Editing Molecular dynamics (section)

== Examples of applications ==
[[File:MD rotor 250K 1ns.gif|thumb|upright=1.15|Molecular dynamics simulation of a [[synthetic molecular motor]] composed of three molecules in a nanopore (outer diameter 6.7 nm) at 250 K<ref>{{cite journal | vauthors = Palma CA, Björk J, Rao F, Kühne D, Klappenberger F, Barth JV | title = Topological dynamics in supramolecular rotors | journal = Nano Letters | volume = 14 | issue = 8 | pages = 4461–4468 | date = August 2014 | pmid = 25078022 | doi = 10.1021/nl5014162 | bibcode = 2014NanoL..14.4461P }}</ref>]]{{Primary sources|section|date=January 2024}}
Molecular dynamics is used in many fields of science.
* First MD simulation of a simplified biological folding process was published in 1975. Its simulation published in Nature paved the way for the vast area of modern computational protein-folding.<ref>{{cite journal | vauthors = Levitt M, Warshel A | title = Computer simulation of protein folding | journal = Nature | volume = 253 | issue = 5494 | pages = 694–698 | date = February 1975 | pmid = 1167625 | doi = 10.1038/253694a0 | s2cid = 4211714 | bibcode = 1975Natur.253..694L }}</ref>
* First MD simulation of a biological process was published in 1976. Its simulation published in Nature paved the way for understanding protein motion as essential in function and not just accessory.<ref>{{cite journal | vauthors = Warshel A | title = Bicycle-pedal model for the first step in the vision process | journal = Nature | volume = 260 | issue = 5553 | pages = 679–683 | date = April 1976 | pmid = 1264239 | doi = 10.1038/260679a0 | s2cid = 4161081 | bibcode = 1976Natur.260..679W }}</ref>
* MD is the standard method to treat [[collision cascade]]s in the heat spike regime, i.e., the effects that energetic [[neutron]] and [[ion irradiation]] have on solids and solid surfaces.<ref name="Smith">{{cite book |editor=Smith, R. |title=Atomic & ion collisions in solids and at surfaces: theory, simulation and applications |publisher=Cambridge University Press |location=Cambridge, UK |year=1997}}{{page needed|date=April 2020}}</ref>

The following biophysical examples illustrate notable efforts to produce simulations of a systems of very large size (a complete virus) or very long simulation times (up to 1.112 milliseconds):
* MD simulation of the full ''[[satellite tobacco mosaic virus]]'' (STMV) (2006, Size: 1 million atoms, Simulation time: 50 ns, program: [[NAMD]]) This virus is a small, icosahedral plant virus that worsens the symptoms of infection by Tobacco Mosaic Virus (TMV). Molecular dynamics simulations were used to probe the mechanisms of [[Virus#Structure|viral assembly]]. The entire STMV particle consists of 60 identical copies of one protein that make up the viral [[capsid]] (coating), and a 1063 nucleotide single stranded RNA [[genome]]. One key finding is that the capsid is very unstable when there is no RNA inside. The simulation would take one 2006 desktop computer around 35 years to complete. It was thus done in many processors in parallel with continuous communication between them.<ref>{{cite web |url=http://www.ks.uiuc.edu/Research/STMV/ |title=Molecular dynamics simulation of the Satellite Tobacco Mosaic Virus (STMV) |vauthors=Freddolino P, Arkhipov A, Larson SB, McPherson A, Schulten K |work=Theoretical and Computational Biophysics Group |publisher=University of Illinois at Urbana Champaign}}</ref>
* Folding simulations of the [[Villin]] Headpiece in all-atom detail (2006, Size: 20,000 atoms; Simulation time: 500 μs= 500,000 ns, Program: [[Folding@home]]) This simulation was run in 200,000 CPU's of participating personal computers around the world. These computers had the Folding@home program installed, a large-scale distributed computing effort coordinated by [[Vijay Pande]] at Stanford University. The kinetic properties of the Villin Headpiece protein were probed by using many independent, short trajectories run by CPU's without continuous real-time communication. One method employed was the Pfold value analysis, which measures the probability of folding before unfolding of a specific starting conformation. Pfold gives information about [[Phi value analysis|transition state]] structures and an ordering of conformations along the [[Protein folding|folding pathway]]. Each trajectory in a Pfold calculation can be relatively short, but many independent trajectories are needed.<ref>{{cite journal | vauthors = Jayachandran G, Vishal V, Pande VS | title = Using massively parallel simulation and Markovian models to study protein folding: examining the dynamics of the villin headpiece | journal = The Journal of Chemical Physics | volume = 124 | issue = 16 | pages = 164902 | date = April 2006 | pmid = 16674165 | doi = 10.1063/1.2186317 | bibcode = 2006JChPh.124p4902J | doi-access = free }}</ref>
* Long continuous-trajectory simulations have been performed on [[Anton (computer)|Anton]], a massively parallel supercomputer designed and built around custom [[application-specific integrated circuit]]s (ASICs) and interconnects by [[D. E. Shaw Research]]. The longest published result of a simulation performed using Anton is a 1.112-millisecond simulation of NTL9 at 355 K; a second, independent 1.073-millisecond simulation of this configuration was also performed (and many other simulations of over 250 μs continuous chemical time).<ref name="DESRES-Science2011">{{cite journal | vauthors = Lindorff-Larsen K, Piana S, Dror RO, Shaw DE | title = How fast-folding proteins fold | journal = Science | volume = 334 | issue = 6055 | pages = 517–520 | date = October 2011 | pmid = 22034434 | doi = 10.1126/science.1208351 | s2cid = 27988268 | citeseerx = 10.1.1.1013.9290 | bibcode = 2011Sci...334..517L }}</ref> In ''How Fast-Folding Proteins Fold'', researchers Kresten Lindorff-Larsen, Stefano Piana, Ron O. Dror, and [[David E. Shaw]] discuss "the results of atomic-level molecular dynamics simulations, over periods ranging between 100 μs and 1 ms, that reveal a set of common principles underlying the folding of 12 structurally diverse proteins." Examination of these diverse long trajectories, enabled by specialized, custom hardware, allow them to conclude that "In most cases, folding follows a single dominant route in which elements of the native structure appear in an order highly correlated with their propensity to form in the unfolded state."<ref name="DESRES-Science2011" /> In a separate study, Anton was used to conduct a 1.013-millisecond simulation of the native-state dynamics of bovine pancreatic trypsin inhibitor (BPTI) at 300 K.<ref>{{cite journal | vauthors = Shaw DE, Maragakis P, Lindorff-Larsen K, Piana S, Dror RO, Eastwood MP, Bank JA, Jumper JM, Salmon JK, Shan Y, Wriggers W | title = Atomic-level characterization of the structural dynamics of proteins | journal = Science | volume = 330 | issue = 6002 | pages = 341–346 | date = October 2010 | pmid = 20947758 | doi = 10.1126/science.1187409 | s2cid = 3495023 | bibcode = 2010Sci...330..341S }}</ref>

