1. By Kaila Bennett, Amitoj Chopra, Jesse Johnson, Enrico Sagullo
Development of Software Package for Determining Protein Titration Properties Final Presentation Winter 2010 By
Kaila Bennett, Amitoj Chopra, Jesse Johnson, Enrico Sagullo

2. Background
Electrostatic interactions are very important for the function of proteins which include:
Binding
Enzymatic catalysis
Conformational transitions
Electrostatic Interaction
Stability
Ionizable amino acids
Electrostatic interactions
Salt Bridges
Dipole-Dipole
Columbic interaction
Facilitate interactions with aqueous environments
Mediate polar contributions biological processes
Binding
Catalysis
Goes in first bullet
protein ligand interaction
Function communication
Protein protein ligand interaction
With ligands and memebrane
2nd bullet
Ionizable amino acids salt bridges depending on pka to donate or extract protons and salt bridge
Protein stability function
Polar exterior polar contribte to sufrace property to facilitate the surface solvent
Depicts electrostatic potential (isopotential contour) red represents the negative, and the blue represent the positive

3. Background
Functions of proteins such as catalysis are dependent on protonation state of ionizable amino acid residues
pKa for a single amino acid is 50% protonation
pKa values are environment dependent
The environment may cause shifts in pKa
pKa values are important for understanding many biological processes
pKa intrinsic - pKa for one amino acid pKa apparent- pKa of the entire protein
Individaul 50% neutral, and 50% charge of specific amino acid residues
Asparagine- as the example
For calculation we have 2 pka intrinisic is a intermediate to calculate the apparent.

4. Catalysis
Asp102 of Chymotrypsin – hydrogen bond with His57 – increases pKa
His57 can accepts proton from Ser195 – activates serine protease for cleavage of substrate
pKa shift important for each chemical reaction in catalytic mechanism
Necessary to donate and abstract protons from neighboring groups
Without pKa shift of His57, catalysis would not be possible!

5. From S.Fischer et al, Proteins 2009
Salt Bridge
pKa shifts also effect intermolecular salt bridges
Salt bridges are short range, Columbic interactions that occur between two ionizable amino acid residues
From S.Fischer et al, Proteins 2009

6. Figure: Morikis et al, Protein Sci 2001
Conformation Change
Another important biological process that is dependent on pKa of the environment is transition states of proteins
Conformational switch
Figure: Morikis et al, Protein Sci 2001

7. Binding

8. Background Linearized Poisson-Boltzmann Equation (LPBE) ε high ε low
Electrostatic Free Energies
ε high
ε low
ε surface
κ surface
ε: Dielectric coefficient
κ: Ion accessibility function
I: Ionic strength
q: Charge
φ: Electrostatic potential
κ = 0
Question how do we get to solve for g and why we are using background on ABPS
κ ≠ 0
Background Charges
Solvent Charges
Partial Charges (Electric dipoles)
Courtesy of C. Kieslich

9. Background
Intrinsic pKa calculation by the free energies of the thermodynamic cycle
Thermodynamic cycle has four proposed states:
1-Neutral to charge of bound
2-Bound charge to amino acid
3-Neutral to charge free
4-Bound neutral to amino acid
This method also allows for calculation free energy values
Ultimately allowing for the elucidation of intrinsic pKa values and titration curves 1 4 2 3

10. Background Adapted from lecture notes of Bioengineering 135
Figure: Courtesy of Morikis et al
Adapted from lecture notes of Bioengineering 135

11. Background (PDB file)
The Protein Data Bank (PDB) archive is the single worldwide repository of proteins.
A PDB file is a downloadable file from the databank that contains all the necessary information about a protein needed for 3-D modeling and our calculations.

