Paul Brenner

Modeling Conformational Ensembles of Slow Functional Motions in Pin1-WW

Protein-protein interactions are often mediated by flexible loops that experience conformational dynamics on the microsecond to millisecond time scales. NMR relaxation studies can map these dynamics. However, defining the network of inter-converting conformers that underlie the relaxation data remains generally challenging. Here, we combine NMR relaxation experiments with simulation to visualize networks of inter-converting conformers. We demonstrate our approach with the apo Pin1-WW domain, for which NMR has revealed conformational dynamics of a flexible loop in the millisecond range. We sample and cluster the free energy landscape using Markov State Models (MSM) with major and minor exchange states with high correlation with the NMR relaxation data and low NOE violations. These MSM are hierarchical ensembles of slowly interconverting, metastable macrostates and rapidly interconverting microstates. We found a low population state that consists primarily of holo-like conformations and is a “hub” visited by most pathways between macrostates. These results suggest that conformational equilibria between holo-like and alternative conformers pre-exist in the intrinsic dynamics of apo Pin1-WW. Analysis using MutInf, a mutual information method for quantifying correlated motions, reveals that WW dynamics not only play a role in substrate recognition, but also may help couple the substrate binding site on the WW domain to the one on the catalytic domain. Our work represents an important step towards building networks of inter-converting conformational states and is generally applicable.

Accelerating the replica exchange method through an efficient all-pairs exchange

The authors accelerate the replica exchange method through an efficient all-pairs replica exchange. A proof of detailed balance is shown along with an analytical estimate of the enhanced exchange efficiency. The new method provides asymptotically four fold speedup of conformation traversal for replica counts of 8 and larger with typical exchange rates. Experimental tests using the blocked alanine dipeptide demonstrate the methods correctness and show an approximate sampling efficiency improvement of 100% according to potential energy cumulative averages and an ergodic measure. An explicitly solvated PIN1 WW domain system of 4958 atoms is sampled using our new method, yielding a cluster sampling rate almost twice that of the single exchange near neighbor implementation. Computational software and scripts along with input and output data sets are available at.

Energy efficient virtual machine allocation in the cloud

Reducing energy consumption is a critical step in lowering data center operating costs for various institutions. As such, with the growing popularity of cloud computing, it is necessary to examine various methods by which energy consumption in cloud environments can be reduced. We analyze the effects of virtual machine allocation on energy consumption, using a variety of real-world policies and a realistic testing scenario. We found that by using an allocation policy designed to minimize energy, total energy consumption could be reduced by up to 14%, and total monetary energy costs could be reduced by up to 26%.

Separating Abstractions from Resources in a Tactical Storage System

Sharing data and storage space in a distributed system remains a difficult task for ordinary users, who are constrained to the fixed abstractions and resources provided by administrators. To remedy this situation, we introduce the concept of a tactical storage system (TSS) that separates storage abstractions from storage resources, leaving users free to create, reconfigure, and destroy abstractions as their needs change. In this paper, we describe how a TSS can provide a variety of filesystem and database abstractions for unmodified applications without requiring special privileges or kernel changes. A TSS provides performance competitive with NFS for single clients and also scales well for multiple servers and multiple clients. A prototype TSS of 120 disks and 6 TB of storage has been deployed at the University of Notre Dame and used for applications in high energy physics and bioinformatics.

Scheduling Grid workloads on multicore clusters to minimize energy and maximize performance

Energy is a significant and growing component of the cost of running a large computing facility. A grid workload consisting of millions of jobs running on thousands of processors may consume millions of kilowatt hours of electricity. However, because a grid workload generally consists of many independent sequential processes, we may shape its execution to satisfy energy constraints. By varying the number and frequency of processors available, a scheduler may trade off energy against performance. In this paper, we explore energy and performance tradeoffs in the scheduling of grid workloads on large clusters. We build upon previous work by showing the interaction of intelligent job assignment, automated node scaling, and frequency scaling on multicore clusters. An unexpected result is that, even though low frequency is the most efficient mode of operating a single node, the careful application of frequency scaling can actually reduce overall energy consumption even further by reducing the number of nodes powered on.

