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Application of the linear interaction energy method for rational design of artemisinin analogues as haeme polymerisation inhibitors

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Application of the linear interaction energy method for rational design of artemisinin analogues as haeme polymerisation inhibitors
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  Journal of Molecular Graphics and Modelling 22 (2004) 249–262 Application of the linear interaction energy method (LIE) to estimate thebinding free energy values of   Escherichia coli  wild-type and mutantarginine repressor C-terminal domain (ArgRc)– l -arginine andArgRc– l -citrulline protein–ligand complexes A.M. Asi a , N.A. Rahman b , A.F. Merican a , ∗ a  Institute of Biological Sciences, Faculty of Science, University of Malaya, 50603 Kuala Lumpur, Malaysia b  Department of Chemistry, Faculty of Science, University of Malaya, 50603 Kuala Lumpur, Malaysia Received 27 March 2003; received in revised form 21 August 2003; accepted 12 September 2003 Abstract Protein–ligand binding free energy values of wild-type and mutant C-terminal domain of   Escherichia coli  arginine repressor (ArgRc)proteinsystemsboundto l -arginineor l -citrullinemoleculeswerecalculatedusingthelinearinteractionenergy(LIE)methodbymoleculardynamics (MD) simulation. The binding behaviour predicted by the dissociation constant ( K  d ) calculations from the binding free energyvalues showed preferences for binding of   l -arginine to the wild-type ArgRc but not to the mutant ArgRc(D128N). On the other hand, l -citrulline do not favour binding to wild-type ArgRc but prefer binding to mutant ArgRc(D128N). The dissociation constant for thewild-type ArgRc– l -arginine complex obtained in this study is in agreement with reported experimental results [J. Mol. Biol. 235 (1994)221–230].Ourresultsalsosupporttheexperimentaldataforthebindingof  l -citrullinetothemutantArgRc(D128N)[J.Mol.Biol.279(1998)753–760].TheseshowedthatLIEmethodforprotein–ligandbindingfreeenergycalculationcouldbeappliedtothewild-typeandthemutant  E. coli  ArgRc– l -arginine and ArgRc– l -citrulline protein–ligand complexes and possibly to other transcriptional repressor–co-repressorsystems as well.© 2003 Elsevier Inc. All rights reserved. Keywords:  Protein–ligand binding free energy; Protein–ligand binding affinity; Force field based simulation; Molecular modelling; Arginine repressorprotein;  Escherichia coli  K-12 1. Introduction The  Escherichia coli  arginine repressor (ArgR) proteinis an  l -arginine-dependent DNA-binding protein that regu-lates transcription of genes involved in the biosynthesis of  l -arginine. This repressor protein is also required as an ob-ligate accessory protein in Xer site-specific recombinationat cer and related recombination sites in natural multicopyplasmids[1–3].Mutationalandcrystallographicstudieshave shown that the N-terminal domain of ArgR (ArgRn) is re-sponsible for DNA binding while the C-terminal domain(ArgRc) is responsible for  l -arginine binding and hexamer-ization [4–7].ArgR is composed of a dimer of trimers and  l -arginineacts as a co-repressor for ArgR. The crystal structure of ArgRc– l -arginine complex showed that six  l -arginine ∗ Corresponding author. Tel.:  + 60-3-79674189; fax:  + 60-3-79674178.  E-mail address:  merican@um.edu.my (A.F. Merican). molecules are involved in stabilising the homohexamericArgR [6]. Mutational analysis showed that  l -arginine bind-ing is also required for ArgR binding to DNA [4,5]. How- ever, the role of   l -arginine molecules in the activation of the repressor to bind to DNA remains unclear. On the otherhand, mutants that are defective in trimer–trimer interactioncan bind to DNA in an  l -arginine independent manner [8].There are several computational methods that could beused for protein–ligand binding affinity calculations. A pop-ular method for assessing protein–ligand binding affinity isthe force field based simulation, either using partitioningmethod, where the free energy is partitioned into differentcontributions[9–15]orusingnon-partitioningmethodwhere the free energy of a system is related to the ensemble av-erage of an energy function that described the system [9].The non-partitioning method such as free energy perturba-tion (FEP) is the more accurate method to calculate absoluteprotein–ligand binding free energy. However, it is computa-tionally expensive, time consuming and often subjected to 1093-3263/$ – see front matter © 2003 Elsevier Inc. All rights reserved.doi:10.1016/j.jmgm.2003.09.003  250  A.M. Asi et al./Journal of Molecular