Electrostatic properties of human beta defensin-2Nic Novak, Chris Kieslich, Dimitrios Morikis
Biomolecular Modeling and Design Laboratory, Department of BioengineeringUniversity of California, Riverside
Summer 2008
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
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)
Sequence comparison• HβD 1-6:
• HβD 1-3:
• HβD 4-6:
Analysis performed with ClustalW (www.ebi.ac.uk/clustalw)
• HβD 1-6 (5 dropped):
Disulfide bonds
Structure comparisonHβD-1 HβD-2 HβD-3
Human beta defensin models showing secondary structure in addition to point-representation of basic, acidic, polar, and
nonpolar residues.
+4 +6 +11
PDB: 1KJ5 PDB: 1FD3 PDB: 1KJ6
Structure comparison
(Above) The locations of the 3 disulfide bonds that connect the 6 conserved
cysteines in HβD-1, HβD-2, and HβD-3.
(Left) Superimposed models of HβD-1, HβD-2, and HβD-3.
HβD-1 HβD-3 HβD-2 HβD-3
Antimicrobial Action• Antimicrobial peptides (AmPs)
– Gram-negative and gram-positive bacteria– Fungi– Some viruses
• Shai-Matsuzaki-Huang Mechanism1. Accumulation of defensin on microbial membrane due
to electrostatic interactions2. Insertion into outer leaflet causing stress3. Destabilization of microbial membrane
Internal space of
bacteria
HβD-2 (+6 net charge)
Outside of bacterial cellBilayer image from Shental-
Bechor et al.
Negatively charged bacterial membrane
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)
UCRESI Protocol• Unpublished protocol developed at BioMoDeL• A series of Python and Perl scripts• Created EZ-UCRESI, a GUI wrapper for the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:
Parent PDB
Generate mutant PDB files
Generate PQR files
Generate DX files
Calculate ESIs
Calculate distances
OutputProtein Data Bank
WHATIF
PDB2PQR
APBS
Perl script
Perl script
MATLAB & PyMOL
Cluster Analysis (Sets 09-17)Analysis of all 90 Princeton mutants together
Cluster Analysis (Sets 09-17)Analyses of individual sets
Mutant set 14Flexible template from MD simulations with explicit solvation
0° 90° 180° 270° Charge
Isopotential contours
+6
+6
+6
+7
+6
+5
+5
+5
+5
+5
+5
Sequence selection: weighted average model
Max mutations: 10
Mutant set 14Par. 1
G2I
3G
4D
5P
6V
7T
8C
9L
10K
11S
12G
13A
14I
15C
16H
17H
18V
19F
20C
ID2 R R I
ID3 R I
ID4 N M
ID5 N I
ID6 N I
ID7 R F
ID8 Q R F
ID9 N I
ID10 N I
ID11 N I
Par. 21P
22R
23R
24Y
25K
26Q
27I
28G
29T
30C
31G
32L
33P
34G
35T
36K
37C
38C
39K
40P
ID2 I I L R W W L
ID3 I I L Q R W W L
ID4 I F L N R W W L
ID5 V I L N R W W L
ID6 I I L Q R W W Y
ID7 I F L N R W W Y
ID8 I F L R W W L
ID9 Y I L N R W W L
ID10 I F L Q R W W L
ID11 Y F L N R W W L
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
Alanine Scans of HβD1-3
+6
+4
+11
*
*
**
Alanine Scan of HβD1
0° 90° 180° 270° Charge
Isopotential contours
+4
+5*
Alanine Scan of HβD2
0° 90° 180° 270° Charge
Isopotential contours
+6
+7
*
Alanine Scan of HβD3
0° 90° 180° 270° ChargeIsopotential contours
+11
+12+12
**
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.
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
AcknowledgementsThe BioMoDeL lab membersOur Princeton collaborators
Jun Wang and the BRITE program
Bioengineering
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 Clin Immunol. 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.
Questions?