Development of Software Package for Determining

Protein Titration Properties

Final Presentation Winter 2010

By

Kaila Bennett, Amitoj Chopra, Jesse Johnson, Enrico Sagullo

BackgroundElectrostatic interactions are very important for the function of proteins which include:

BindingEnzymatic catalysisConformational transitionsElectrostatic Interaction Stability

Ionizable amino acidsElectrostatic interactions

Salt BridgesDipole-DipoleColumbic interaction

Facilitate interactions with aqueous environmentsMediate polar contributions biological processes

Depicts electrostatic potential (isopotential contour) red represents the negative, and the blue represent the positive

BackgroundFunctions of proteins such as catalysis are dependent on protonation state of ionizable amino acid residues pKa for a single amino acid is 50% protonationpKa values are environment dependentThe environment may cause shifts in pKa

pKa values are important for understanding many biological processespKa values are important for understanding many biological processespKa intrinsic - pKa for one amino acidpKa apparent- pKa of the entire protein

0 2 4 6 8 10 12 14-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

Pa

rtia

l ch

arg

e

pH

VCP E108 VCP E120 SPICE K108 SPICE K120

Catalysis

Asp102 of Chymotrypsin – hydrogen bond with His57 – increases pKa

His57 can accepts proton from Ser195 – activates serine protease for cleavage of substratepKa shift important for each chemical reaction in catalytic mechanism

Necessary to donate and abstract protons from neighboring groupsWithout pKa shift of His57, catalysis would not be possible!

Salt BridgepKa 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

Conformation Change

Another important biological process that is dependent on pKa of the environment is transition states of proteins

Conformational switch

+ –

+–+

–

–

+–+–––++

–+

++–

G (neutra l)h-c

G (pH)h-c

G (pH)h,ion G (pH)c,ion

h: helix c: co il

neutra l

ionized

-1

-0.9

-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

-5 -3 -1 1 3 5 7 9 11 13 15 17 19 21 23 25

pH

Par

tial

ch

arg

e

Tyr67

Tyr100

Tyr115

Tyr177

Asp68

Asp76

Asp144

Asp160

Glu162

Glu173

His108 His132

His137

His119

His121

Catalytic site His108 His132

His137

His119

His121

Catalytic site

Figure: Morikis et al, Protein Sci 2001

Binding

Background

∑=

−=+∇⋅∇−F

iii

B

rrzTk

errrrr

10

22

0 )(4

)()()()()( δε

πϕκεεϕε

Tk

Ier

Bεεκ

0

22 4

)( =

ε: Dielectric coefficientκ: Ion accessibility functionI: Ionic strengthq: Charge φ: Electrostatic potential

Background Charges

Solvent Charges

Partial Charges (Electric dipoles)

=

=M

iii nzI

1

02

2

1

( )ϕκε ,,,q

ε high

ε lowε surface

κ surfaceκ = 0

κ ≠ 0

Linearized Poisson-Boltzmann Equation (LPBE)

Electrostatic Free Energies

Courtesy of C. Kieslich

= iielectro qG 2

1

BackgroundIntrinsic pKa calculation by the free energies of the thermodynamic cycleThermodynamic cycle has four proposed states:

1-Neutral to charge of bound2-Bound charge to amino acid3-Neutral to charge free4-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

PolymerAH

A-

PolymerA-

AH

1

4 2

3

Background

€

GFree − ΔG protein = ΔGneutral − ΔGch arg e

€

Gn−c = ΔGch arg e − ΔGneutral

€

ka = eΔG protein

RT →→

€

−log(ka ) =ΔG protein

2.303RT

€

Pka

protein =ΔG protein

2.303RT

€

Pka

free =ΔG free

2.303RT

€

2.303RT(Pka free − Pkaprotein ) = ΔGn−c

€

Pkaprotein = Pka free +ΔGn−c

2.303RT

Adapted from lecture notes of Bioengineering 135

Figure: Courtesy of Morikis et al

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.

Background

These modifications include:Adding a limited number of missing heavy atomsPlacing polar hydrogen'sOptimizing 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

RationaleDeveloping 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

Experimental Procedure (So Far)

Experimental Parameters

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

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

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 <- 100width <- 100height <- 100in_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")close(con)TC <- system(paste( "/apbs-1.2-mac-univ/bin/apbs", "infile.in",">", "outfile.txt", sep = " "))

Reads in our input template

Reads in our input template

Four PQR files which correspond to each state of TC

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

System call to APBS to use new input file and calculate free energies

Results (Free Energy Calc.)

IndexingIndexing

For loop to run through sequence

one amino acid at a time

For loop to run through sequence

one amino acid at a time

k <- ( as.numeric(neutral_pqr$atom[1,"resno"]) )end_of_seq <- length(seq.pdb(neutral_pqr) ) - 1seq <-our_seq(LY2, end_of_seq)AAdf <- NULL

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

}

Calls APBS for every ionizable amino acid to

calculate specific ΔG values

Calls APBS for every ionizable amino acid to

calculate specific ΔG values

Results (Intrinsic pKa)

DiscussionWe believe that our ΔG values may be off by a order of magnitudeIf 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

Progress Tracker (Winter)

Future work

ConclusionDeveloped and refined scripts that took in PDB files and converted them to neutral and charged PQR filesDeveloped and refined scripts that took neutral and charged PQR files and generated files that corresponds to the four states of the thermodynamic cycleIntergrated 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

AcknowledgmentsDr. Dimitrios MorikisChris KieslichRonald GorhamDr. Jerome SchultzGokul UpadhyayulaHong XuDr. Thomas Girke

References

Questions?

Our group would like to mention that no computers were injured in the making of

the software package