Computer Cluster for Computational Biology and Biophysics

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 DESCRIPTION: This is a proposal to purchase a Computer Cluster to support six NIH-funded research groups at Temple University (in total, more than 50 students, post-docs, and senior personnel) carrying out diverse projects spanning biophysics, biochemistry, structural biology, population genetics and genomics. Specifically, it is proposed to acquire a Linux cluster containing 40 compute nodes with four 16-core processors each, for 2560 processor cores in total. The cluster will provide the capacity that is optimized for the computing needs of the NIH supported projects described in this proposal. The projects for which the requested equipment will be used include: Protein-Ligand Binding and Allostery: Effective Potentials, Advanced Sampling Methods, and Applications (R.M. Levy); Permeation of Biologically Active Molecules and Regulation of Membrane Channels by Molecular Dynamics Simulations (M.L. Klein, V. Carnevale, and G. Fiorin); Optimization of New Statistical Scoring Terms in the Rosetta Program and Application to Antibody- Specific Computational Design (R. Dunbrack); Early Stages of Protein Folding Explored by Experimental and Computational Approaches (H. Roder and V. Voelz); Designing and Modeling Spiroligomer Based Metalloenzyme Mimics (C. Schafmeister), and Implementation of Statistical Methods for Human Population Genomics (E.J. Hey). These computationally intensive projects are currently supported by seven R01 grants, one P01 grant and one P50 grant. The requested hardware consists of a balanced combination of compute nodes with high- throughput low-latency InfiniBand interconnect and a high-performance storage appliance to accommodate projects which require shared memory in-node parallelization and loosely coupled message passing parallel or uncoupled independent processes operating on independent data sets. A key aspect of the proposed computer cluster acquisition is to obtain greater MPI parallel capabilities needed for modern atomic simulations of proteins using advanced sampling algorithms, molecular dynamics simulations of membranes and ion channels, and Markov Chain Monte-Carlo simulations employed in population genetics and genomics modeling. The public health-related relevance of the projects described in this proposal include improving methods for the characterization of protein structures (and assemblies) as a basis for structure based drug design for treatments of HIV/AIDS and other diseases, as well as understanding the nature of the binding of anesthetics to voltage-gated ion channels.