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The immunostimulatory cytokine interleukin-2 (IL-2) is a growth factor for a wide range of leukocytes, including T cells and natural killer (NK) cells. Considerable effort has been invested in using IL-2 as a therapeutic agent for a variety of immune disorders ranging from AIDS to cancer. However, adverse effects have limited its use in the clinic. On(More)
To date, the slowest-folding proteins folded ab initio by all-atom molecular dynamics simulations have had folding times in the range of nanoseconds to microseconds. We report simulations of several folding trajectories of NTL9(1-39), a protein which has a folding time of approximately 1.5 ms. Distributed molecular dynamics simulations in implicit solvent(More)
Simulating protein folding has been a challenging problem for decades due to the long timescales involved (compared with what is possible to simulate) and the challenges of gaining insight from the complex nature of the resulting simulation data. Markov State Models (MSMs) present a means to tackle both of these challenges, yielding simulations on(More)
Understanding molecular kinetics, and particularly protein folding, is a classic grand challenge in molecular biophysics. Network models, such as Markov state models (MSMs), are one potential solution to this problem. MSMs have recently yielded quantitative agreement with experimentally derived structures and folding rates for specific systems, leaving them(More)
Amyloid fibril deposits of the intrinsically disordered hIAPP peptide are found in 95% of type II diabetes patients, and the aggregation of this peptide is suggested to induce apoptotic cell-death in insulin-producing β-cells. Understanding the structure and dynamics of the hIAPP monomer in solution is thus important for understanding the nucleation of(More)
Simulating biologically relevant timescales at atomic resolution is a challenging task since typical atomistic simulations are at least two orders of magnitude shorter. Markov State Models (MSMs) provide one means of overcoming this gap without sacrificing atomic resolution by extracting long time dynamics from short simulations. MSMs coarse grain space by(More)
Biomolecular simulation is a core application on supercomputers, but it is exceptionally difficult to achieve the strong scaling necessary to reach biologically relevant timescales. Here, we present a new paradigm for parallel adaptive molecular dynamics and a publicly available implementation: Copernicus. This framework combines performance-leading(More)
Allosteric sodium in the helix bundle of a G protein-coupled receptor (GPCR) can modulate the receptor activation on the intracellular side. This phenomenon has confounded the GPCR community for decades. In this work, we present a theoretical model that reveals the mechanism of the allosteric modulation induced by sodium in the δ-opioid receptor. We found(More)
Interleukin 15 (IL-15) and IL-2 have distinct immunological functions even though both signal through the receptor subunit IL-2Rβ and the common γ-chain (γ(c)). Here we found that in the structure of the IL-15-IL-15Rα-IL-2Rβ-γ(c) quaternary complex, IL-15 binds to IL-2Rβ and γ(c) in a heterodimer nearly indistinguishable from that of the(More)
Markov state models (MSMs) are a powerful tool for modeling both the thermodynamics and kinetics of molecular systems. In addition, they provide a rigorous means to combine information from multiple sources into a single model and to direct future simulations/experiments to minimize uncertainties in the model. However, constructing MSMs is challenging(More)