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How does the Proliferating Cell Nuclear Antigen modulate binding specificity to multiple partner proteins? Hubert Li, Manbir Sandhu, Linda H. Malkas, Robert Joseph Hickey, and Nagarajan Vaidehi J. Chem. Inf. Model., Just Accepted Manuscript • DOI: 10.1021/acs.jcim.7b00171 • Publication Date (Web): 02 Nov 2017 Downloaded from http://pubs.acs.org on November 9, 2017

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Journal of Chemical Information and Modeling

How Does The Proliferating Cell Nuclear Antigen Modulate Binding Specificity To Multiple Partner Proteins? Hubert Li1, Manbir Sandhu1, Linda H Malkas2, Robert J Hickey2 and Nagarajan Vaidehi1,* 1 Department of Molecular Immunology, and 2Department of Molecular Medicine, Beckman Research Institute of the City of Hope, 1500, E Duarte Road, Duarte, CA – 91010 * correspondence to: [email protected]

Abstract: Proliferating cell nuclear antigen (PCNA) is a member of the family of sliding clamp proteins that serves as a clamp during DNA repair, DNA replication, cell cycle control, and multiple forms of chromatin modification. PCNA functions as a homotrimer and complexes with multiple proteins in order to carry out each of these varied functions. PCNA binds to different partner proteins in the same region of its structure called the “ inter-domain connecting loop” but with different affinities. This inter-domain connecting loop is an intrinsically disordered region and takes different conformations while binding to different partner proteins. In this work we have performed all-atom molecular dynamics simulations on PCNA trimer unbound to any partner protein and PCNA bound to peptides from different partner proteins and PCNA bound to the full Fen 1 protein in two different conformations. Using these massive number of simulation results we have analyzed if PCNA in its free trimeric form samples conformations that are similar to those when it is bound to different partner proteins. We observed that PCNA samples many of these peptide bound conformations even when not bound to the peptides and selects specific conformations when binding to partner proteins. We have also identified PCNA-peptide interactions formed in the peptide bound simulation that play a crucial role in complex formation. The calculated binding energies correlate well with the measured binding affinity of various peptides to PCNA. Lastly we studied the internal dynamics of PCNA and propose a mechanism through which PCNA recruits binding partners. This work highlights the functional role of intrinsically disordered regions in multifunctional proteins such as PCNA. Keywords: PCNA, molecular dynamics, conformation selection, Fen1.

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Introduction Proliferating cell nuclear antigen (PCNA) is a member of the family of sliding clamp proteins that serves as a clamp during DNA repair, DNA replication, cell cycle control, and multiple forms of chromatin modification. PCNA carries out its wide range of function by binding to different binding partner proteins.1,2 Despite its involvement in a large number of functions the vast majority of PCNA is not post-translationally modified1,3 in normal cells, and nearly all living organisms have a form of functionally and structurally related form of sliding clamp protein.2,4 Cellular growth and replication are critical components of cancer progression, and cancer cells show elevated expression of PCNA.5–7 Despite the elevated levels of PCNA in cancer, its usefulness as a prognostic marker is contested. 6–8 However, it has been suggested that post-translationally modified forms of PCNA are associated with cancer.9,10 Thus inhibition of PCNA function has been suggested as an potential therapeutic strategy.4,11,12 The three dimensional structure of PCNA forms a toroid ring that encircles DNA as seen in Figure 1.13 The ring structure of PCNA is loaded on to DNA by the replication factor C complex. PCNA bound to DNA provides a stable scaffold and interaction site for many DNA associated proteins to interact with PCNA.2,14 In humans, the PCNA trimer is composed of three units identical both in amino acid sequence and structure.15 Each monomer can be further divided into two non superimposable domains joined together by beta sheets that line the exterior surface of the toroid structure and an interior lined by alpha helices.13,15 The alpha helices lining the interior surface of each PCNA protein contain high concentration of positively charged residues to facilitate interaction with DNA backbone.16,17 The two domains in each PCNA protein are linked together by a single flexible loop connecting the N-terminal domain to the Cterminal domain called the interdomain connecting loop (IDCL).2,18 This overall structural unit is conserved across the various kingdoms of DNA sliding clamps.2,19


