Regulation of Small Conductance Calcium-activated Potassium Channels
Summary
Small conductance calcium-activated potassium (SK) channels play critical roles in cardiac excitability. The goals of the project is to understand the atomistic regulation of SK channels by calmodulin and PIP2. The overall thrust of the project is to design a comprehensive computational model to address successively the functional activation and regulation of SK channels in the heart.
Job Description
Perform MD simulations under guidance of a postdoctoral researcher (Dr. Ryan Woltz) on XSEDE resources to gain exposure to large scale computing and visualization capabilities.
Specifically, the project will test the Hypothesis that SK2 channel activation occurs via a two-step process, from the closed to activate state through the open but inactive intermediary. PIP2 activates SK2 channel by binding to the channel, providing a more energetically favorable conformation in the open and active state. We will take advantage of full atom-molecular dynamic (FA-MD) simulations on the SK2-CaM channel complex in a membrane that closely mimics biology to decipher not only the atomistic activation of SK2-CaM but also the regulation of SK2-CaM complex by PIP2. The findings will be directly confirmed experimentally.
Computational Resources
An application for XSEDE allocation was submitted April 15, 2020. The application was not approved. However, we have been approved for a Startup Allocation. A revised application will be submitted on July 15, 2020.
Contribution to Community
Position Type
Apprentice
Training Plan
The student will work closely with a postdoctoral researcher in the lab (Dr. Ryan Woltz) as well as the PI (Dr. Nipavan Chiamvimonvat). The student will be trained in Rosetta protein structure prediction as well as molecular dynamics simulation. The student will attend weekly lab meetings and journal clubs on computational studies of cardiac ion channels.
Student Prerequisites/Conditions/Qualifications
Experience with MATLAB, Python, basic Bash programming, machine learning, data analysis, and structural modeling.