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Forschungsarbeit

3D Protein complexes from evolutionary sequence variation

By Thomas Hopf (18.07.2013)

The evolution of a protein sequence is constrained by the need to maintain its biological function. Collections of homologous sequences in a protein family contain a rich record of these evolutionary constraints. In particular, the pressure to maintain favorable interactions between amino acids leaves a visible footprint of residue covariation across the family (Fig. 1).

[Bildunterschrift / Subline]: Figure 1. Extracting evolutionary couplings from the sequence record to predict the 3D structure of proteins.

The calculation of evolutionary couplings between residues is a difficult challenge, however, because the causative pattern of covariation has to be uncovered within the observed data which is full of transitive, non-causative correlations. These obstacles have been overcome by the advent of high-throughput genomic sequencing and improved statistical methods, which have enabled us to reliably identify directly covarying residue pairs which are close in 3D space [1]. Surprisingly, the information contained in these pairs is sufficient to predict the 3D fold of proteins from amino acid sequences alone (Fig. 1). In subsequent work, we have also shown that evolutionary couplings can be used to predict the 3D structures of transmembrane proteins which have not been experimentally solved yet [2]. Besides structure, our method EVfold uncovers potential multimerization sites, conformational changes in transporters and functionally important residues e.g. in active sites.

[Bildunterschrift / Subline]: Figure 2. Protein-protein complex interaction of ATP synthase subunits gamma (blue) and epsilon (green) predicted from evolutionary sequence variation.

In our current work, we go one step beyond single protein structures and investigate the coevolution of residues across protein-protein interactions. Evolutionary couplings calculated between the interacting monomers in the complex accurately capture the proximal amino acids and can be used to reconstitute the full complex by molecular docking to approx. 1-2 Å backbone root mean square deviation (Fig. 2). Besides these preliminary results, we now aim to find answers to other open questions: Can we predict protein specificity and plasticity? Can we use evolutionary couplings across proteins to identify interaction partners and relative binding affinities? How do genetic mutations interfere with the correct association of protein complexes or information transmission in cancer?

In summary, we anticipate that our work on evolutionary couplings will shed more light on crucial aspects of protein evolution, and may therefore help to gain a better understanding of the basic principles governing life and disease on the molecular level.

References:

[1] Marks D.S., Colwell L.J., Sheridan R., Hopf T.A., Pagnani A., Zecchina R., Sander C. (2011): Protein 3D structure computed from evolutionary sequence variation. PLoS ONE e6(12): 28766. 

[2] Hopf T.A., Colwell L.J., Sheridan R., Rost B., Sander C., Marks D.S. (2012). Three-dimensional structures of membrane proteins from genomic sequencing. Cell 149 (7), 1607-21.

[3] Marks D.S., Hopf T.A., Sander C. (2012). Protein structure prediction from sequence variation. Nature Biotechnology 30 (11), 1072-80.


mailto: Thomas Hopf
Thomas Hopf
* 1986

Scientific career
  • 2006-2009
  • Bachelor studies in Bioinformatics, LMU & TU munich
  • 2009-2012
  • Master studies in Bioinformatics, LMU & TU Munich
  • 2012-today
  • PhD in computational biology, supervised by Dr. Debora Marks (Harvard Medical School), in the lab of Prof. Dr. Burkhard Rost at TUM

Awards and Scholarships
  • 2006-2012
  • Scholarship of the State of Bavaria for gifted students (Max Weber-Programm)
  • 2009-2012
  • Scholarship of the German National Academic Foundation (Studienstiftung des deutschen Volkes)

Publications (Excerpt)
  • * Marks D.S., Hopf T.A., Sander C. (2012). Protein structure prediction from sequence variation. Nature Biotechnology 30 (11), 1072-80.
  • * Hopf T.A., Colwell L. J., Sheridan R., Rost B., Sander C., Marks D. S. (2012). Three-dimensional structures of membrane proteins from genomic sequencing. Cell 149 (7), 1607-21.
  • * Hopf T.: Membrane Protein 3D Structure from Sequence Alone (2012). Master's Thesis, Technische Universität München.