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The protein-protein interaction site in PCNA has been identified by mapping consensus sequences among many PCNA binding partners.14 The amino acid sequence of the PCNA interacting protein box (PIP-box shown in Figure 2a) found in protein partners is the consensus sequence QxxHxxAA where (Q represents the amino acid glutamine, H represents any hydrophobic amino acid, A represents monocyclic aromatic residue like phenylalanine or tyrosine, and lastly x any other standard amino acid residue).14 Partner proteins containing this PIP-box sequence interact in a pocket lined on one side by the IDCL and the other by the Cterminal tail of PCNA.20,21 This pocket provides a hydrophobic region that is known to favor protein-protein interactions as shown in Figure 2b.21 The interaction site has been confirmed through multiple mutagenic studies, multiple peptide bound X-ray PCNA structures, and NMR.15,22–26 Most partners interacting with PCNA containing the PIP-box sequence adopt a 310 left handed helix structure at this site. To date over 200 proteins have been shown to directly interact with PCNA.27 PCNA interacts with multiple partner proteins even in its post-translationally unmodified form.4 The partner proteins are involved in DNA replication (polymerase-δ), DNA repair (pol-ι, pol κ, and pol-η), cell cycle regulatory proteins (p21, p53, and p35), chromatin accessibility (HDAC1), and transcription (p65).19 Despite the large number of binding partners the only full length protein complex structure is that of the Flap endonuclease 1 (Fen1) PCNA complex.24 The remaining PCNA-partner protein bound crystal structures are derived from peptide sequences that contain portions of the partner proteins that bind to the PIP box.15,22–26 Despite the numerous binding partners the PIP-box is the site where most proteins interact.24,28 PCNA binds to its protein partners with different binding affinities. The molecular mechanism of how PCNA modulates its



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conformational ensemble to bind to different partner proteins with different affinities is not evident. Analysis of the crystal structures of PCNA: To date there are 14 bound crystal structures of human PCNA deposited in the PDB shown in Table S1 of the Supporting Information. These structures show a high degree of structural similarity as shown in Figure S1a of the Supporting Information. Analysis of the amino acid residue contacts between the PCNA and the partner peptides do not show significant differences that explain the difference in their binding affinities to PCNA. Analysis of the PCNA-peptide complex crystal structures shows that in these structures, the PCNA part lacks residues of the N-terminus, IDCL, and the C-terminus. The crystal structures also lack large portions of the bound peptides due to poor resolution in these regions. The peptides bound to PCNA are intrinsically disordered in these regions and hence not resolved in the crystal structure. Therefore, the mechanism through which PCNA modulates its interaction with different partner proteins in same region of the structure is unknown. We hypothesize that studying the dynamical conformational ensemble of the intrinsically disordered regions of the partner proteins would lead to a rational structural basis for the differential selectivity of PCNA to its various partner proteins. It is possible that the internal dynamics of multi functional proteins such as PCNA, even when not bound to any partner protein, samples all the bound conformations suggesting conformational selection is important in the activity of PCNA. This postulate is supported by the two possible conformations of Fen1 seen when bound to the trimeric PCNA toroid as shown in Figure S1b of Supporting Information. We define the conformation of Fen1 that is close to the DNA as the “active” conformation and the


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conformation of Fen1 that is farther of from the DNA when bound to PCNA as the “inactive” conformation of Fen1. In this paper we use molecular dynamics (MD) simulations to understand how PCNA modulates its interaction with the intrinsically disordered regions of the various partner proteins with different affinities even when using a shared binding site. Since the IDCL regions of PCNA are intrinsically disordered they could adopt an ensemble of conformations that could be used to impart differential binding affinities to various partner proteins. We used extensive all-atom molecular dynamics (MD) simulations to investigate the conformational dynamics of PCNA with and without the peptides of the partner proteins (referred to as partner peptides hereafter) to understand if PCNA adopts the various bound conformations even in the absence of the partner peptides. Previous MD simulations with Fen1 bound PCNA and targeted MD simulations on Pol bound PCNA have provided specific conformational changes in these PCNA partner proteins that lead to their activity on the DNA.17,29–33 We have utilized extensive MD simulations on (a) the free toroid ring trimer structure of PCNA, (b) free monomer of PCNA, (c) several peptide bound PCNA structures, and (d) PCNA monomer with Fen 1 complex. We used this comprehensive set of MD simulation results to provide insight into the conformational dynamics of PCNA and the structural basis of PCNA specificity to various binding partners. Modeling of the entire peptide binding to PCNA also provides structural basis for the peptide binding affinities to PCNA.

Computational Methods We use extensive molecular dynamics (MD) simulations of PCNA and PCNA bound to its partner proteins to understand the mechanism of protein-protein interactions in PCNA.



