During our initial stages as an iGEM team, we faced difficulties constructing gene circuits. The primary problem was the identification of crucial genetic elements such as Ribosome Binding Sites (RBS), Anderson Promoter Regions, and Flanking Regions. These elements play an important role in the proper regulation and functioning of genetic circuits, making them essential for successful synthetic biology projects. In response to these challenges, we developed SeqPredict. This software can locate RBS, Anderson Promoter Regions, and Flanking Regions within a given DNA sequence. By doing so, we aim to streamline the process of gene circuit design and assembly, saving teams valuable time and effort. To know more about SeqPredict: Go to our software page!
One of the programs that was developed by our iGEM 2017 team was the “Promoter Strength Predictor." This tool adapts a machine learning approach to predict the strength of Sigma 70 promoters in E. coli, thus streamlining and enhancing promoter selection for the iGEM projects. To utilize this tool, users need to input the DNA sequence of the promoter to predict its strength. The predicted promoter strength is reported based on comparing the values associated with the well-characterized Anderson promoters, which are known for their expression levels. Specifically, the user should submit the -10 and -35 hexamers of the promoter sequence as input. Upon submission, our tool will analyze and predict its strength. We developed an upgraded version of this software, “PromoterStrengthPredict 2.0”, which involves finding the RBS strength when the sequence is given as the input. The output will be a 2-D plot between the RBS sequence score (X-axis) and the RBS strength value (Y-axis). To know more about PromoterStrengthPredict 2.0: Go to our software page!
Our team has uploaded additional information for an existing part in the iGEM registry BBa_K729002. We added Ramachandran Plot, 2-D and 3-D interaction plots for Laccase and Polyethylene. The three dimensional structure of the protein was predicted using SWISS-MODEL. The model was validated using Ramachandran plot analysis. It was observed that 95.91 % of the residues were under the favoured region. This confirms the reliability of the predicted protein model. The molecular docking analysis was performed for laccase and PE (Polyethylene n=10) using AUTODOCK tools. From the 2D and 3D interaction maps it was observed that the PE was within the active site pocket and residues LYS474, PRO274, VAL 300, LEU276 was found to interact with the PE substrate.