Hello, A new project on the LCRC cluster has been requested. Please forward the information on to the LCRC Allocation sub-committee. Applicant's name: wei jiang Applicant's institution: ANL Applicant's division: Leadership Computing Facility Project Name: estrogen_namd Project title: Long-scale conformational activation in estrogen receptor with NAMD on GPU/CPU heterogeneous architecture Associated funding: ALCF fund DOD grant Other Systems: Mira Science: Structure-function relation of protein; Developing SIMD version force kernel for namd; Compare simd version CPU and GPU/CPU performance. Project description: Wei Jiang, Sunhwan Jo, Sichun Yang Leadership Computing Facility, Argonne National Laboratory Case Western Reserve University, Department of Pharmacology The ligand-binding domain (LBD) of an estrogen receptor undergoes a large conformational switching from an inactive to active state in response to hormone stimuli (see figure below). Very recently, a novel D538G mutant has been identified to be active in advanced breast cancer tumors. Despite being the key target for breast cancer therapeutics, the LBD is a remarkable example of conformational switching, where the dynamics of a C-terminal α-helix H12 from an inactive to active conformation remains unclear. The inactive conformation can be stabilized by therapeutic inhibitors such as tamoxifen, so H12 is in a helix-bundle forming conformation (marked in blue in Figure) that can block the receptor from recruiting coactivators for transcriptional activation. Once activated by estrogen binding, H12 is switched to a completely different orientation covering the estrogen-binding pocket in the active conformation (marked in red). These two well-defined conformations—active and inactive—have been revealed extensively by crystallographic studies. Our recent coarse-grained molecular dynamics shows such a transition could take at least in the order of 100 ns (Huang et al, JCTC, 10 (8) 2897–2900, 2014). While this information is highly informative, a key question remains, i.e., whether the mutation affects the active state only or sculpts the entire landscape, including both inactive and active states. To answer this question from a broad landscape perspective, the modeling of such a large-scale H12 transition can be quite challenging for atomic-level simulations using the standard CPU-based MD simulations. To obtain long-scale and long-time MD trajectories, we propose to use the GPU version (Nvidia CUDA) NAMD package on the Blues bigmem GPU/CPU nodes. NAMD is the only one MD code that can run at strong scaling on massively distributed GPU/CPU platform such as Cray XT7. In this proposal, in addition to the brutal-force GPU/CPU work, we also explore AVX256 instruction set to optimize force kernel of NAMD for state-of-th e-art Intel architecture. A fully vectorized force kernel with AVX256 also provides a better reasonable CPU performance reference for GPU. In this proposal we apply a total 45,000 cpu hours, including both long production run on GPU/CPU nodes and code development with AVX256. Industry partnership: Project URL: Requested allocation: 45000 Q1: 0 Q2: 0 Q3: 20000 Q4: 25000 Justification: NAMD is the only one MD code that can run at strong scaling on massively distributed GPU/CPU platform such as Cray XT7. Storage requirements: 1 TB The requester has used undetermined amount hours of their initial startup project. In addition to approving an initial amount, please specify a Category and Subcategory for this project. For a list of the current selection of approved categories, please see: https://wiki.lcrc.anl.gov/wiki/Processes/Categories Once the Allocation committee has approved the project, please go to the Project Management page to create it: https://accounts.lcrc.anl.gov/projects.php Thank You, The LCRC Accounts System