Detail

Dataset for Discovery of Self-Assembling π-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation

Shmilovich, Kirill; Mansbach, Rachael A.; Sidky, Hythem; Dunne, Olivia; Panda, Sayak Subhra; Tovar, John D.; Ferguson, Andrew L.

Organizations

MDF Open

Year

2019

Source Name

ferguson_peptide

License

CC-BY 4.0

Contacts

Andrew Ferguson <andrewferguson@uchicago.edu> Kirill Shmilovich <kirills@uchicago.edu>

DOI

10.18126/xqiz-hzc2 View on Datacite
This dataset contains 186 molecular dynamics simulation trajectories of coarse-grained pi-conjugated peptides in the Asp-X-X-X-(oligophenylenevinylene)3-X-X-X-Asp (DXXX-OPV3-XXXD) family, where X denotes one of the 20 natural amino acids. The oligopeptide wings are constrained to be mirror-symmetric both in the identity of the amino acids and the N-to-C directionality such that each molecule possesses two C-termini. These trajectories were generated during an active learning search for the peptide sequences that yield structurally optimal self-assembled pseudo-1D nanoaggregates with good stacking between the pi-cores. Directories containing the trajectories are named "dxxx" where each "x" corresponds to an amino acid in the DXXX-OPV3-XXXD sequence (e.g. 'dfag' corresponds to the structure DFAG-OPV3-GAFD). Each trajectory itself is a 3,000 nanosecond simulation of 96 identical pi-conjugated peptides in water (/solvent), and the same trajectories where the water has been removed (/no-solvent).