Generosity and gluttony in GEMS: grid enabled molecular simulations

Biomolecular simulations produce more output data than can be managed effectively by traditional computing systems. Researchers need distributed systems that allow the pooling of resources, the sharing of simulation data, and the reliable publication of both tentative and final results. To address this need, we have designed GEMS, a system that enables biomolecular researchers to store, search, and share large scale simulation data. The primary design problem is striking a balance between generosity and gluttony. On one hand, storage providers wish to be generous and share resources with their collaborators. On the other hand, an unchecked data producer can be gluttonous and easily replicate data unnecessarily until it fills all available space. To balance generosity and gluttony, GEMS allows both storage providers and data producers to state and enforce policies on the consumption of storage and the replication of data. By taking advantage of known properties of simulation data, the system is able to distinguish between high value final results that must be preserved and low value intermediate results that can be deleted and regenerated if necessary. We have built a prototype of GEMS on a cluster of workstations and demonstrate its ability to store new data, to replicate within policy limits, and to recover from failures.

Applying feedback control to a replica management system

Many modern storage systems used for large-scale scientific systems are multiple use, independently administrated clusters or grids. A common technique to gain storage reliability over a long period of time is the creation of data replicas on multiple servers, but in the presence of server failures, ongoing corrective action must be taken to prevent the loss of high value and low value data. Such a system is difficult to control, and replica management is typically handled in an ad hoc manner. In this work, we claim that repairing prioritized faults is a scheduling problem, founded on the need to minimize a risk-based error function, E. Citing experiments on a prototype replica system for molecular simulations, we apply concepts from control system theory to analyze and handle the application of corrective action

A Service Learning Program for CSE Students

We describe a service-learning program within the CSE department at the University of Notre Dame. Started in 1997 as the first affiliate of the Purdue EPICS program, this service-learning program involves volunteer faculty-mentored teams of students applying engineering skills in local, national, and international consulting projects for various community, educational, and not-for-profit organizations. Student-led teams, functioning as small engineering consulting firms, participate in identifying and selecting potential consulting engagements followed by the delivery of solutions to those clients. We describe 1) our unique adaptation of the EPICS model 2) supporting resources, and 3) a review of computer science centric education in multidisciplinary service engineering projects. The practical considerations of real world project management, client interaction, and liability are discussed in correlation with recent service projects undertaken by the students. Advice for interested educational institutions for developing their own engineering service learning program is presented

Enabling Sustainable Clouds via Environmentally Opportunistic Computing

Increasing economic and environmental costs of running data centers has driven interest in sustainable computing. Environmentally Opportunistic Computing (EOC) is an approach to harvesting heat produced by computing clusters. Our Green Cloud EOC prototype serves as an operational demonstration that IT resources can be integrated with the dominate energy footprint of existing facilities and dynamically controlled to balance process throughput, thermal transfer, and free cooling via job management and migration. We will describe the architecture and operation of this successful prototype with prime interest in the management of servers running in free cooling conditions.

Student Engineers Reaching Out: Case studies in service learning and a survey of technical need

We introduce Student Engineers Reaching Out (SERO), an EPICS team at the University of Notre Dame committed to Service Learning founded in engineering curricula. Two SERO case studies highlight the framework, implementation, challenges, and shared benefits of our unique Service Learning course developed specifically for engineers. The first study demonstrates the progressive refinement of a single project and the second study involves completion of numerous varied projects for a single client. For both studies we examine the application of Kolbs Learning Cycle, the Action Research cycle, and correlations with Community Based Research (CBR). Based on the success of the case studies, a comprehensive survey of the local non-profit community was undertaken. The overwhelming magnitude and variety of technical community needs are presented as new opportunities for additional Service Learning projects in engineering curricula.