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Simulating proteins on lipid membranes could provide unprecedented insights into cancer biology and a host of other phenomena. However, such simulations face conflicting computational constraints: reaching biologically relevant time and length scales (milliseconds and microns) requires continuum-level models but understanding the processes of interest requires molecular level detail. I will present a new type of massively parallel, multiscale simulation framework that brings together these two modeling paradigms. Using a machine learning algorithm, we couple a novel continuum model to an ensemble of molecular dynamics simulations. The result is a simulation at macro length- and time-scales that incorporates microscale precision. We demonstrate this capability with a large-scale simulation of several hundred k-Ras proteins on a realistic lipid bilayer spanning 1 μm2. Citation Format: Frederick H. Streitz. Multiscale simulations of k-Ras on lipid bilayers [abstract]. In: Proceedings of the AACR Special Conference on Targeting RAS-Driven Cancers; 2018 Dec 9-12; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(5_Suppl):Abstract nr IA10.

Driver mutations in KRAS occur in almost 30% of human tumors, primarily in pancreatic, colorectal and lung tumors. These mutations result in increased cell proliferation and survival predominantly mediated through the MAPK signaling pathway. MAPK signal transduction is initiated by the interaction of RAF kinase with active RAS at the plasma membrane. The precise molecular details of this process are currently unknown. The Frederick National Laboratory for Cancer Research has partnered with the Department of Energy to harness high-performance computing and experimental data to generate models and hypotheses of how KRAS engages with RAF kinase at the plasma membrane to initiate signal transduction. The initial phase of this work has focused on identifying membrane bound states of KRAS. We have used a variety of biophysical approaches (including NMR, protein foot-printing and neutron reflectivity) to investigate the structural orientation of KRAS at the membrane. In addition, large scale coarse-grained simulations of membrane bound KRAS spanning the millisecond time scale, have been completed. Three predominant membrane bound KRAS states were observed computationally: an exposed state (where switch 1 is available for RAF binding), an occluded state (where switch 1 is unavailable for RAF binding) and a transition state (where helix 5 is perpendicular to the membrane). These three states are also identified in the experimental data. Cumulatively, experimental and computational data predict KRAS exists in a dynamic equilibrium on the plasma membrane, interconverting between 3 states on the nanosecond time scale. The experimental data indicates the most populated conformation of KRAS is the transition state. Future efforts will address the significance of these three states for RAF interaction and signal transduction. This in depth understanding of RAS activation of RAF and the MAPK pathway is critically important for developing effective therapeutic interventions for cancers harboring mutant RAS. Citation Format: Andrew G. Stephen, Animesh Agarwal, Angel E. Garcia, Gnana S. Gnanakaran, Jeevapani Hettige, Christopher Neale, Timothy Travers, Harsh Bhatia, Peer-Timo Bremer, Tim Carpenter, Jim Glosli, Helgi Ingolfsson, Piyush Karande, Felice Lightstone, Tomas Oppelstrup, Liam Stanton, Shiv Sundram, Xiaohua Zhang, Debsindhu Bhowmik, Arvind Ramanathan, Christopher Stanley, Debanjan Goswami, Gulcin Gulten, Frantz Jean-Francios, Dhirendra Simanshu, Tommy Turbyville, Rebika Shrestha, Que Van, Frank McCormick, Dwight Nissley, Fred Streitz, Constance Agamasu. Identification of KRAS membrane bound states using an integrated computational and experimental approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3373.