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JCSG Personnel



Overview and Mission
(Choose a colored segment for more information about each Core group)

Overview

The JCSG high-throughput (HTP) platform, assembled over the past 15 years, has delivered a large numbers of protein structures to the community by both X-ray crystallography and NMR on a wide range of targets from bacteria to human, including challenging targets, such as eukaryotic proteins, protein-protein and other macromolecular complexes. Our primary approach to HTP structural biology involves processing sets of targets through an extensive combination of bioinformatics and biophysical analyses to efficiently characterize each target in order to optimize its path through our pipeline.

The Joint Center for Structural Genomics (JCSG) is funded by the National Institute of General Medical Sciences (NIGMS), as part of the third phase of the Protein Structure Initiative (PSI) of the National Institutes of Health. (U54 GM094586)

The JCSG is a multi-institutional consortium with major activities at The Scripps Research Institute (TSRI); the Genomics Institute of the Novartis Research Foundation (GNF); the University of California, San Diego (UCSD); the Sanford-Burnham Medical Research Institute (SBMRI); and the Stanford Synchrotron Radiation Lightsource (SSRL), SLAC National Accelerator Laboratory.

 

Vision

To explore the expanding protein universe to find new challenges and opportunities to significantly contribute to new biology, chemistry and medicine through development of HT approaches to structural genomics.

 

Mission

Our primary mission as a PSI:Biology Center for High-Throughput Structure Determination is to provide a robust, flexible HTP structure determination pipeline that meets the challenges and embraces the opportunities that arise from PSI:Biology Partnerships projects and the community through (PSI Community Nominated Target) CNTs. The JCSG is leveraging its HTP platform to promote the biological and biomedical impact of all of our structures through extensive functional and bioinformatics analyses both internally and in collaboration with our Partnerships, CNTs and other collaborations within the PSI:Biology network, as well as the general scientific community. As part of the PSI:Biology Network, we strive to promote widespread use of PSI resources, materials, methodologies and data to the general scientific community. The JCSG also continues to develop new technologies and methodologies, both experimental and computational, to address a wide spectrum of targets, while keeping the cost per structure to a minimum and quality to the highest standard.

 

Center Organization

The JCSG centralizes each core activity into single dedicated sites, each handling distinct, but interconnected objectives. This unique approach allows each specialized group to focus on its own area of expertise and provides well-defined interfaces among the groups. In addition, this approach addresses the requirements for the scalability needed to process large numbers of targets at a greatly reduced cost per target. 

JCSG production groups are:

Administrative Core
Bioinformatics Core
Crystallomics Core
Structure Determination Core
NMR Core

The JCSG is committed to a model that employs distributed local management and centralized coordination to establish a pipeline with fully functional large-scale production sites that are tightly integrated to ensure standardization of data, uniformity of communication interfaces, and synchronization of production schedules. The overall structure of the JCSG is designed to ensure the most efficient operation and data management that optimizes the use of resources and minimizes the cost per structure. This "factory"-like approach was developed in a scalable mode to enable the JCSG to easily adapt to changing goals and challenges, which importantly includes a learning environment to feed results back from prior experiments in order to increase productivity at each step in the process.
JCSG Leadership Structure Determination Core Structure Determination Core Crystallomics Core Bioinformatics Core
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