12. Background These modifications include:
PDB
PQR
APBS
Background
These modifications include:
Adding a limited number of missing heavy atoms
Placing polar hydrogen's
Optimizing the protein for favorable hydrogen bonding
Removing unfavorable van der Waals clashes (when two atoms try to occupy the same space)
Assigning charge ( partial or whole) and van der Waals radii parameters from a variety of force fields

13. Figure: Test case protein 1LY2
Rationale
Developing a software package that not only incorporates APBS to calculate free energies but also calculate protein titration characteristics, will help ultimately aid to elucidate proteins stability, catalysis, salt bridges, binding
Figure: Test case protein 1LY2

14. Experimental Procedure (So Far)
Make Two PDB files neutral and charged
Two PDB’s are made to be incorporated into free energy calculations
One neutral PDB that contains all the amino acids in their neutral forms
One Charged PDB that contains all the amino acids in their charged forms
PDB to PQR
Take cleaned PDB file and covert file to a PQR file to make compatible with APBS software
Obtain PDB to PQR converter
Use python to call the converter from R
System call from R to convert file
Generate four states of TC
Charged and Neutral PQR’s are combined and trimed to make the four states of the Thermodynamic Cycle
Each ionizable amino acid are placed within the neutral to leave one charged and the rest neutral to make the first state
The charged and neutral amino acids by themselves correspond to two of the states
The last state is the neutral PQR by itself
Call of APBS
Newly converted PQR were taken for energy calculations using APBS software
Make four PQR files to correlate to the four states in the Thermodynamic Cycle
Develop a template input file which will be edited through scripts to make a specific input file
Template was read in, edited and then written into a new input file
Use system call with new input file to calculate free energies using APBS
Calculate intrinsic pKa
Each ΔG value is used to calculate the pKa of its corresponding residue
The ΔG values are first divided by thermo energy then subtracted by the model pKa

15. Experimental Parameters
Ionic strength
Dielectric solvent (εlow)
Dielectric
Solute
(εhigh)
Temp
150.0 mM
80.0
20.0 K
Box Size (Å) X Y Z
fglen
100
cglen
Grid size
129

16. Results (PDB2PQR) Code (General) :
$ python pdb2pqr.py [options] --ff={forcefield} {path} {output-path}
Forcefield
Path
Output_path
Code used in program:
system("python /Users/senior_design/pdb2pqr-1.5/pdb2pqr.py --ff parse 1LY2.pdb 1LY2.pqr")
Using PARSE to give van der Waal radii and atomic charge
Where the file is located
Where the PQR file are to be generated
Figure: Protein 1LY2

17. Results ( Neutral and Charge)
Neu_Char_pdb <- function(pdb) {
x <- pdb
x$atom[atom.select(x, resid = "ASP" )$atom,4]<-sub("ASP", "ASH", x$atom[atom.select(x, resid = "ASP" )$atom,4])
x$atom[atom.select(x, resid = "GLU" )$atom,4]<-sub("GLU", "GLH", x$atom[atom.select(x, resid = "GLU" )$atom,4])
x$atom[atom.select(x, resid = "LYS" )$atom,4]<-sub("LYS", "LYN", x$atom[atom.select(x, resid = "LYS" )$atom,4])
x$atom[atom.select(x, resid = "ARG" )$atom,4]<-sub("ARG", "AR0", x$atom[atom.select(x, resid = "ARG" )$atom,4])
write.pdb(pdb = x,file = "1ly2_neutral”
Generates the neutral and charged PDB’s
The newly generated PDB’s will be incorporated into the calculation of free energies

18. Results (Call APBS Script)
con <- file("apbs_template.in", "r")
in_file <- readLines(con)
close(con)
bdp_file <- “1LY2_noGLU35.pqr"
bp_file <- “1LY2_GLU35.pqr"
fdp_file <- "GLU35_no.pqr"
fp_file <- "GLU35.pqr"
length <- 100
width <- 100
height <- 100
in_file[2] <- paste(" mol pqr ",bdp_file, sep = "")
in_file[3] <- paste(" mol pqr ",bp_file, sep = "")
in_file[4] <- paste(" mol pqr ",fdp_file, sep = "“)
in_file[5] <- paste(" mol pqr ",fp_file, sep = "")
in_file[11] <- paste(" cglen ",length,width,height, sep = " ")
in_file[12] <- paste(" fglen ",length,width,height, sep = " ")
in_file[34] <- paste(" cglen ",length,width,height, sep = " ")
in_file[35] <- paste(" fglen ",length,width,height, sep = " ")
in_file[57] <- paste(" cglen ",length,width,height, sep = " ")
in_file[58] <- paste(" fglen ",length,width,height, sep = " ")
in_file[80] <- paste(" cglen ",length,width,height, sep = " ")
in_file[81] <- paste(" fglen ",length,width,height, sep = " ")
con <- file("infile.in","w")
writeLines(in_file,con,sep = "\n")
TC <- system(paste( "/apbs-1.2-mac-univ/bin/apbs", "infile.in",">", "outfile.txt", sep = " "))
Reads in our input template
Four PQR files which correspond to each state of TC
Writes a new input file with our specific parameters
System call to APBS to use new input file and calculate free energies