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MD simulation details: The crystal structures with their respective PDB ids listed in Table S2 (Supporting Information) were retrieved from the Protein Data Bank.34 The bound peptides had portions of the peptide structure missing in the crystal structures due to poor resolution. We used MODELLER to fill in unresolved amino acids, missing loop regions of PCNA and the bound peptides.35,36 Missing regions of PCNA were modeled using the structure of these regions from the trimer structure of PCNA (pdb ID: 1VYM). Large missing portions of the bound peptides were added using MODELLER. A total of 5 top scoring (DOPE scores from MODELLER) homology models were generated for each crystal structure. Peptide bound structures were selected to minimize the existing contacts with PCNA so that the modeled part of the peptides do not have any predetermined contacts with PCNA prior to MD simulations. Each model thus chosen, was then set up using the ff14SB force field in a solvation box extending 12Å from the periphery of the protein using TIP3P. Na+ counterions were added to neutralize the system. System minimization, equilibration, and production dynamics were performed using the PMEMD module of Amber14.37 Each system was minimized for 2000 steps using a nonbond cutoff of 12Å using constant volume NVT ensemble. The system was equilibrated for 80 ps to a temperature of 310K under NVT conditions. This step optimizes the packing of the solvent around the protein and the production runs were carried out at constant pressure maintained by a Berendsen barostat.38 The SHAKE and SETTLE algorithms were used to constrain bonds with hydrogen and the internal water geometry.39,40 The simulations were carried for a minimum of 500ns using the GPU accelerated version of pmeMD. The MD simulations for the free trimeric structure of PCNA were run for 100ns. The total simulation time for each system simulated in


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this study is listed in Table S3 of the Supporting Information.

MD trajectory Analysis To compare the inherent flexibility and dynamics of PCNA and bound peptides, we calculated the root-mean-squared deviations (RMSDs) in coordinates of the backbone atoms (N, Cα, and C) of the proteins over the course of the simulations and the root-mean-squared fluctuations (RMSFs) relative to the average structure for each residue. Both RMSD and RMSF were calculated using cpptraj from the AmberTools14 package only backbone atoms C, N, and CA were used for backbone calculations.41 Hydrogen bonds were analyzed using the default parameters set in cpptraj searching for hydrogen bonds formed with any peptide atoms.41 These data was processed using numpy and plotted using matplotlib.41–43 Principal component analysis Principal component analysis was used to analyze large scale domain motion in free PCNA trimer and in peptide bound PCNA. Principal component analysis was performed using the packages integrated in ProDy.44 To perform principal component analysis we used the coordinates of only the protein backbone atoms of residues 1 to 255 of PCNA. The last six residues of the C-terminus of PCNA were removed from this analysis to minimize the influence of the highly dynamic carboxy tail. The trajectories were then concatenated together and aligned to the average structure of the large trajectory. A covariance matrix was generated using the mean coordinates as the reference. The resulting modes derived from the covariance matrix were used as the principal components.



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Results and Discussion The crystal structures of PCNA bound to various peptides show only a small section of the bound peptide resolved in the structure, as shown in Figure 3a. However, longer peptide constructs of the partner proteins were used in the biochemical assays measuring the binding affinities of these peptides to PCNA.25,26,28,45,46 Most of the peptide residues remain unresolved in the crystal structures possibly due to their flexibility in the binding region. Our initial MD simulations using these crystal structures (shown in Figure 3) with truncated peptides bound, did not yield any insight into the differing binding affinities of the peptides to PCNA. Subsequently, we modeled the missing regions of the bound peptide which typically varied from 1 to 11 amino acid residues in length (shown in Figure 3 in red ribbons). The unresolved residues in the peptides were built in the crystal structure in an extended conformation using MODELLER. In this extended conformation the peptide does not make contacts with PCNA as shown in Figure 3. We also modeled the 6 missing residues in the carboxy terminus of PCNA using MODELLER.35,36,47–49

Folding of the unresolved part of the bound peptides to PCNA: To understand how the unresolved modeled regions of the bound peptide fold over the PCNA we clustered the MD simulation trajectories of the peptide bound PCNA using RMSD based clustering. We extracted the representative conformation from the most populated conformation cluster and analyzed the contacts of the unresolved regions of the bound peptides when they folded over the PCNA surface and make extensive contacts with PCNA residues. The structure of the peptide folded over the PCNA making the maximum number of contacts with PCNA, from the most populated conformational cluster within 500ns of simulation time for


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various peptides is shown in Figures 3. The peptides formed non-bond interactions with residues in PCNA and the number of such interactions increased during the MD simulations compared to the starting structures as shown in Figure 3. We further examined if the contacts made by the folded peptide structures would account for the differences in the binding of the various peptides since the crystal structures of the peptide-PCNA complexes did not have these regions of the peptide and could not account for the differential binding of the peptides.

