Vision Statement

The NYSGRC will provide international leadership in enabling collaborative structural biology research where partnerships with leading biologists will define and solve important questions in biology and disease.

Mission Statement

The NYSGRC will complement high-throughput structure determination capabilities with biochemical and computational approaches to establish an integrated platform with the capabilities and flexibility to meet the wide ranging and dynamic challenges inherent in integrating structure and biology within the collaborative framework of the PSI:Biology Network.

Overview

The NYSGRC has a 10-year proven track record in high-throughput structure determination, solving more than 1000 structures to date, as well as in discovering and implementing infrastructure to increase the speed, accuracy, success rate and affordability of structural biology studies. We have demonstrated the ability to address a wide range of important biological and biomedical problems, including human and pathogen-encoded phosphatases, metastasis factors, nuclear pore components and structures that have significantly impacted high-throughput functional annotation efforts. Over the past ten years the NYSGRC has evolved a series of core activities that support all aspects of the Protein Structure Initiative (PSI):

  • Data Management/LIMS
    Tool that efficiently tracks all activities within the NYSGRC, including all required reporting activities and coordination with other elements of the PSI network
  • Bioinformatics
    For target identification, ortholog expansion, construct design, homology modeling, structure leverage and annotation
  • Protein Production
    For high-throughput cloning, expression, purification and quality control
  • Structure Determination
    For high-throughput crystallization, data collection and structure determination
  • Technology Development
    For new approaches to augment the existing high-throughput pipeline (e.g., novel protein expression technologies) and the development and utilization of cutting-edge biochemical and computational technologies that complement and leverage structure data.

This infrastructure and the management team have been highly effective in furthering the stated aims of PSI-2, which has dramatically expanded structural coverage of sequence space. Our overall productivity is evidenced both by the number of structures completed as well as the total number of residues that have been structurally characterized from unique PDB depositions (>550,000 residues). The latter attests to the high average median length of NYSGRC structures completed.

This strategy changed considerably during PSI:Biology. We focus on numerous challenging and high priority targets from a wide range of sources (e.g., multidomain eukaryotic proteins, multi-component assemblies, and secreted proteins). Such targets require enhanced experimental and computational capabilities and are demand efforts substantially greater than those needed for typical PSI-2 targets. The NYSGRC has been reorganized to meet these challenges by augmenting existing high-throughput infrastructure with an emphasis on innovative and cutting-edge eukaryotic expression platforms as well as novel biochemical, biophysical and computational approaches that will be invaluable to the PSI:Biology collaborators. These enhancements will result in a highly robust pipeline that possesses both the bandwidth and the flexibility to accommodate the evolving demands of the targets likely to populate PSI:Biology Network.

In addition to established albeit conventional PSI-2 capabilities, the NYSGRC offers the PSI:Biology Network a set of unique capabilities including:

  • unique resources to address mammalian proteins, with particular expertise in secreted proteins
  • an emerging automated platform to rapidly and efficiently screen for minimal/optimal constructs for binary protein assemblies
  • complementary computational and experimental infrastructure to address the problems inherent in structure determination of large protein assemblies
  • extensive experience with enzymes (and ligand-bound complexes), and
  • emerging multi-disciplinary structure determination capabilities, combined with the carefully considered use of traditional methods to address the remarkable 90% failure rate in structure determination for modeling families.

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