Graphics and Modelling 22 (2004) 249–262 convergence problems [10,11,13]. Simplified methods of re- gression approach using predictions based on molecular me-chanics [16,17] or empirical scoring functions [18,19] has also been used to calculate protein–ligand binding affinity.This scoring function method calculates the score of a singleconformation of protein–ligand complex.In this study, the linear interaction energy (LIE) method,a linear response semi-empirical approach based on forcefield simulation developed by Aqvist and co-workers[10,12–15] was used to calculate the binding free energy of the wild-type and mutant ArgRc protein–ligand complexes.The LIE method employs molecular dynamics (MD) sim-ulation for sampling the interaction energies trajectory. InLIE, the binding free energy is estimated using averages of force field energies. LIE method considers the contributionsfrom Lennerd–Jones (LJ) and electrostatic interactions tothe total binding energy by the equation given below: G bind  = α(  V  LJl – s  bound − V  LJl – s  free ) + β(  V ell – s  bound − V  ell – s  free )  (1)where  α  is the empirical scaling factor for LJ interactionenergy and  β  the scaling factor for electrostatic interac-tion energy.   V  JLl – s  bound  denotes the LJ interaction energycontribution between the bound ligand and its surround-ing environment (i.e. water molecules and protein atoms)and   V  JLl – s  free  the LJ interaction energy contribution be-tween free-state ligand and its surrounding environment,  V  ell – s  bound  represents the electrostatic contribution betweenthe bound ligand and its surrounding environment while  V  ell – s  free  is the electrostatic interaction energy contributionbetween the free-state ligand and its surrounding environ-ment.The binding free energy values of protein–ligand in-teractions for the wild-type complexes ArgRc– l -arginine Fig. 1. The wild-type ArgRc– l -arginine and the mutant ArgRc(D128N)– l -arginine complexes. (a) The crystal structure of wild-type ArgRc– l -argininecomplex Asp128 of subunits C and D residues, as well as  l -arginine K1 which is adjacent to  l -arginine G1 molecule, are shown in the figure. (b)ArgRc(D128N) is a mutant protein in which the Asp128 was substituted to asparagine residue. Alphabetical letters in brackets denote the protein subunits. and ArgRc– l -citrulline, and the mutant complexes ArgRc-(D128N)– l -arginine and ArgRc(D128N)– l -citrulline werestudied. ArgRc(D128N) is a mutant protein obtained byside-directed mutagenesis in which Asp128 was substitutedwith asparagine [20]. By isothermal titration calorime- try, in contrast to the wild-type ArgR, the mutant proteinArgRc(D128N) was found to bind to  l -citrulline morestrongly than to  l -arginine [20]. The simulations in this study were carried out to investigate the effect of specificmutations on protein–ligand binding affinity using the LIEmethod, in an attempt to understand the structure–functionrelationship of ArgR. 2. Methodology The crystal coordinates of the ArgRc– l -arginine com-plex (PDB accession number 1xxa; at 2.2Å resolution)[6] was used as the initial conformation for the con-struction of the mutant ArgRc(D128N) protein systemand ligand substitution with  l -citrulline molecule. TheArgRc– l -arginine crystal structure complex was used astemplate and was subjected to Accelrys InsightII Biopoly-mer module on a Silicon Graphics (SGI) Octane R12000to generate ArgRc(D128N)– l -arginine, ArgRc– l -citrullineand ArgRc(D128N)– l -citrulline protein–ligand complexstructures. Fig. 1 shows the structures of wild-type and mu- tant ArgRc– l -arginine complexes, focusing on the locationof Asp128 and the Asn128 residues in the wild-type andmutant proteins, respectively, in relation to the  l -argininebinding site. Mutation of Asp128 to asparagine residue wascarried out for all the six ArgRc protein subunits. The struc-tures of   l -citrulline and  l -arginine are shown in Fig. 2. Sub-stitution of   l -arginine with  l -citrulline was carried out forall the six  l -arginine molecules G1–L1. In these simulations,   A.M. Asi et al./Journal of Molecular Graphics and Modelling 22 (2004) 249–262  251Fig. 2. Structures of   l -arginine (a) and  l -citrulline (b). Circles highlightthe differences between the  l -arginine guanidino group and  l -citrullineurea moiety. we chose  l -arginine G1 (as defined in the crystal structure;Fig. 3) or  l -citrulline G1 (in the case of   l -arginine sub-stitution with  l -citrulline) as the ligand molecule for theLIE protein–ligand binding free energy calculations sincetrimer 1 (comprising subunits A–C) has a lower crystalstructure B-factor average value as compared to trimer 2(subunits D–F) (data not shown).  