Ruiyan Wang

All Publications

• Cav3.1 is a neuronal leucine sensor that mediates satiety and weight loss in response to dietary protein. Cell metabolism Tsang, A. H., Heeley, N., Alcaino, C., Hwang, E., Lam, B. Y., Rahman, T., Darwish, T., Nuzzaci, D., Kay, R. G., Sarkar, A., Wang, R., Basha, N., Punnoose, A., Kirwan, P., Ma, M., Yeo, G. S., Merkle, F. T., Gribble, F. M., Reinmann, F., Williams, K. W., Blouet, C. 2026; 38 (5): 876-890.e13

  Abstract

  Dietary protein promotes satiety and weight loss, yet how appetite-regulating neurons sense dietary protein remains poorly understood. Here, we show that Cacna1g, which encodes the T-type voltage-gated calcium channel Cav3.1, is enriched in hypothalamic leucine-sensing neurons and mediates neuronal leucine sensing. Pharmacological inhibition of Cav3.1 blunts leucine-induced activation of pro-opiomelanocortin (POMC) neurons in cultured neurons and brain slices, thereby suppressing the anorectic response to hypothalamic leucine in vivo. Genetic deletion of Cacna1g in POMC neurons abolishes the appetite- and weight-suppressive effects of high-protein feeding. Mechanistically, leucine binds a hydrophobic pocket of Cav3.1 and lowers its threshold for voltage-dependent activation. Finally, pharmacological activation of mediobasal hypothalamic Cav3.1 promotes weight loss in diet-induced obese mice and potentiates responses to anorectic agents, including liraglutide. Together, these findings establish hypothalamic Cav3.1 as a neuronal leucine sensor and nominate it as a tractable target for anti-obesity therapy.

  View details for DOI 10.1016/j.cmet.2026.03.017

  View details for PubMedID 42025169

• Complete Active Space Self-Consistent Field with GPU-Accelerated Density Fitting. Journal of chemical theory and computation Wang, R., Wang, Y., Lu, L., Hait, D., Martínez, T. J. 2026

  Abstract

  The complete active space self-consistent field (CASSCF) method is essential for describing complex photochemical processes, but its application in ab initio molecular dynamics is often limited by the computational cost associated with four-center two-electron repulsion integrals (ERIs). We implement the atomic orbital (AO)-based GPU-accelerated density fitting (DF) approximation for CASSCF within the TeraChem software package. Validation on salicylaldimine demonstrates that the DF approximation introduces negligible errors in relative energies, yielding excitation energies accurate to within 10 microHartrees of the integral-direct reference. The DF-CASSCF implementation achieves significant computational speedups, accelerating total energy and gradient calculations by more than an order of magnitude for small- to medium-sized systems with large AO basis sets. We demonstrate the practical utility of this approach through ab initio multiple spawning dynamics simulations of excited-state intramolecular proton transfer (ESIPT). The DF-CASSCF trajectories reproduce the photodynamics of the reference simulations while reducing the total wall time (for a single GPU) by a factor of 3-30, depending on the choice of the basis set. This work significantly lowers the barrier for high-throughput, high-accuracy multireference simulations on modern GPU architectures.

  View details for DOI 10.1021/acs.jctc.5c02079

  View details for PubMedID 41854296

• A Mathematical Model of Cellular Aggregation Predicts Patterns of Tau Accumulation in Neurodegenerative Disease ADVANCED SCIENCE Huang, S., Quaegebeur, A., Pansuwan, T., Rittman, T., Wang, R., Knowles, T. P. J., Rowe, J. B., Klenerman, D., Meisl, G. 2026; 13 (1): e11297

  Abstract

  Protein aggregates are a hallmark of neurodegenerative disease, yet the molecular processes that control their appearance remain incompletely characterized. In particular, it is unknown to what degree the development of aggregates in one cell is triggered by nearby aggregate-containing cells, as opposed to proceeding cell-autonomously. Here, a minimal, bottom-up computational model is developed that is characterized by just two parameters: the relative rate of cell autonomous and cell-to-cell triggers of aggregation and a length scale of cell-to-cell interactions. Its applicability is demonstrated in the primary tauopathy Progressive Supranuclear Palsy by extracting mechanistic information from the distribution of tau aggregates at different disease stages from post-mortem human brain. Despite its simplicity, the model is able to reproduce the aggregate patterns observed in the data and reveals that the triggering of aggregation by nearby aggregated cells, over distances of ≈100 µm, is the major driver of disease progression once a low threshold level of aggregates is reached. The model also provides a natural explanation for an increase in the rate of disease progression when this threshold is reached, providing fundamental new insights into disease mechanisms and predicting the efficiency of different therapeutic strategies.

  View details for DOI 10.1002/advs.202511297

  View details for Web of Science ID 001602811600001

  View details for PubMedID 41144847

  View details for PubMedCentralID PMC12767001