Another important application of MD method benefits from its ability of 3-dimensional characterization and analysis of microstructural evolution at atomic scale.
* MD simulations are used in characterization of grain size evolution, for example, when describing wear and friction of nanocrystalline Al and Al(Zr) materials.<ref>{{cite journal | vauthors = Shi Y, Szlufarska I |title=Wear-induced microstructural evolution of nanocrystalline aluminum and the role of zirconium dopants |journal=Acta Materialia |date=November 2020 |volume=200 |pages=432–441 |doi=10.1016/j.actamat.2020.09.005 |bibcode=2020AcMat.200..432S |s2cid=224954349 |doi-access=free }}</ref> Dislocations evolution and grain size evolution are analyzed during the friction process in this simulation. Since MD method provided the full information of the microstructure, the grain size evolution was calculated in 3D using the Polyhedral Template Matching,<ref>{{cite journal | vauthors = Larsen PM, Schmidt S, Schiøtz J |title=Robust structural identification via polyhedral template matching |journal=Modelling and Simulation in Materials Science and Engineering |date=1 June 2016 |volume=24 |issue=5 |pages=055007 |doi=10.1088/0965-0393/24/5/055007|arxiv=1603.05143 |bibcode=2016MSMSE..24e5007M |s2cid=53980652 }}</ref> Grain Segmentation,<ref>{{cite journal | vauthors = Hoffrogge PW, Barrales-Mora LA |title=Grain-resolved kinetics and rotation during grain growth of nanocrystalline Aluminium by molecular dynamics |journal=Computational Materials Science |date=February 2017 |volume=128 |pages=207–222 |doi=10.1016/j.commatsci.2016.11.027|arxiv=1608.07615 |s2cid=118371554 }}</ref> and Graph clustering<ref>{{cite arXiv | vauthors = Bonald T, Charpentier B, Galland A, Hollocou A |title=Hierarchical Graph Clustering using Node Pair Sampling |date=22 June 2018 |class=cs.SI |eprint=1806.01664}}</ref> methods. In such simulation, MD method provided an accurate measurement of grain size. Making use of these information, the actual grain structures were extracted, measured, and presented. Compared to the traditional method of using SEM with a single 2-dimensional slice of the material, MD provides a 3-dimensional and accurate way to characterize the microstructural evolution at atomic scale.