Research - Software Development
Folding@Home is a distributed computing resource for molecular dynamics simulations run by Vijay Pande at Stanford University. Long simulations are broken up into small workunits that run on users computers. The results are then collected and analyzed. The amount of data presents several challenges in terms of maintenance and analysis methodologies: an iterative approach is infeasible, so we are developing a set of tools for the management and analysis that take advantage of as many distributed resources as possible. We are running several experiments on Folding@Home for the WW domain. This domain is comprised of 35 to 40 residues that form into 3 beta-strands and is associated with protein signaling processes. The goal of one set of experiments is to better understand how the WW domain folds. In order to do so we are comparing experimental results for a set of engineered WW mutants with the simulation results.
ProtoMol is an object-oriented, component based, framework for molecular dynamics (MD) simulations. Originally designed for prototyping new MD methods, ProtoMol is easily extended and modular due to its object-oriented architecture. We use ProtoMol for testing and validating the methods we've developed such as NML as well as running MD simulations used in our collaborations with the experimental community such as the WW project.
Studying processing such as protein folding and protein dynamics generates large amounts of data: millions of trajectories over multiple projects results in several terabytes of data. In order to get results in a reasonable amount of time the analyses of the data must be done in a parallel fashion. the Protolyze and Prototools projects are our approach to this problem. The goal for Protolyze is to provide a framework to manage the analyses (such as submitting jobs to the Sun Grid Engine, coordinating database access, etc). Prototools is a repository of tools and workflows used to run various analyses (calculating RMSDs, secondary structure, etc).
OpenMM is a library of molecular dynamics (MD) method implementations designed to allow MD simulation packages to take advantage of hardware (GPU) acceleration with minimal effort. We are working with the OpenMM group to make a GPU-accelerated implementation of our NML method available to OpenMM users. We believe that doing so will encourage widespread availability of NML in widely-used MD simulation packages such as GROMACS and adoption by the MD community.
Cytoprophet is a project developed by the Laboratory for Computational Life Sciences at the Computer Science Department of the University of Notre Dame. It is a tool to help researchers to infer new potential protein (PPI) and domain (DDI) interactions. It is implemented as a Cytoscape plugin, where users input a set of proteins and retrieve a network of plausible protein and domain interactions with a score. Three algorithms are used for the estimation of PPI/DDI: Maximum Specificity Set Cover (MSSC) Approach, Maximum Likelihood Estimation (MLE) and the Sum-Product Algorithm (SPA) for protein networks. To see more details, refer to the documentation.