Chunhong’s RyR Paper Online

Chunhonginvestigated the valence selectivity of RyR channels by using atomistic MD simulations, and observed the details of competition between Ca++ and K+ in the extended selectivity filter of RyRs. The presence of Ca++ significantly decreases the K+ conductance, while K+ has little impact on Ca++ permeation, due to the much stronger binding of Ca++ in the highly negatively charged and size-limited luminal vestibule. This is a further application of our recently developed multisite Ca++ model, showing atomistic details of valence selectivity of RyRs that are in good agreement with previous experimental findings and simplified models. The paper can be found here.

GBA Biophysics Forum


Dr. Chen SONG was invited to give a talk at “The First Great Bay Area Biophysics and New Drug Discovery Forum” on April 10, where he presented our recent story on the valence selectivity of ryanodine receptors. Dr. Yang WANG presented a poster of our NompC work at the forum, which attracted much attention.


Aihua is leaving


Sadly, Dr. Aihua ZHANG is leaving the group for family reasons. Aihua was one of the first members who joined me to build up the group. He has contributed so much to the group, not only in developing the new calcium model allowing us to simulate calcium-permeating ion channels, but also in helping group members in so many different ways. It has been a great pleasure to work with Aihua. We wish him all the best in every aspect of the future.


Happy NIU Year!


Quite a few group members stayed in Beijing during the Chinese New Year holidays. We had a hot pot together in the Jiayuan cafeteria on the first day of the Niu Year. Happy New Year, everyone!


Seminar by Prof. XU Dong

Invited by Dr. SONG, Prof. XU Dong from the University of Missouri-Columbia gave us an online CQB seminar entitled “Graph Neural Networks to Learn Long-range Interactions in Proteins from Molecular Dynamics Simulations” on Jan 11, 2021. Around 140 attendees participated in the event, and it’s very interesting to see how graph neural networks can be used to identify the allosteric pathways from MD trajectories.