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Stromal interaction molecule 1 (STIM1) is a Ca-sensing protein in the endoplasmic reticulum (ER) membrane. The depletion of ER Ca stores induces a large conformational transition of the cytosolic STIM1 C-terminus, initiated by the dimerization of the transmembrane (TM) domain. We use the AI-guided transition path sampling algorithm aimmd to extensively sample the dimerization of STIM1-TM helices in an ER-mimicking lipid bilayer. In nearly 0.5 ms of all-atom molecular dynamics simulations without bias potentials, we harvest over 170 transition paths, each about 1.2 μs long on average. We find that STIM1 dimerizes into three distinct and coexisting configurations, which reconciles conflicting results from earlier crosslinking studies. The dominant X-shaped bound state centers around contacts supported by the SxxxG TM interfacial motif. Mutating residues in this contact interface allows us to tune the STIM1-dimerization propensity in fluorescence experiments. From the trained model of the committor probability of dimerization, we identify the transition state ensemble for TM-helix dimerization. At the transition state, interhelical contacts in the luminal halves of the two monomers dominate, which likely enables the luminal Ca-sensing domain in STIM1 to condition the dimerization of the TM helices. Our work demonstrates the unique power of AI-guided simulations to sample rare and slow molecular transitions and to produce detailed atomistic insight into the mechanism of STIM1 TM-helix dimerization as a key step in ER Ca-sensing.
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http://dx.doi.org/10.1073/pnas.2506516122 | DOI Listing |
Proc Natl Acad Sci U S A
September 2025
Department of Theoretical Biophysics, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany.
Stromal interaction molecule 1 (STIM1) is a Ca-sensing protein in the endoplasmic reticulum (ER) membrane. The depletion of ER Ca stores induces a large conformational transition of the cytosolic STIM1 C-terminus, initiated by the dimerization of the transmembrane (TM) domain. We use the AI-guided transition path sampling algorithm aimmd to extensively sample the dimerization of STIM1-TM helices in an ER-mimicking lipid bilayer.
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View Article and Find Full Text PDFSci Data
June 2025
Department of Physics, Technical University Munich, James-Franck-Str. 1, 85748, Garching, Germany.
Lignin-carbohydrate complexes (LCCs) are bioproducts with high potential as alternatives for petrochemicals. However, the complex structure and the lack of protocols for high-yield production limit their usage. Herein, we present data collected from a comprehensive artificial intelligence (AI)-guided optimization of the AquaSolv Omni (AqSO) biorefinery process targeting high-yield production of LCCs.
View Article and Find Full Text PDFAdv Sci (Weinh)
July 2025
Tianjin Key Laboratory of Life and Health Detection, Life and Health Intelligent Research Institute, Tianjin University of Technology, Tianjin, 300384, China.
Colloidal nanoparticle self-assembly is a key area in nanomaterials science, renowned for its ability to design metamaterials with tailored functionalities through a bottom-up approach. Over the past three decades, advancements in nanoparticle synthesis and assembly control methods have propelled the transition from single-component to binary assemblies. While binary assembly has been recognized as a significant concept in materials design, its potential for intelligent and customized assembly has often been overlooked.
View Article and Find Full Text PDFCell Transplant
March 2025
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
With the rising demand for liver transplantation (LT), research on acute rejection (AR) has become increasingly diverse, yet no consensus has been reached. This study presents a bibliometric and latent Dirichlet allocation (LDA) topic modeling analysis of AR research in LT, encompassing 1399 articles. The United States, Zhejiang University, and the University of California, San Francisco emerged as leading contributors, while Levitsky J and Uemoto SJ were key researchers.
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