Loading Neuron Loading Neuron Loading Neuron


Chevron Forward Description
Chevron Forward Engineering
Chevron Forward Implementation
Chevron Forward Contribution

Aptamer against Bacteria and Fungal element

We have identified 3 aptamers, which bind to the bacteria Escherichia coli ATCC 25922 (BBa_K4391000), Salmonella typhimurium (BBa_K4391002), and Penicillin G or Benzyl Penicillin from the fungus Penicillium chrysogenum. (BBa_K4391001).

For each of these, we have modeled the 2D, and 3D folded structures and performed molecular docking. We have further characterized the aptamers for E. coli and Penicillin G by:

  1. Cloning into pUC19 vector, followed by transformation into Escherichia coli DH5α.
  2. Gradient asymmetric PCR to amplify the aptamer construct.
  3. Gel electrophoresis to confirm the size of the aptamer.
  4. GO/PANI fixing followed by Electrochemical Impedance Spectroscopy (EIS) and Cyclic Voltammetry.
  5. Sensitivity of the aptamers to their respective targets.

Detailed documentation can be found in the parts registry.

In-silico aptamer generation against Vibrio Sp.

In collaboration with Team- Montpellier, iGEM 2022, we have designed an aptamer against ToxR Protein (PDB ID: 4MLO) of Vibrio cholerae. The design process may be summarised as follows:

We have also run Molecular Dynamics simulations to demonstrate that the designed aptamer shows good binding affinity to ToxR. More information on this: BBa_K4391003.

Modeling of existing aptamers

We have run 2D and 3D folding structure predictions and molecular docking simulations with target molecules for 2 existing aptamers: IL-6 aptamer (BBa_K3724001) and Lactoferrin Aptamer (BBa_K3724005). Please visit the part registry to learn about the modeling protocol and results.


We have developed Kwick Aptamer-based Motif Identification (KAMI). This software can be used to identify the particular short amino acid sequence (motif) that binds to a particular aptamer. This makes it possible to improve aptamer design by testing binding affinity to a peptide sequence.

It can also be used to identify the protein (given a database of proteins) that the aptamer best binds to. Thus, KAMI is really helpful in identifying the exact proteins that aptamers generated using cell-SELEX bind to. This can be used to improve the aptamer sequences, making them more specific and sensitive. Please visit the Software Section to know more.

Neural Chip

We have developed the neural chip - a biological computation device that is able to detect input signals and can be trained to produce output signals based on the requirement. This device can be used by future iGEM teams as a tool in combination with synthetic biology constructs such as aptamers to create a fast, accurate detection kit. This chip can also be implemented in disease risk prediction and personalized medicine. In the future, the neural chip can be further developed to create full-scale computers. No iGEM team has attempted this novel idea before.

The neural chip development consists of 3 main steps:

  1. ECAD design of chip circuit followed by metal deposition to create the electrodes.
  2. Culturing neural cell lines (SH-SY5Y and N2a) and transferring them onto chip
  3. Training of the neural circuit using varying AC voltage and frequency

More information on the neural chip: Project Description. Take a look at the design and engineering of the chip: Engineering Success. To know more about the wet lab experiments required for the neural chip: Wet Lab Experiments.

Book on Aptamers with iGEM Linkoping, Sweden, iGEM NU Kazakhstan, and iGEM Tirupati

We collaborated with Team Linkoping and others to develop a book on aptamers contributing to future iGEM teams and the scientific community. To learn more, check https://2022.igem.wiki/linkoping-sweden/contribution.