The main goal of this proposal is to produce high-accuracy comparative models for proteins that share less than 30% sequence identity with their homologs of known structures. Model accuracy is influenced by the target-template sequence alignment accuracy and the structural similarity between target and template. We work under the assumption that model inaccuracies that have different origins (misalignment vs. structural divergence) need to be dealt with in different ways, and that effective improvement of model accuracy requires understanding the nature of the interplay between """"""""alignment error"""""""" and """"""""template error."""""""" In this project the alignment error is dealt with through a new alignment optimization procedure guided by structure-based evaluation of the model implied by the alignment. The template error is dealt with a new refinement approach that combines simulation with template-derived restraints. Molecular dynamics and Monte Carlo simulations are used to explore conformational space and to provide an accurate refinement environment that includes explicit solvent. Finally, alignment error and template error are iteratively optimized in an approach that exploits the synergy of alignment and structure refinement. To guarantee that the approach is practical it is also applied to a real modeling project with experimental validation. This multidisciplinary approach is possible because of the combination of researchers in comparative modeling (Dr. Sanchez), computational biophysics (Drs. Osman and Mezei), and experimental structural biology (Dr. Zhou). At the end of the project period it is expected that a new modular approach to comparative modeling will have been developed that is capable of modeling remote homologs of known structures with an accuracy equivalent to that of high-resolution NMR structures. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM081713-01
Application #
7304375
Study Section
Special Emphasis Panel (ZGM1-CBB-3 (HM))
Program Officer
Smith, Ward
Project Start
2007-08-01
Project End
2010-07-31
Budget Start
2007-08-01
Budget End
2008-07-31
Support Year
1
Fiscal Year
2007
Total Cost
$268,420
Indirect Cost
Name
Mount Sinai School of Medicine
Department
Biology
Type
Schools of Medicine
DUNS #
078861598
City
New York
State
NY
Country
United States
Zip Code
10029
Ghersi, Dario; Sanchez, Roberto (2012) Automated identification of binding sites for phosphorylated ligands in protein structures. Proteins 80:2347-58
Lin, Yingjie; Yoo, Seungyeul; Sanchez, Roberto (2012) SiteComp: a server for ligand binding site analysis in protein structures. Bioinformatics 28:1172-3
Chakravarty, Suvobrata; Ghersi, Dario; Sanchez, Roberto (2011) Systematic assessment of accuracy of comparative model of proteins belonging to different structural fold classes. J Mol Model 17:2831-7
Ghersi, Dario; Sanchez, Roberto (2011) Beyond structural genomics: computational approaches for the identification of ligand binding sites in protein structures. J Struct Funct Genomics 12:109-17
Ghersi, Dario; Sanchez, Roberto (2009) Improving accuracy and efficiency of blind protein-ligand docking by focusing on predicted binding sites. Proteins 74:417-24
Ghersi, Dario; Sanchez, Roberto (2009) EasyMIFS and SiteHound: a toolkit for the identification of ligand-binding sites in protein structures. Bioinformatics 25:3185-6
Hernandez, Marylens; Ghersi, Dario; Sanchez, Roberto (2009) SITEHOUND-web: a server for ligand binding site identification in protein structures. Nucleic Acids Res 37:W413-6
Sanchez, Roberto; Zhou, Ming-Ming (2009) The role of human bromodomains in chromatin biology and gene transcription. Curr Opin Drug Discov Devel 12:659-65
Chakravarty, Suvobrata; Godbole, Sucheta; Zhang, Bing et al. (2008) Systematic analysis of the effect of multiple templates on the accuracy of comparative models of protein structure. BMC Struct Biol 8:31