Simulation of Multi-Protein systems

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The main area of research, supported by the grant R01 GM118078, entitled “Simulation of Multi-Protein Systems”, is investigating the interactions between proteins in cellular assemblies. Elucidating such interactions will further mechanistic understanding of cellular processes, and will enable effective therapy development. NIGMS administrative supplement is requested to acquire a high performance GPU cluster to develop physics aware deep learning models . Typically atomic simulations are performed using either physics or machine learning based approaches, with results obtained by the two methods being orthogonal to each other. Instead of a trivial combination of methods, the project goal is to develop special deep neural network architectures, which encode geometry and physics of the underlying system. The inference of such network will be performing realistic physical simulations, with parameters trained on the available data to optimally reproduce experimental observations. Training of such models require significant GPU resources thus justifying the need for the cluster. The new models will be applied to understanding the molecular mechanisms in healthy and diseased cells on the genomics scale. In addition, the results of the research in the Kozakov lab are made available through the macromolecular modeling server ClusPro, a public resource with more than 25000 users running tens of thousands calculation each month. Deploying these methods on the server is also requiring significant GPU resources. Thus the purchased GPU cluster will serve dual goals, first provide training time to develop and apply the new models and then adding to the ClusPro backend.