The aggregation propensity and rates of aggregation were found for each of the 400 possible dipeptides in water. This was done by computationally producing each dipeptide and 400 boxes of water and inserting 300 identical dipeptides into each box (300 ALA-ALA dipeptides in one box, 300 PHE-PHE dipeptides in another box, and so on for all 400 dipeptides). The energy inside the boxes was then minimized and equilibrated in a 250 ns simulation with 2000 frames throughout each simulation. The solvent accessible surface area (SASA) was calculated for each frame to allow for the calculation of aggregation propensity values (AP scores). Using the AP scores as a function of time throughout the simulations, average rates of aggregation were also calculated. The data obtained was then analyzed to compare the AP scores and rates of each of the 400 dipeptides. This was done 6 times, producing 6 sets of data that were then analyzed for consistency throughout the 6 sets of simulations. It was determined that rate and AP score are directly correlated, meaning high AP scores result in high aggregation rates. Each set of data is shown in a heatmap and each of the six heatmaps look very similar, ultimately showing the consistency of the data.<br/>

Natural aggregation of dipeptides in water

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

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