Modeling protein structures, designing novel folds
We are developing a computational approach to model proteins for which a limited number of experimental restraints are available. We utilize our recently developed fragment library of supersecondary structure elements (Smotifs) that was shown to have saturated almost 10 years ago. We hypothesize that all protein folds should be possible to build from this library. We are developing algorithms that take advantage of NMR checial shift information to identify a subset of Smotifs that form a protein and setting up optimization approaches that will rapidly assemble overlapping Smotifs into compact folds.
Structural genomics (Structural basis of receptor ligand interactions.)
As members of the New York Structural Genomics Center and the Immune Function Network we are exploring a variety of biomedical topics from a structral biology point of view. We are particularly interested in the cell surface costimulatory and inhibitory immunoglobulin superfamily proteins that effect immunity and tolerance responses. We are interested in understanding of the molecular level recognition mechanisms of these receptor ligand systems.
Evolution of robustness in gene networks (Protein-DNA interactions, structure based prediction of DNA binding motifs.)
Previous research has shown gene regulatory networks are robust to perturbations at the level of the connections between transcription factors. We investigate the mechanisms underlying the evolution of robustness in gene networks using a modeling approach, which considers three levels: binding of individual transcription factors to DNA, dynamics of gene expression levels, and fitness effects at the population level.
Fernandez-Fuentes N, Dybas JM, Fiser A
Structural characteristics of novel protein folds.
PLoS Comput Biol (2010) 6(4) : e1000750
Rykunov D, Fiser A
New statistical potential for quality assessment of protein models and a survey of energy functions.
BMC Bioinformatics (2010) 11, 128
Template-based protein structure modeling.
Methods Mol Biol (2010) 673, 73-94
Rykunov D, Steinberger E, Madrid-Aliste CJ, Fiser A
Improved scoring function for comparative modeling using the M4T method.
J Struct Funct Genomics (2009) 10(1) : 95-9
Madrid-Aliste CJ, Dybas JM, Hogue Angeletti R, Weiss LM, Kim K, Simon I, Fiser A
EPIC-DB: a proteomics database for studying Apicomplexan organisms.
BMC Genomics (2009) 10(1) : 38
Rubinstein R, Fiser A
Predicting disulfide bond connectivity in proteins by correlated mutations analysis.
Bioinformatics (2008) 24(4) : 498-504
Dybas JM, Madrid-Aliste CJ, Che FY, Nieves E, Rykunov D, Angeletti RH, Weiss LM, Kim K, Fiser A
Computational Analysis and Experimental Validation of Gene Predictions in Toxoplasma gondii.
PLoS ONE (2008) 3(12) : e3899
Fernandez-Fuentes N, Rai BK, Madrid-Aliste CJ, Fajardo JE, Fiser A
Comparative protein structure modeling by combining multiple templates and optimizing sequence-to-structure alignments.
Bioinformatics (2007) 23(19) : 2558-65
Feyfant E, Sali A, Fiser A
Modeling mutations in protein structures.
Protein Sci (2007) 16(9) : 2030-41
Rykunov D, Fiser A
Effects of amino acid composition, finite size of proteins, and sparse statistics on distance-dependent statistical pair potentials.
Proteins (2007) 67(3) : 559-68
Rai BK, Fiser A
Multiple mapping method: a novel approach to the sequence-to-structure alignment problem in comparative protein structure modeling.
Proteins (2006) 63(3) : 644-61
Fernandez-Fuentes N, Oliva B, Fiser A
A supersecondary structure library and search algorithm for modeling loops in protein structures.
Nucleic Acids Res (2006) 34(7) : 2085-97
Fernandez-Fuentes N, Fiser A
Saturating representation of loop conformational fragments in structure databanks.
BMC Struct Biol (2006) 6, 15
Rai BK, Madrid-Aliste CJ, Fajardo JE, Fiser A
MMM: a sequence-to-structure alignment protocol.
Bioinformatics (2006) 22(21) : 2691-2
More Information About Dr. Andras Fiser
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Albert Einstein College of Medicine
Michael F. Price Center
1301 Morris Park Avenue , Room 453A
Bronx, NY 10461