Developing a Model to Quantify Biological Molecule Cofilin

Abstract

The base of learning and long term memory in animals is synaptic plasticity – the ability of neural synapses to strengthen or weaken over time, in response to changes in biological activity. Long-term potentiation (LTP) – a type of synaptic plasticity  involves the strengthening of neural synapses. Cofilin, a biological molecule, plays a crucial role in reorganization of actin within the cytoskeleton to support synaptic plasticity. It also cuts off the capping proteins from actin in order to allow further growth. In order to gain a deeper understanding of the molecular basis of learning and memory, a model was developed to analyze cofilin, activated by various temporal patterns of synaptic input. To more precisely quantify cofilin activity, we built functions using python to determine how long cofilin stayed above the concentration threshold, and the area under the curve for this time. These functions analyze cofilin in various parts of the neuron (spine, dendrite, dendrite membrane, etc). We are also able to sum up different molecules within a region, in order to account for different forms of Cofilin. We used github to store code since it is open to the public, provides backup storage, and has version control.