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

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

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.

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!

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

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

Binding

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

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

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

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: 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

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

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

Experimental Parameters Ionic strength Dielectric solvent (εlow) Dielectric Solute (εhigh) Temp 150.0 mM 80.0 20.0 298.15 K Box Size (Å) X Y Z fglen 100 cglen Grid size 129

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 <- 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

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

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

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

Progress Tracker (Winter)

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

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

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

References

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