19. Results (Free Energy Calc.)
k <- ( as.numeric(neutral_pqr$atom[1,"resno"]) )
end_of_seq <- length(seq.pdb(neutral_pqr) ) - 1
seq <-our_seq(LY2, end_of_seq)
AAdf <- NULL
Indexing
for ( i in seq ) {
if ( i == "R" | i == "K" | i == "H" | i == "C" | i == "Y"
| i == "D" | i == "E" )
Before <- trim.pdb( neutral_pqr, atom.select(neutral_pqr, resno = 1:( k - 1 ) ) )
Free_protonated <- trim.pdb( charged_pqr,atom.select (charged_pqr, resno = k ) )
After <- trim.pdb( neutral_pqr, atom.select (neutral_pqr, resno = (k+1): end_of_seq ) )
Free_deprotonated <- trim.pdb( neutral_pqr, atom.select(neutral_pqr, resno = k))
write.pqr(Free_protonated, file = "Free_protonated.pqr")
Before_FP <- cat_pdb( Before, Free_protonated )
Total <- cat_pdb(Before_FP, After)
write.pqr(Total, file = "Bound_Protonated.pqr")
write.pqr(Free_deprotonated, file = "Free_deprotonated.pqr")
bp <- read.pqr("Bound_Protonated.pqr")
bdp <- read.pqr("1ly2_neutral.pqr")
fp <- read.pqr("Free_protonated.pqr")
fdp <- read.pqr("Free_deprotonated.pqr")
delta_G <- call_apbs(in_file)
AAdf <- rbind(AAdf, c("Resid"=i,"Resno" = k+1,"delta_G"=delta_G)) }
k <- k + 1
For loop to run through sequence one amino acid at a time
Calls APBS for every ionizable amino acid to calculate specific ΔG values

20. Results (Intrinsic pKa)
Protein 1LY2
Residue
Average ΔG (kJ/mole)
Average pKa
Arginine
-50.21
20.79
Aspartic Acid
-50.29
12.71
Cystine
-50.30
17.09
Glutamic Acid
-48.86
12.86
Histidine
-47.94
14.28
Lysine
19.31
Tyrosine
-46.51
18.24

21. Values courtesy of H++ software
Discussion
We believe that our ΔG values may be off by a order of magnitude
If the ΔG values are off by a order of magnitude, this would throw off our pKa values as well
Complete evaluation of all scripts will done to see if our scripts are running the right calculations
Special evaluation will be done on APBS template file
pKa are off because free energies are off
But we do see that the acidic amino acid residues pKa’s are lower then basic amino acid residues pKa’s
pKa values from established software with same parameters yield
Arginine = 10.7
Aspartic Acid = 3.1
Cystine = N/A (software doesn’t recognize cystine as ionizable)
Glutamic Acid = 2.6
Histidine = 5.2
Lysine = 10.9
Tyrosine = 9.6
Values courtesy of H++ software

22. Progress Tracker (Winter)

23. Future work
Perform test calculations for 1,2,3 and m (goes first)

24. Conclusion
Developed and refined scripts that took in PDB files and converted them to neutral and charged PQR files
Developed and refined scripts that took neutral and charged PQR files and generated files that corresponds to the four states of the thermodynamic cycle
Intergrated all codes to run sequentially to calculate free energies and pKa
Successful in taking protein 1LY2 PDB file and calculating intrinsic pKa for all ionizable amino acids of 1LY2

25. Acknowledgments Dr. Dimitrios Morikis Chris Kieslich Ronald Gorham
Dr. Jerome Schultz
Gokul Upadhyayula
Hong Xu
Dr. Thomas Girke

26. References

27. Questions?
Our group would like to mention that no computers were injured in the making of the software package