational models, especially those arising from MD simulations, are useful because they can provide crucial mechanistic insights that may be difficult or impossible to garner otherwise[.]This is further explained in the introduction:
An all-atom MD simulation typically comprises thousands to millions of individual atoms representing, for example, all the atoms of a membrane protein and of the surrounding lipid bilayer and water bath. The simulation progresses in a series of short, discrete time steps; the force on each atom is computed at each time step, and the position and velocity of each atom are then updated according to Newton’s laws of motion. Each atom in the system under study is thus followed intimately: its position in space, relative to all the other atoms, is known at all times during the simulation. This exquisite spatial resolution is accompanied by the unique ability to observe atomic motion over an extremely broad range of timescales—12 orders of magnitude - from about 1 femtosecond (10^-15 s), less than the time it takes for a chemical bond to vibrate, to >1 ms (10^-3 s), the time it takes for some proteins to fold, for a substrate to be actively transported across a membrane, or for an action potential to be initiated by the opening of voltage-gated sodium channels. MD simulations thus allow access to a spatiotemporal domain that is difficult to probe experimentally.What is this for? The authors write:
Simulations can be particularly valuable for membrane proteins, for which experimental characterization of structural dynamics tends to be challenging. [...] A wide variety of physiological processes are amenable to study at the atomic level by MD simulation. Examples relevant to membrane protein function include the active transport of solutes across bilayers by antiporters and symporters; the passive transport of water, ions, and other solutes by structurally diverse channels; the interconversion of transmembrane electrochemical gradients and chemical potential energy by pumps such as the F1F0-ATPase and the Na+/K+-ATPase; the transmission of extracellular stimuli to the cell interior by G protein–coupled receptors (GPCRs) and tyrosine kinase receptors; and the structural coupling of cells and organelles to one another by integrins and membrane curvature modulators.The paper further presents several case studies, such as "Permeation through a water channel: aquaporin 0 (AQP0)", "Reconciling discordant experimental results: ß2-adrenergic receptor (ß2AR)" and "Permeation and gating of an ion channel: Kv1.2".
As "major strengths and limitations of MD as a technique for molecular physiology", the authors primarily suggest "accessible timescales" ("MD simulations have historically been most powerful for simulating motions that take place on submicrosecond timescales"). A further paragraph in this chapter deals with "accuracy and errors". Also, "system size" is to be considered when designing an MD simulation study, and:
Classical MD simulations treat covalent bonds as unchanging. To simulate chemical reactions, one must use alternative techniques such as quantum mechanics/molecular mechanics simulations, in which the bulk of the system is simulated as in classical MD, but a small part is evaluated using more computationally intensive quantum mechanical approaches.