Wetlab
Our experimental procedures are detailed in our lab sheets, in an easy-to-use reproducible format for any iGEM team to replicate. This structure to us, again, enables wetlab workflow to be compatible with an atypically large group of student researchers. We thus highly recommend other undergraduate iGEM teams to incorporate this structure as they are expanding.
Computational Biology
PPI:
Running Peptiderive on 11 various protein-protein interactions to generate partner-receptor candidates.
Software was run locally using Rosetta 3 on students’ computers, and candidate files were aggregated and analyzed using Rosetta binding energy tools.
For three of the 11 PPIs (1ETH, 1A01, 8FAB), which involved proteins complexes featuring multiple chains, binding energy scores were output for the best candidate from each partner-receptor chain pair. For the remaining 8 PPIs (1NW9, 4QBE, 5OEN, 7EK6, 1H59, 8E9T, 7F9D, 2p7V), the binding energy of all candidates generated by the program for each partner-receptor chain pair were assessed.
CheRMiT:
Generating chemical reaction validators and writing labeling functions. Two Jupyter notebooks were generated, as all executables generated by students were written in Python 3.8.
For the cheminformatics notebook, validator softwares were written by each student based off a canonical database list of reaction operators, RDKit functionality, and a list of sample reactions to test validators on. For the machine learning notebook, labeling functions were generated by each student to pick up on various semantic patterns within the text, at the students’ discretion; these functions were then validated based on a sample subset of annotated sentences from papers.
Hallucinating Scaffolds:
Generating alanine scans of candidate sequences and gaining familiarity with benchmarking mutant sequences. Each residue of the amino acid sequence of phytoene desaturase (PDB: 4dgk) was mutated independently to an alanine, generating 100 candidate sequences to test and benchmark. Mutated sequences were then scored for their increase in protein disorder, using IUPred, and for their change in protein secondary structure using PSIPRED.
