a simulation for each dipeptide ( in their zwitterionic form ) was set up using the gromacs molecular dynamics package .
a cubic box with 300 dipeptides , placed randomly with a minimum distance of 3  between them , was solvated in standard martini cg water ( four water molecules per bead ) to a final concentration of 0.4 m. a berendsen thermostat and barostat were used to keep the temperature at 303 k and pressure at 1 bar , respectively .
bond lengths in aromatic side chains and the backbone  side - chain bonds in i , v , and y were constrained using the lincs algorithm . all boxes were energy minimized using the steepest descent integrator and then equilibrated for 4  10 time steps of 25 fs .
the extended ff simulation was performed in duplicate , and reported tube sizes were averaged over 10 different positions in either simulation . for all experimentally studied dipeptides , a similar simulation over 40  10 steps was performed to study the effect of a longer simulation on the ap .
the total screening simulation time equates to 100 ns , but because of the smoothness of the cg potentials , this roughly equates to an effective 400 ns of atomistic simulation time . throughout this letter
, all times refer to the simulation time speeded up by this factor of 4 .
the size of our systems , the time scales required , and the number of systems that are assessed in a virtual screen excludes the possibility of performing these md simulations using all - atom models on modest computing resources .
the complete , 400 ns simulation for a single dipeptide system described above can be carried out in ca
. 4 h on a four - core 2.6 ghz opteron compute node . more details of the simulation can be found in the supporting information .
 several short peptide sequences are known to self - assemble into supramolecular nanostructures with interesting properties . in this study , 
 coarse - grained molecular dynamics is employed to rapidly screen all 400 dipeptide combinations and predict their ability to aggregate as a potential precursor to their self - assembly . 
 the simulation protocol and scoring method proposed allows a rapid determination of whether a given peptide sequence is likely to aggregate ( an indicator for the ability to self - assemble ) under aqueous conditions . 
 systems that show strong aggregation tendencies in the initial screening are selected for longer simulations , which result in good agreement with the known self - assembly or aggregation of dipeptides reported in the literature . 
 our extended simulations of the diphenylalanine system show that the coarse - grain model is able to reproduce salient features of nanoscale systems and provide insight into the self - assembly process for this system . 
Computational Methods