A recent collaborative study, originating from the Gregory Voth and Andrew Ferguson Labs and involving researchers from the University of Utah, has utilized advanced supercomputer simulations to explore the dynamic instability of microtubule tips.
The research team, led by graduate student Jiangbo Wu and including Yihang Wang, Weizhi Xue, Siva Dasetty, and CCTC Post-Doctoral Researcher Daniel Beckett, initially published their findings on microtubule tip behavior in Biophysical Journal.
Their findings demonstrated that microtubule tips consistently "splay," a result that conflicts with earlier interpretations.
As detailed in a Phys.org article written by Jorge Salazar, this key discovery lays the groundwork for further exploration of microtubule dynamics
Professor Voth credited the advanced machine learning of supercomputers for enabling their progress.
"In the end,” he said, “we discovered new behavior pertinent to living cells.”
This research provides a better understanding of how microtubules work, particularly how their malfunctions contribute to neurodegenerative diseases, which could lead to advances in treatments.
Read the article at Phys.org: Supercomputer models microtubule dynamics, offering new insights into neurodegenerative diseases
Read the study: Data-driven equation-free dynamics applied to many-protein complexes: The microtubule tip relaxation