1 / 7

Computational Biophysics and Bioinformatics lab

Computational Biophysics and Bioinformatics lab. Predicting protein-protein interactions and the corresponding 3D structures of protein-protein complexes by homology. Using the 3D structures to compute biophysical characteristics. Emil Alexov http://www.ces.clemson.edu/compbio.

toan
Download Presentation

Computational Biophysics and Bioinformatics lab

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Computational Biophysics and Bioinformatics lab Predicting protein-protein interactions and the corresponding 3D structures of protein-protein complexes by homology. Using the 3D structures to compute biophysical characteristics Emil Alexov http://www.ces.clemson.edu/compbio

  2. From Genes  Proteins  Protein-protein complexes

  3. A B AB Modeling biophysical characteristics of protein-protein interactions Part A. Salt dependence of protein-protein binding mobile ions – red – negative charge, blue – positive charge • Two questions to be addressed: • (a) Linear vs non-linear Poisson-Boltzmann equation • (b) Possible correlations in respect to macroscopic characteristics • net charge, interfacial area, charge at the interface etc…

  4. Part A. Salt dependence of protein-protein binding - - hetero homo ● ● ● ● slope ln(I)

  5. Part B. Parameter dependence of protein-protein binding Protein dielectric constant dependence Hetero Homo

  6. Part B. Parameter dependence of protein-protein binding Force field dependence • Conclusions: • Very good correlations • Quite many outliers

  7. Acknowledgements Kemper Talley, Undergraduate student, Department of Physics and Astronomy Petras Kundrotas – Senior Scientist, Center for Bioinformatics, Kansas Univ. Radhey Shyam – PhD student, Department of Physics and Astronomy Shaolei Teng – PhD student, Department of Biochemistry and Genetics Rooplekha Mitra – PhD student, Department of Physics and Astronomy Indranil Mitra – PhD student, Department of Mathematical Sciences The minimization of the structures used in this work was made possible by a Condor pool deployed and maintained by Clemson Computing and Information Technology. The authors would like to acknowledge the support of the staff from the Cyber Infrastructure Technology Integration group, especially Barr Von Oehsen. We thank Barr Von Oehsen and Matt Salzmann for the help with Axiom cluster We thank Murray Daw for the help with Augustine cluster This research was supported by an award to Clemson University from the Howard Hughes Medical Institute Undergraduate Science Education Program. We thank Eureka program.

More Related