Faculty Profile

Areas of Research: receptor-ligand recognition in the immunological synapse; protein structure modeling and design; transcription factor recognition of cognate DNA binding sites; modeling of gene regulatory networks;

Professional Interests

Molecular basis of receptor-ligand recognition in the Immunological Synapse

Our long-term goal is to understand the principles underlying molecular recognition and selectivity at the immunological synapse through a multi-disciplinary program exploiting complementary computational and experimental approaches. These studies are essential to (i) understand the molecular basis of normal immune function associated with IgSFs; (ii) define the mechanisms underlying IgSF-associated dysfunction and disease, and (iii) define strategies to re-engineer IgSF receptor:ligand interactions for the realization of surgically defined mutants with altered affinities and selectivities, which can act as biologic drugs

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 chemical 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.

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.

Selected Publications

 Gil N, Fiser A
The choice of sequence homologs included in multiple sequence alignments has a dramatic impact on evolutionary conservation analysis.
Bioinformatics
(2018) ,06:27

Gil N, Fiser A
Identifying Functionally Informative Evolutionary Sequence Profiles.
Bioinformatics
(2018) 34:8, 1278-1286

Yap EH, Fiser A
ProtLID, a Residue-Based Pharmacophore Approach to Identify Cognate Protein Ligands in the Immunoglobulin Superfamily.
Structure
(2016) 24(12) : 2217-2226

Dybas JM, Fiser A
Development of a motif-based topology-independent structure comparison method to identify evolutionarily related folds.
Proteins
(2016) 84(12) : 1859-1874

Vallat B, Madrid-Aliste C, Fiser A
Modularity of Protein Folds as a Tool for Template-Free Modeling of Structures.
PLoS Comput Biol
(2015) 11(8) : e1004419

Pujato M, Kieken F, Skiles AA, Tapinos N, Fiser A.
Prediction of DNA binding motifs from 3D models of transcription factors; identifying TLX3 regulated genes.
Nucleic Acids Res
(2014);4222:13500-12

Khafizov K, Madrid-Aliste C, Almo SC, Fiser A
Trends in structural coverage of the protein universe and the impact of the Protein Structure Initiative.
Proc Natl Acad Sci U S A
(2014) 111(10) : 3733-8

Yap EH, Rosche T, Almo S, Fiser A
Functional clustering of immunoglobulin superfamily proteins with protein-protein interaction information calibrated hidden markov model sequence profiles.
J Mol Biol
(2014) 426(4) : 945-61

Rubinstein R, Ramagopal UA, Nathenson SG,Almo SC, Fiser A
Functional classification of immune regulatory proteins.
Structure
(2013) 21(5): 766-76

Menon V, Vallat BK, Dybas JM, Fiser A
Modeling proteins using a super-secondary structure library and NMR chemcial shift information.
Structure (2013) 21(6): 891-9

Fajardo E, Fiser A
Proteins structure based prediction of catalytic residues.
BMC Bionformatics (2013) 14(63)

Pujato M, MacCarthy T, Fiser A, Bergman A.
The underlying molecular and network level mechanism in the evolution of robustness in gene regulatory networks.
Plos Comput. Biol. (2013) 9(1)

Fernandez-Fuentes N, Fiser A
A modular perspective of protein structures: application to fragment based loop modeling.
Methods Mol. Biol (2013) 932: 141-58

 

More Information About Dr. Andras Fiser

Lab Web Page

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Albert Einstein College of Medicine
Michael F. Price Center
1301 Morris Park Avenue , Room 453A
Bronx, NY 10461

Tel: 718.678.1068

Research Information