The broad goal is to develop and apply computational methods for building data-derived models of the structure and dynamics of proteins and their assemblies. These models can give insights into how the assemblies work, how they evolved, how they can be controlled, and how similar functionality can be designed. One successful approach, integrative structure modeling, casts the building of such models as a computational optimization problem where all knowledge about the assembly is encoded into the scoring function used to evaluate candidate models. It is proposed here to extend and enhance the open source Integrative Modeling Platform (IMP;http://integrativemodeling.org/) that provides programmatic support for developing and distributing integrative structure modeling protocols. IMP allows representation of molecules at a variety of resolutions, use of scoring functions based on many types of data, and searches for solutions by a variety of sampling algorithms. In addition, IMP is easily extensible to add support for new data sources and algorithms, and is distributed under an open source license, with more than 300 unique downloads since March 2010. So far, it has been applied mostly to data from electron microscopy, small angle X-ray scattering, and various proteomics methods. The package will be extended to allow addressing a greater range of biological problems and to make it more generally useful to the scientific community. Specifically, the traditional scoring functions used by IMP will be supplemented with inference-based scoring functions that extract the maximum possible information from the data. The formulation of these functions will follow a Bayesian approach with minimal assumptions and approximations, to account for errors and incompleteness in the data as well as a heterogeneous sample. Sampling of the scoring function landscape will be improved by a method that efficiently divides the complete set of degrees of freedom into potentially overlapping subsets, finds optimal and suboptimal solutions for the subsets independently by traditional optimizers or enumeration, and then combines compatible solutions to obtain guaranteed best-scoring solutions for the whole system. IMP will also be extended to make best use of the wealth of information provided by mass spectrometry. To maximize the impact of IMP and its utility to the community, it will be interfaced with other packages, including structure viewers such as Chimera, structure prediction and design programs such as Rosetta, and web portals such as the Protein Model Portal. Finally, the software will be well-tested and documented, and the growing IMP community will be supported with mailing lists, examples, demonstrations at workshops, and hosting of select users at UCSF.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM083960-06
Application #
8450759
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Lyster, Peter
Project Start
2008-04-01
Project End
2016-03-31
Budget Start
2013-04-01
Budget End
2014-03-31
Support Year
6
Fiscal Year
2013
Total Cost
$298,185
Indirect Cost
$105,185
Name
University of California San Francisco
Department
Pharmacology
Type
Schools of Pharmacy
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94143
Fernandez-Martinez, Javier; Kim, Seung Joong; Shi, Yi et al. (2016) Structure and Function of the Nuclear Pore Complex Cytoplasmic mRNA Export Platform. Cell 167:1215-1228.e25
Cimermancic, Peter; Weinkam, Patrick; Rettenmaier, T Justin et al. (2016) CryptoSite: Expanding the Druggable Proteome by Characterization and Prediction of Cryptic Binding Sites. J Mol Biol 428:709-19
Chen, Zhuo A; Pellarin, Riccardo; Fischer, Lutz et al. (2016) Structure of Complement C3(H2O) Revealed By Quantitative Cross-Linking/Mass Spectrometry And Modeling. Mol Cell Proteomics 15:2730-43
Carter, Lester; Kim, Seung Joong; Schneidman-Duhovny, Dina et al. (2015) Prion Protein-Antibody Complexes Characterized by Chromatography-Coupled Small-Angle X-Ray Scattering. Biophys J 109:793-805
Politis, Argyris; Schmidt, Carla; Tjioe, Elina et al. (2015) Topological models of heteromeric protein assemblies from mass spectrometry: application to the yeast eIF3:eIF5 complex. Chem Biol 22:117-28
Roy Choudhury, Amrita; Sikorska, Emilia; van den Boom, Johannes et al. (2015) Structural Model of the Bilitranslocase Transmembrane Domain Supported by NMR and FRET Data. PLoS One 10:e0135455
Verschueren, Erik; Von Dollen, John; Cimermancic, Peter et al. (2015) Scoring Large-Scale Affinity Purification Mass Spectrometry Datasets with MiST. Curr Protoc Bioinformatics 49:8.19.1-16
Shi, Yi; Pellarin, Riccardo; Fridy, Peter C et al. (2015) A strategy for dissecting the architectures of native macromolecular assemblies. Nat Methods 12:1135-8
Luo, Jie; Cimermancic, Peter; Viswanath, Shruthi et al. (2015) Architecture of the Human and Yeast General Transcription and DNA Repair Factor TFIIH. Mol Cell 59:794-806
Robinson, Philip J; Trnka, Michael J; Pellarin, Riccardo et al. (2015) Molecular architecture of the yeast Mediator complex. Elife 4:

Showing the most recent 10 out of 55 publications