1 / 23

Electrostatic properties of human beta defensin-2

Electrostatic properties of human beta defensin-2. Nic Novak, Chris Kieslich, Dimitrios Morikis Biomolecular Modeling and Design Laboratory, Department of Bioengineering University of California, Riverside Summer 2008. Overview. Characteristics of Defensins Sequence comparison

zohar
Download Presentation

Electrostatic properties of human beta defensin-2

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. Electrostatic properties of human beta defensin-2 Nic Novak, Chris Kieslich, Dimitrios MorikisBiomolecular Modeling and Design Laboratory, Department of BioengineeringUniversity of California, RiversideSummer 2008

  2. Overview • Characteristics of Defensins • Sequence comparison • Structure comparison • Mechanism of antimicrobial action • Main Objective and Defensin Analysis • UCRESI Protocol • Cluster analyses of electrostatic potentials • Alanine scan of all ionizable residues • Results • Conclusions • Future Work • Acknowledgements • References

  3. Characteristics of Defensins • Endogenous in all mammals • Antimicrobial • Short peptides (41-78 AAs) • Multiple varieties • Alpha defensins (4) - Stomach • Beta defensins (6) – Skin, saliva • Features • Conserved cysteines (6) • Cationic (Net positive charge of 4-11) HβD-2 (1FD3)

  4. Sequence comparison Disulfide bonds • HβD 1-6 (5 dropped): • HβD 1-3: • HβD 4-6: HβD 1-6: Analysis performed with ClustalW (www.ebi.ac.uk/clustalw)

  5. Structure comparison HβD-3 HβD-1 HβD-2 +4 +6 +11 PDB: 1KJ5 PDB: 1FD3 PDB: 1KJ6 Human beta defensin models showing secondary structure in addition to point-representation of basic, acidic,polar, and nonpolar residues.

  6. Structure comparison (Left) Superimposed models of HβD-1, HβD-2, and HβD-3. HβD-3 HβD-1 HβD-2 HβD-3 (Above) The locations of the 3 disulfide bonds that connect the 6 conserved cysteines in HβD-1, HβD-2, and HβD-3.

  7. Antimicrobial Action Internal space of bacteria HβD-2 (+6 net charge)Outside of bacterial cell • Antimicrobial peptides (AmPs) • Gram-negative and gram-positive bacteria • Fungi • Some viruses • Shai-Matsuzaki-Huang Mechanism • Accumulation of defensin on microbial membrane due to electrostatic interactions • Insertion into outer leaflet causing stress • Destabilization of microbial membrane Bilayer image from Shental-Bechor et al. Negatively charged bacterial membrane

  8. Mutant Analysis • Objective: predict molecules based on the defensin structure that will have improved antimicrobial action • Analysis of 9 pre-selected sets of HβD-2 mutations (Princeton collaborators) • UCRESI Protocol • Computational, theoretical mutagenesis • Comparison of electrostatic similarity indices (ESIs) • Visualized by dendrograms (cluster analysis)

  9. UCRESI Protocol • Unpublished protocol developed at BioMoDeL • A series of Python and Perl scripts • Created EZ-UCRESI, a GUI wrapper for the protocol, to automate the following tasks: Output Protein Data Bank Parent PDB WHATIF Generate mutant PDB files PDB2PQR Generate PQR files APBS Generate DX files Perl script Calculate ESIs MATLAB & PyMOL Perl script Calculate distances

  10. Cluster Analysis (Sets 09-17)Analysis of all 90 Princeton mutants together

  11. Cluster Analysis (Sets 09-17)Analyses of individual sets

  12. Mutant set 14Flexible template from MD simulations with explicit solvation Sequence selection: weighted average modelMax mutations: 10 Isopotential contours 0° 90° 180° 270° Charge +6 +6 +6 +7 +6 +5 +5 +5 +5 +5 +5

  13. Mutant set 14

  14. Alanine Scans • High-throughput computational protocol • Mutate each ionizable residue into alanine, one at a time, to determine the residue’s effect the peptide’s electrostatic potential • Performed on HβD1-3 • Acidic (-) • Aspartic acid • Glutamic acid • Basic (+) • Arginine • Lysine • Histidine

  15. Alanine Scans of HβD1-3 * +6 * +4 * * +11

  16. Alanine Scan of HβD1 Isopotential contours 0° 90° 180° 270° Charge +5 * +4

  17. Alanine Scan of HβD2 Isopotential contours 0° 90° 180° 270° Charge +7 * +6

  18. Alanine Scan of HβD3 Isopotential contours 0° 90° 180° 270° Charge +12 +12 * * +11

  19. Conclusions • In most cases, the mutations suggested by our collaborators at Princeton and those generated by the alanine scans were predicted to have an equal or lower net charge than their parent protein. • However, a small number of mutants (7/121 = 5.8%) were predicted to have a higher net charge and larger isopotential contours than the parent. • According to the Shai-Matsuzaki-Huang mechanism, these mutants should theoretically exhibit improved attraction to microbial membranes. • Provided that no major structural changes were introduced by the mutations, these mutants should have improved antimicrobial properties.

  20. Future Work • Analyze top 20 mutants (instead of top 10) • Expand mutant sets • Perform additional literature analyses to see what efforts are already in progress for creating synthetic defensins • Synthesize the mutants predicted by these calculations to be the best binders • Perform experimental studies based on these predictions

  21. Acknowledgements The BioMoDeL lab members Our Princeton collaborators Jun Wang and the BRITE program Bioengineering

  22. References • Baker N.A., Sept D, Joseph S, Holst M.J., McCammon J.A. Electrostatics of nanosystems: application to microtubules and the ribosome. Proc. Natl. Acad. Sci. A 98, 10037-10041 2001. (APBS) • ClustalW web service. Available online: http://www.ebi.ac.uk/Tools/clustalw2/index.html • Dolinsky T.J., Nielsen J.E., McCammon J.A., Baker N.A. PDB2PQR: an automated pipeline for the setup, execution, and analysis of Poisson-Boltzmann electrostatics calculations. Nucleic Acids Research 32 W665-W667 (2004). • Fung, H., Floudas, C., Taylor, M., and Morikis, D. (2007). Toward full-sequence de novo protein design with flexible templates for human beta-defensin-2. Biophysical Journal. 94:584-599. • Kisich K.O., Carspecken C.W., Fieve S., Boguniewicz M., Leung D.Y. (2008). Defective killing of Staphylococcus aureus in atopic dermatitis is associated with reduced mobilization of human beta-defensin-3. J Allergy ClinImmunol. 122(1): 62-68. • Krishnakumari V., Nagarj R. (2008). Interaction of antibacterial peptides spanning the carboxy-terminal region of human beta-defensins 1-3 with phospholipids at the air-water interface and inner membrane of E. coli. Peptides. 29(1):7-14. • Krishnakumari V., Singh S., Nagaraj R. (2006). Antibacterial activities of synthetic peptides corresponding to the carboxy-terminal region of human beta-defensins 1-3. Peptides. 27(11):2607-2613. • Shental-Bechor, D., Haliloglu, T., Ben-Tal, N. (2007). Interactions of cationic-hydrophobic peptides with lipid bilayers: A Monte Carlo simulation method. Biophysical Journal. 93:1858-1871. • Yang, J., Kieslich, C., Gunopulos, D., and Morikis, D. (2008). Insights into protein-protein interactions using a high-throughput computational protocol for alanine scans and clustering analyses of the spatial distributions of electrostatic potentials, In Preparation.

  23. Questions?

More Related