1. 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 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 pK a for a single amino acid is 50% protonation pK a values are environment dependent The environment may cause shifts in pK a pK a values are important for understanding many biological processes

4. Binding

5. Catalysis Asp102 of Chymotrypsin – hydrogen bond with His57 – increases pK a 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 pK a shift of His57, catalysis would not be possible!

6. Salt Bridge pK a 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

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

8. Background ε: Dielectric coefficient κ: Ion accessibility function I: Ionic strength q: Charge φ: Electrostatic potential Background Charges Solvent Charges Partial Charges (Electric dipoles) ε high ε low ε surface κ surface κ = 0 κ ≠ 0 Linearized Poisson-Boltzmann Equation (LPBE) Electrostatic Free Energies Courtesy of C. Kieslich

9. Background pK a calculation by the use of 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 pK a values and titration curves 1 4 2 3

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

11. 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 PDBPQRAPBS

12. 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

13. 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 Δ G value is used to calculate the pKa of its corresponding residue The Δ G values are first divided by thermo energy then subtracted by the model pKa

14. Experimental Parameters

15. 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

16. 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

17. 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") close(con) TC ", "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

18. Results (Free Energy Calc.) Indexing 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) ) - 1 seq <-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 Δ G values

19. Results (Intrinsic pK a )

20. Progress Tracker (Winter)

21. Future work

22. Discussion 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 pK a Successful in taking protein 1LY2 PDB file and calculating intrinsic pK a for all ionizable amino acids of 1LY2

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

24. References Trylska, Joanna. "View Continuum Molecular Electrostatics, Salt Effects, and Continuum Molecular Electrostatics, Salt Effects, and Counterion Binding—A Review of the Poisson– Boltzmann Counterion Binding—A Review." Wiley InterScience 28.2 (2007). Antosiewicz, Jan M. "Protonation Free Energy Levels in Complex Molecular Systems." Wiley InterScience 89.4 (2007). Gilson, Micheal K. "INTRODUCTION TO CONTINUUM ELECTROSTATICS, WITH MOLECULAR APPLICATIONS." Editorial. 13 Jan. 2006. Morikis, Dimitrios. "Molecular thermodynamics for charged biomacromolecules." Fluid Phase Equilibria (2006). Nielsen, Jens. "Analyzing Enzymatic pH Activity Profiles and Protein Titration Curves Using Structure-Based pK a Calculations and Titration Curve Fitting." Methods in Enzymology.

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