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Workshop on Biological Macromolecular Structure Models RCSB PDB Piscataway, NJ November 19-20, 2005 Topic 3: Structural Genomics and Models Contributors:

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Presentation on theme: "Workshop on Biological Macromolecular Structure Models RCSB PDB Piscataway, NJ November 19-20, 2005 Topic 3: Structural Genomics and Models Contributors:"— Presentation transcript:

1 Workshop on Biological Macromolecular Structure Models RCSB PDB Piscataway, NJ November 19-20, 2005 Topic 3: Structural Genomics and Models Contributors: S.K. Burley, A. Fiser, A. Godzik, A. Joachimiak, J. Markley, G. Montelione, C. Orengo, A. Sali, and M. Sauder Discussion Leader: Stephen K. Burley

2 Role of Comparative Protein Structure Modeling in Structural Genomics

3 Protein Structure Initiative 2: Need for Large-Scale Homology Modeling PSI-2 will yield 3,000-4,000 protein structures, most at course granularity Each structure will represent a large number of sequence homologues Homology modeling must provide “useful” models for distant (15-30%) sequence homologues  protein function assignment and evolutionary insights Models should guide functional characterization Models must be readily accessible Models must be subject to rigorous peer review

4 Issues Addressed in Contributed Slides Current limitations of homology modeling Role of homology modeling in target selection/execution Role of homology modeling in structure determination Homology modeling pipelines

5 Current Limitations of Homology Modeling Input from Joachimiak--MCSG Sali--NYSGXRC

6 Issues with Homology Modeling for Structural Genomics Models for distant (15-30%) homologues are poor quality For very large families only small fraction of sequences can be reliably modeled (<10%) Modeling must guide target selection in fine coverage of protein families Domain parsing needs improvement We should be able to model multi-domain proteins from structures of individual domains We should be able to model side chains and important structural and functional features that currently are difficult to assign and predict correctly We need methods to predict unusual features and departures from the structure that is used for modelling Modelling loop and high B factor regions needs improvement

7 Good Models >30% seq.id. >30% seq.id. Scope for further improvement (significant e-value, bad model score) Models Based on NYSGXRC Target Structures Only 363 bad-models ≥30% sequence identity. Good Models: E-Value ≤ 1.0e -4 GAScore ≥ 0.7 Good Models <30% seq.id <30% seq.id

8 Questions for Homology Modeling Community Should models be stored in archives or calculated “on the fly”? Should models from pipeline approaches be centrally accessible? Should the output of pipeline approaches be made interoperable with the PDB? Should there be a publicly available model database for storage of modeling results to facilitate peer review? Should models currently on deposit in the PDB be moved elsewhere? If so, where?


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