A  primary  goal  of  this  work  is  to  make  the  computational  tools broadly available to the community. To achieve this, we have hosted both  our  inexpensive  peptide  model  and  machine  learning protocol for peptide design on the code sharing site GitHub for free, open-source, public download.

As  part  of  our  DMREF  program, we place a high premium on exposing  undergraduate  researchers  to  problems  that  require strong  synergies  between  computational  and  experimental approaches.  Shown  at  right  is  one  such  student  (Clara  T.-V.),  a chemical  engineering  undergraduate  at  Johns  Hopkins  working  with her   graduate   mentor   Jessie   D.      Clara’s   project   entails   the development  of  peptides  that  will  be  programmed  to  self-sort  into segregated  heterostructures.    This  will  enable  the  formation  of supramolecular   “p-n   junctions”   and   other   types   of   complex architectures.    She  has  been  exposed  to  the  empirical  instinctual aspect  of  peptide  design  to  achieve  this  goal  and  will  soon  benefit from exposure to computational tools to assist with sequence design to promote self-sorting.