l -arginine G1 is adjacentto subunits A and C (Fig. 3).The  l -arginine/  l -citrulline G1 alpha carbon was chosenas the centre atom from which an 18Å spherical bound-ary was defined for dynamic simulation. The 18Å spheri-cal boundary was chosen through trial and error modellingof charges on polar amino acid residues in order to ob-tain an electro-neutral state of the wild-type ArgRc pro-tein atoms. The modelling of charges was also applied to l -arginine molecules which were not defined as the lig-and in the simulations, i.e. H, I, J, K and L. The amino Fig. 3. ArgRc with six  l -arginine molecules.  l -arginine G1 (shown by CPK representation) was chosen as ligand molecule for LIE protein–ligand bindingfree energy calculations.  l -arginine molecules, H1, I1, J1, K1 and L1 (shown by Connolly surface representation) were included as part of surroundingatoms in MD simulation.  l -arginine G1 is adjacent to ArgRc protein subunits A and C and makes protein–ligand trimer–trimer interactions with subunit D. acid residues charges of the wild-type ArgRc protein atomswithin the 18Å simulation spherical boundary were mod-elled to electro-neutral condition by turning off the distantamino acid residues charges within the outermost 3Å of thesimulation spherical boundary and turning on the amino acidresidues charges within 15Å from the centre atom. For theamino acid residues that were switched off during the mod-elling of the amino acid charges, a correction value of  + 1.0kcalmol − 1 had been included [10] (the value was obtainedby Coulomb’s law calculation using a uniform dielectricconstant of 80, which would be a typical value long-rangecharge–charge interactions in solvated system).To take into account for the loss of negative charges by thesubstitution of Asp128 with asparagine in ArgRc(D128N)mutant protein, Ala147 of subunit A, Ala105 of subunit Band Ala126 of subunit D, located within the outermost 3Åof the simulation spherical boundary were substituted withaspartic acid residue (Table 1). To counteract for the lossof positive charges caused by  l -arginine substitution with l -citrulline (not including the defined ligand atoms of the G1molecule), Ala94, Pro135 and Ala136 of subunit A as wellas Ala109 of subunit E, which are located within the outer-most 3Å of the simulation spherical boundary were substi-tuted with lysine residue (Table 1). The alanine and proline residues were chosen for substitution to minimise majorstructural changes in the protein conformations becausetheseresiduesarerarelyinvolvedinsecondaryalpha-helixorbeta-strands protein conformation. The outermost 3Å spher-ical solute boundary was subjected to a 20kcalmol − 1 Å − 2 polarisational restraint during MD simulation. With thesemutations, the overall charges of ArgRc– l -arginine andArgRc(D128N)– l -arginine protein–ligand complexes were  252  A.M. Asi et al./Journal of Molecular Graphics and Modelling 22 (2004) 249–262 Table 1Modelling of amino acid residues charges for molecular dynamics simu-lationProtein–ligandsystemPositive chargeswithin the outermost3Å simulationspherical boundaryNegative chargeswithin the outermost3Å simulationspherical boundaryArgRc– l -arginine Arg 110 (A) Asp 113 (A)Lys 117 (A) Asp 128 (A)Arg 110 (E ) Asp 129 (A) l -Arginine (G) Asp 128 (C) l -Arginine (H) Asp 129 (C) l -Arginine (I) Asp 128 (D) l -Arginine (J) Asp 129 (D) l -Arginine (K)ArgRc(D128N)– l -arginineArg 110 (A) Asp 113 (A)Lys 117 (A) Asp 128 (A)Arg 110 (E) Asp 147 (A) b l -Arginine (G) Asp 105 (B) b l -Arginine (H) Asp 129 (C) l -Arginine (I) Asp 126 (D) b l -Arginine (J) Asp 129 (D) l -Arginine (K)ArgRc– l -citrulline Arg 110 (A) Asp 113 (A)Lys 117 (A) Asp 128 (A)Lys 94 (A) a Asp 129 (A)Lys 135 (A) a Asp 128 (C)Lys 136 (A) a Asp 129 (C)Lys 109 (E) a Asp 128 (D)Arg 110 (E) Asp 129 (D)ArgRc(D128N)– l -citrullineLys 94 (A) a Asp 113 (A)Arg 110 (A) Asp 129 (A)Lys 117 (A) Asp 147(A) b Lys 135 (A) a Asp 105 (B) b Lys 136 (A) a Asp 129 (C)Lys 109 (E) a Asp 126 (D) b Arg 110 (E) Asp 129 (D) a Lys 94, Lys 135, Lys 136 and Lys 109 were srcinally Ala 94, Pro135, Ala 136 and Ala 109, respectively. b Asp 147, Asp 105 and Asp 126 were srcinally Ala 147, Ala 105and Ala 126, respectively. Overall protein–ligand charges obtained forArgRc– l -arginine and ArgRc(D128N)– l -arginine were  + 1, while that of ArgRc– l -citrulline and ArgRc(D128N)– l -citrulline were neutral. Alpha-betical letters in brackets denote the protein subunit. positive one ( + 1) while the overall charges for ArgRc– l -citrulline and ArgRc(D128N)– l -citrulline protein–ligandcomplexes were