Faculty Profile

Address:
701 West 168 Street
Room 217
New York, NY 10032

Phone: 212-305-3773

rost@columbia.edu

Affiliations
Department of Biochemistry & Molecular Biophysics
Biomedical Informatics

Training Activities
Integrated Program in Cellular, Molecular and Biophysical Studies
MD/PhD Program

Research Summary
Bioinformatics. Goals: sequence analysis, prediction of protein structure and function. Means: statistics and artificial intelligence

Dr. Rost's Laboratory

We try to predict aspects of protein structure and function from the evolutionary information contained in families of protein sequences. The main current projects are to (1) predict functional classes for orphans, (2) the sub-cellular localisation from sequence, and (3) protein-protein, and protein-substrate interactions from sequence and predicted structure. We also continue to work on structure prediction. Particular goals are: (1) Improve predictions for secondary structure, solvent accessibility, transmembrane proteins, (2) develop methods predicting residue-residue distances, and (3) improve methods that allow to model the 3D structure for proteins that have distant homologues of known structure (threading). Additionally, we work on describing and clustering the space of protein sequences and structures in context of structural genomics. Recently, we have analysed proteins with non- regular structures in detail.

Both in order to accomplish our goals in bioinformatics and to make our methods available, we maintain local copies of most relevant sequence databases. We also maintain a variety of servers that assist biologists in their every day sequence analysis: PredictProtein, META-PP, EVA, PredictNLS. Finally, we are working on a database that collects predictions and alignments for all entirely sequenced organisms. The technical means we apply range from scanning literature, over simple statistical methods, to methods from artificial intelligence (neural networks, hidden Markov models, or genetic algorithms).

Selected Publications

1. Wrzeszczynski KO, Rost B. Cataloging proteins in cell cycle control.
Methods Mol Biol. 2004;241:219-33.

2. Rost B, Liu J, Nair R, Wrzeszczynski KO, Ofran Y. Automatic prediction of protein function. Cell Mol Life Sci. 2003 Dec;60(12):2637-50. Review.

3. Nair R, Rost B. Better prediction of sub-cellular localization by combining evolutionary and structural information. Proteins. 2003 Dec 1;53(4):917-30.

4. Eyrich VA, Przybylski D, Koh IY, Grana O, Pazos F, Valencia A, Rost B. CAFASP3 in the spotlight of EVA. Proteins. 2003;53 Suppl 6:548-60.

5. Liu J, Rost B. NORSp: Predictions of long regions without regular secondary structure. Nucleic Acids Res. 2003 Jul 1;31(13):3833-5.

6. Mika S, Rost B. UniqueProt: Creating representative protein sequence sets. Nucleic Acids Res. 2003 Jul 1;31(13):3789-91.

Current Projects

1. Predictions of structure/function by PredictProtein
Here, we propose a variety of technical and scientific solutions improving the functionality of PredictProtein. (1) The technical solutions address job and data handling, database update, user interface, web page layout, presentation of results, and directly linking original resources. (2) The systematic combination of methods requires evaluating these in parallel on identical tasks, e.g., at which level of probability should a signal peptide prediction override the membrane prediction. Our major focus will be on improving predictions for membrane helical proteins, developing methods predicting beta-membrane proteins, and on using structure predictions to more accurately infer functional information.
National Library of Medicine
5/2003-4/2007

2. Predicting putative protein-protein interface segments
We propose to develop methods predicting interface segments, i.e. regions of residues consecutive in sequence that are in contact with other interface segments. We propose separate methods for internal and external interfaces. We have recently shown that internal, chain-chain, and protein-protein interface segments differ - on average. Thus, our first aim is to predict the interface type based on a combination of sequence features and predicted properties (secondary structure, accessibility, and post-translational modifications). Such a prediction will already provide the first hint for functional regions, and it will simplify the next step. The second aim will be to develop a system that suggests possible protein-protein interaction partners, as well, as putative oligomer interfaces. The third goal will be to develop new methods that predict distances between internal interfaces. This final step will hopefully complement the prediction of external interfaces and will assist methods predicting protein structure.
National Institute of General Medical Sciences
5/2003-4/2007

3. Intruding into the midnight zone of protein comparisons
Here, we propose to refine, extend, and specialise methods combining sequence alignment, structure prediction and functional information. Goal is to unravel hidden similarities in entirely sequenced organisms by a reliable, automatic tool. Towards the end of our project, the sequences for most protein families realised by life will supposedly be available.
National Institute of General Medical Sciences
4/2001-3/2005

Committee, Council, Professional Society Memberships

Keywords
Internet, computer system design /evaluation, informatics, information system, protein structure function, enzyme activity, membrane protein, protein signal sequence, protein structure, artificial intelligence, chemical model, method development, protein binding, protein protein interaction, protein sequence, automated data processing, computer simulation, molecular biology information system, proteomics, structural biology, DNA binding protein, binding site, biochemical evolution, chemical chain length, conformation, data management, functional /structural genomics, molecular dynamics, statistics /biometry