Introduction

Proteins are in the lowest energy conformation and the process in which they assume this conformation from an extended state is called protein folding. Is is possible to simulate this event using computers and hence predicting a proteins lower energy conformation (native state) using protein structure prediction technologies. The reverse, that is, predicting which sequence best fits a specific structure, is also possible and this is generally referred to as in-silico protein design.

Research

Rosetta is the software suite we use to predict structures and model protein-protein interactions. I have focused on using protein structure prediction to annotate genomes and to predict molecular functions. It is also possible to characterize proteins with great precision, like we did for the DS epimerase. Integrating mass spectrometry (MS) data with de novo protein structure prediction technology can elucidate protein structures fast and cheap with a higher accuracy than using only in silico approaches.

References

Nr.	Reference
11.	Malmstroem, L., Hou, L., Atkins, WM., Goodlett, DR. On the use of hydrogen/deuterium exchange mass spectrometry data to improve de novo protein structure prediction. Rapid Commun Mass Spectrom (2009), 23: 459-461.
10.	Pacheco, B., Maccarana, M., Goodlett, DR., Malmstrom, A., Malmstrom, L. Identification of the active site of DS-epimerase 1 and requirement of N-glycosylation for enzyme function. J Biol Chem (2008), 0: Epub ahread of print.
9.	Das, R., Qian, B., Raman, S., Vernon, R., Thompson, J., Bradley, P., Khare, S., Tyka, MD., Bhat, D., Chivian, D., Kim, DE., Sheffler, WH., Malmstrom, L., Wollacott, AM., Wang, C., Andre, I., Baker, D. Structure prediction for CASP7 targets using extensive all-atom refinement with Rosetta@home. Proteins (2007), 1: 118-128.
8.	Malmstrom, L., Riffle, M., Strauss, CE., Chivian, D., Davis, TN., Bonneau, R., Baker, D. Superfamily Assignments for the Yeast Proteome through Integration of Structure Prediction with the Gene Ontology. PLoS Biol (2007), 5: e76.
7.	Kim, DE., Chivian, D., Malmstrom, L., Baker, D. Automated prediction of domain boundaries in CASP6 targets using Ginzu and RosettaDOM. Proteins (2005), Suppl 7: 193-200.
6.	Chivian, D., Kim, DE., Malmstrom, L., Schonbrun, J., Rohl, CA., Baker, D. Prediction of CASP-6 structures using automated Robetta protocols. Proteins (2005), Suppl 7: 157-66.
5.	Bradley, P., Malmstrom, L., Qian, B., Schonbrun, J., Chivian, D., Kim, DE., Meiler, J., Misura, KM., Baker, D. Free modeling with Rosetta in CASP6. Proteins (2005), Suppl 7: 128-34.
4.	Cazzanti, L., Gupta, M., Malmstrom, L., Baker, D., Quality Assessment of Low Free-Energy Protein Structure Predictions. Machine Learning for Signal Processing, 2005 IEEE Workshop on (2005) 375-380
3.	Hazbun, TR., Malmstrom, L., Anderson, S., Graczyk, BJ., Fox, B., Riffle, M., Sundin, BA., Aranda, JD., McDonald, WH., Chiu, CH., Snydsman, BE., Bradley, P., Muller, EG., Fields, S., Baker, D., Yates, JR., Davis, TN. integration of technologies. Mol Cell (2003), 12: 1353-65.
2.	Chivian, D., Kim, DE., Malmstrom, L., Bradley, P., Robertson, T., Murphy, P., Strauss, CE., Bonneau, R., Rohl, CA., Baker, D. Automated prediction of CASP-5 structures using the Robetta server. Proteins (2003), 53: 524-33.
1.	Bonneau, R., Strauss, C., Rohl, C., Chivian, D., Bradley, P., Malmstrom, L., Robertson, T., Baker, D. De Novo Prediction of Three-dimensional Structures for Major Protein Families. J Mol Biol (2002), 322: 65.