maintained at electro-neutral condition.Dynamic simulations were run for  l -arginine G1 mole-cule bound to ArgRc and ArgRc(D128N),  l -citrullineG1 molecule bound to ArgRc and ArgRc(D128N) pro-tein systems, and free-states  l -arginine/  l -citrulline G1molecule using the Q software package [15]. All simulation systems were solvated with water molecules represented bya rigid single point charge (SPC) model which is subjectedto polarisation restraints according to the surface constrainedall-atom solvent (SCAAS) model [21]. The wild-typeArgRc– l -arginine simulation included 220 SPC modelwater molecules while mutant ArgRc(D128N)– l -arginine Fig. 4. The set of partial atomic charges assigned to  l -arginine molecule. simulation included 219 SPC model water molecules. Thewild-type ArgRc– l -citrulline simulation included 217 SPCmodel water molecules while mutant ArgRc(D128N)– l -citrulline included 216 model water molecules. All simu-lations for bound  l -arginine and  l -citrulline included 18crystallographic water molecules. Both the simulation of  l -arginine G1 and  l -citrulline G1 free-states included 787SPC model water molecules. The systems were assignedwith modified GROMOS force field [22,23]. The  l -argininemolecular fragment library file was created and a differentset of partial atomic charges was assigned (Fig. 4). This is due to the fact that the standard  l -arginine molecularfragment in the existing library file was defined as a pep-tide fragment and hence the library file is not suitable for l -arginine molecule. A similar  l -citrulline molecular libraryfile was also created (Fig. 5).  l -citrulline urea angles wereparameterized based on values provided by Lorna Smith(Lorna Smith, pers. comm.; Tom Hansson, pers. comm.) Fig. 5. The set of partial atomic charges assigned to  l -citrulline molecule.   A.M. Asi et al./Journal of Molecular Graphics and Modelling 22 (2004) 249–262  253Fig. 6. The angles for  l -citrulline urea moiety (Lorna Smith, pers. comm.).The atom-types were specified in brackets. (Fig. 6). Qprep4 program was run iteratively to determine an 18Å effective water radius for all simulation systems.All simulations were run at 1fs MD timestep. MD simu-lations were run for 865ps for the wild-type ArgRc boundstate and ligand free-state simulations. MD were run for1160ps for the mutant ArgRc(D128N) bound state simula-tions. The mutant protein–ligand interaction energies tooklonger time to converge. The first 115ps MD were run toequilibrate the simulated systems. The simulation startedwith 1K temperature at 1fs temperature bath relaxationtime (bath coupling time) and MD data collection stageswere carried out at 300K at 10fs bath coupling time. Allsolute atoms (proteins and  l -arginine/  l -citrulline molecules, Fig. 7. The LJ and electrostatic interaction energies of   l -arginine bound to wild-type ArgRc and  l -arginine free-state simulations solvated in watermolecules. The plotted 250ps trajectory data block was well-converged and was used in LIE protein–ligand binding free energy calculation. G, H, I, J, K and L) were subjected to a low force constraintof 5kcalmol − 1 Å − 2 from the beginning of the equilibrationstage to 25ps of simulation time, after which the constraintapplied was removed. Cut-off radius was not applied tointermolecular interaction involving  l -arginine/  l -citrullineG1 ligand atoms. Cut-off radius of 10Å was applied to pro-tein atoms and  l -arginine/  l -citrulline H–L molecules for allsimulations. Local reaction field (LRF) method [24] with10Å solvent–solvent interactions cut-off radius was usedfor all simulations. Shake constraints were applied for sol-vent molecules to keep the solvent molecules bond lengthsand angles constant during dynamics simulation. Shakeconstraint was not applied to solute atoms. The interactionenergies sampling and the trajectories sampling were doneevery 10 and 500fs, respectively. In order to determinethe protein–ligand binding free energy, a simulation on thewater-solvated free-state  l -arginine G1 and  l -citrulline G1molecules were carried out separately. In both free-statesimulations,  l -arginine and  l -citrulline molecules weresubjected to a 10kcalmol − 1 Å − 2 restraints throughout thedynamic simulation.Methods to estimate the dynamic simulation durationand the standard error for the interaction energies samplinghave been described on the standard basis of statisticalinefficiency [14]. In this study, the simulations were run and MD data collection stage trajectories were selected forLIE calculation based on the analysis where the LJ interac-
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