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On the role of physics and evolution in dictating protein structure and function. Israel Journal of Chemistry.. In Press.
WeFold: A Coopetition for Protein Structure Prediction. Proteins: Structure, Function, and Bioinformatics. :n/a-n/a.. 2014.
Restricted N-glycan Conformational Space in the PDB and Its Implication in Glycan Structure Modeling. PLoS Computational Biology. 9(3):e1002946. PDF. 2013.
Are predicted protein structures of any value for binding site prediction and virtual ligand screening? Current opinion in structural biology. 23(2):191-7. PDF. 2013.
Segment assembly, structure alignment and iterative simulation in protein structure prediction. BMC Biology. 11(1):44. PDF. 2013.
A Comprehensive Survey of Small-Molecule Binding Pockets in Proteins. PLoS Computational Biology. 9(10):e1003302. PDF. 2013.
On the Importance of Hydrodynamic Interactions in Lipid Membrane Formation. Biophysical Journal. 104(1):96-105. PDF. 2013.
Interplay of physics and evolution in the likely origin of protein biochemical function. Proceedings of the National Academy of Sciences. 110(23):9344-9349. PDF. 2013.
APoc: large-scale identification of similar protein pockets. Bioinformatics. 29(5):597-604. PDF. 2013.
FINDSITEcomb: A Threading/Structure-Based, Proteomic-Scale Virtual Ligand Screening Approach. Journal of Chemical Information and Modeling. 53(1):230-240. PDF. 2013.
Dynamic simulation of concentrated macromolecular solutions with screened long-range hydrodynamic interactions: Algorithm and limitations. Journal of Chemical Physics. 139:121922-1. PDF. 2013.
Importance of excluded volume and hydrodynamic interactions on macromolecular diffusion in vivo. International Conference of the Quantum Bio-Informatics IV. 30:378-387.. 2013.
EFICAz2.5: application of a high-precision enzyme function predictor to 396 proteomes. Bioinformatics. 28(20):2687-2688. PDF. 2012.
Krylov subspace methods for computing hydrodynamic interactions in Brownian dynamics simulations. The Journal of Chemical Physics. 137:064106. PDF. 2012.
FINDSITEX: A Structure-Based, Small Molecule Virtual Screening Approach with Application to All Identified Human GPCRs. Molecular Pharmaceutics. 9(6):1775-1784. PDF. 2012.
Further Evidence for the Likely Completeness of the Library of Solved Single Domain Protein Structures. The Journal of Physical Chemistry B. 116(23):6654-6664. PDF. 2012.
The distribution of ligand-binding pockets around protein-protein interfaces suggests a general mechanism for pocket formation. Proceedings of the National Academy of Sciences. 109(10):3784-3789. PDF. 2012.
Template-based protein structure modeling using TASSERVMT. Proteins: Structure, Function, and Bioinformatics. 80(2):352-361. PDF. 2012.
GOAP: A Generalized Orientation-Dependent, All-Atom Statistical Potential for Protein Structure Prediction. Biophysical Journal. 101(8):2043-2052. PDF. 2011.
New benchmark metrics for protein-protein docking methods. Proteins: Structure, Function, and Bioinformatics. 79(5):1623-1634. PDF. 2011.
FINDSITE-metal: Integrating evolutionary information and machine learning for structure-based metal-binding site prediction at the proteome level. Proteins: Structure, Function, and Bioinformatics. 79(3):735-751. PDF. 2011.
The utility of geometrical and chemical restraint information extracted from predicted ligand-binding sites in protein structure refinement. Journal of Structural Biology. 173(3):558-569. PDF. 2011.
Brownian dynamics simulation of macromolecule diffusion in a protocell. Proceedings of the International Conference of the Quantum Bio-Informatics IV. 28:413-426. PDF. 2011.
Why not consider a spherical protein? Implications of backbone hydrogen bonding for protein structure and function Physical Chemistry Chemical Physics. 13 (38):17044-17055. PDF. 2011.
Crowding and hydrodynamic interactions likely dominate in vivo macromolecular motion. Proceedings of the National Academy of Sciences of the United States of America. 107:18457-18462. PDF Supplementary Data. 2010.
iAlign: a method for the structural comparison of protein-protein interfaces. Bioinformatics (Oxford, England). 26(18):2259-65. PDF Supplementary Data. 2010.
PSiFR: an integrated resource for prediction of protein structure and function. Bioinformatics (Oxford, England). 26(5):687-8. PDF. 2010.
Structural space of protein-protein interfaces is degenerate, close to complete, and highly connected. Proceedings of the National Academy of Sciences of the United States of America. 107(52):22517-22. PDF Supplementary Data. 2010.
Q-Dock(LHM): Low-resolution refinement for ligand comparative modeling. Journal of computational chemistry. 31(5):1093-105. PDF. 2010.
Cross-Reactivity Virtual Profiling of the Human Kinome by X-ReactKIN: A Chemical Systems Biology Approach. Molecular Pharmaceutics. 7(6):2324–2333. PDF. 2010.
Comprehensive structural and functional characterization of the human kinome by protein structure modeling and ligand virtual screening. Journal of Chemical Information and Modeling. 50:1839-1854. PDF. 2010.
TASSER_low-zsc: An approach to improve structure prediction using low z-score ranked templates. Protiens. 78(13):2769-2080. PDF. 2010.
TASSER_WT: A protein structure prediction algorithm with accurate predicted contact restraints for difficult protein targets. Biophysical Journal. 99(9):3066-75. PDF Supplementary Data. 2010.
The continuity of protein structure space is an intrinsic property of proteins. Proceedings of the National Academy of Sciences of the United States of America. 106(37):15690-5. PDF. 2009.
A threading-based method for the prediction of DNA-binding proteins with application to the human genome. PLoS computational biology. 5(11):e1000567. PDF Supplementary Data. 2009.
From nonspecific DNA-protein encounter complexes to the prediction of DNA-protein interactions. PLoS computational biology. 5(3):e1000341. PDF. 2009.
FINDSITE: a threading-based approach to ligand homology modeling. PLoS computational biology. 5(6):e1000405. PDF. 2009.
FINDSITE: a combined evolution/structure-based approach to protein function prediction. Briefings in bioinformatics. 10(4):378-91. PDF. 2009.
EFICAz2: enzyme function inference by a combined approach enhanced by machine learning. BMC bioinformatics. 10:107. PDF. 2009.