Analysis of close packing residue contacts between the peptides and PCNA: To understand the differences between the interactions of various peptides to PCNA we calculated the inter-residue contacts that are within 5 Å between the bound peptide and PCNA. We also calculated the frequency of occurrence of these contacts over the entire MD simulation trajectories to examine which of these contacts stay sustained over longer periods of time. Figure 4 shows the relative frequency of hydrogen bonds formed between the residues in the IDCL region of PCNA and its partner peptides. The majority of contacts formed between PCNA and the peptides are located in the PIP box binding site, and this includes portions of the C-terminus and IDCL of PCNA. More importantly the residues that were absent in the crystal structure of bound peptides, but modeled here account for significant number of hydrogen bonds between the peptides and PCNA. The residue G127 in the PCNA is a very stable hydrogen bonding partner in every peptide simulation as shown by blue bars in Figure 4. The importance of the backbonebackbone hydrogen bond at this position is highlighted by mutations showing large reductions in efficacy and binding characteristics of peptides.50,51 The formation of a backbone-backbone hydrogen bond at Q125 allows PCNA to tolerate mutation at the site with little effect on peptide affinity, this is substantiated by mutation experiments on pol δ and Fen 1.51,52 However, the



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adjacent residue E124 forms a side chain-side chain hydrogen bond and mutations at that site are not well tolerated.51,52 These observations provide insight into which residues in the IDCL are crucial to peptide binding. The frequency of van der Waal contacts that each peptide makes with the IDCL residues in PCNA is shown in Figure 5. Please note that the X-axis in this figure is the residue number of the residues in the peptides bound to PCNA. Here we used the peptide residues to calculate the van der Waals contacts since each residue on the peptide can make multiple van der Waals contacts with the IDCL residues in PCNA. We calculated the number and frequency of close van der Waal interactions within a cutoff distance of 4Å and correlated this to the peptide binding energy calculated using MMPBSA. Polymerase κ is the weakest binder in this set of peptides studied here, and shows the lowest occurrence of van der Waals contacts while Fen1 and Pol η peptides show the highest occurrence of favorable van der Waals packing contacts. The RNase H2B peptide is an outlier, where the simulation shows frequent van der Waals contacts of the peptide with PCNA while it is a poor binder experimentally. The reason for this occurrence is that in its folded state a secondary helix on the N-terminus of the RNAse H2B peptide is formed and buries itself into a cleft along the IDCL and C-terminal domain of PCNA. This could be an artifact of the simulation since once the helix is formed and buried favorably into PCNA it is harder to break it up within the limited simulation time of 500ns. Therefore we consider this an outlier. The two aromatic residues at the end of PIP box sequence (QxxHxxAA where A is the aromatic amino acid) of PCNA are significant contributors towards making the favorable van der Waals contacts with several peptides. The frequency of the close contacts suggests that the pair of aromatic residues bury deep into the PIP box binding site of PCNA. Of more interest is the


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lack of contribution to the van der Waals packing interactions from the highly conserved leucine, the hydrophobic residue (H) of the PIP box sequence. The lower frequency of close contacts made by this Leucine residue suggests a reduced role of this residue in in protein peptide interaction and in differentiating among the different peptide binding to PCNA. Indeed previous studies have suggested that the inclusion of this hydrophobic residue into the defining PIP box sequence has been called into question.53

Comparison of the flexibility of PCNA when bound to different peptides: To identify the flexible regions in PCNA that have functional implications we analyzed the dynamics of PCNA with different peptides and proteins bound and compared them to free PCNA simulations. Contrary to intuition, simulations performed on peptide bound PCNA show a minor increase in observed atomic fluctuations compared to the free PCNA. Figures 6a and 6b show the changes in root mean square fluctuation (RMSF) of every residue from the average structure derived from the entire trajectory. The RMSF value for each residue shows the level of flexibility over and above the average value, during the simulations. The RMSF plot shows little deviation between the MD simulations of free PCNA and PCNA monomer bound to peptides, as seen in Figures 6a and 6b. Despite the inclusion of a peptide partner bound to PCNA, the IDCL region of PCNA that is involved in peptide binding remains as dynamic in the peptide bound PCNA simulations as in the free PCNA simulations. This indicates that the binding of the peptide does not reduce the flexibility of the IDCL loop region. As seen in Figure 6a, there is a significant increase in flexibility in the βH1-βI1 loop of the N-terminal domain and the βD2-βE2 loop of the C-terminal domain. These regions correspond to the partner protein binding and DNA binding regions respectively in PCNA. Furthermore, comparing the peptide bound



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simulations to the full Fen1 protein bound simulations (Figure 6b) reveals that the full protein bound simulations exhibit increased flexibility over the entire protein except in the IDCL region. The binding of entire Fen1 to PCNA reduces the flexibility in the IDCL compared to fen1 peptide binding to PCNA. We also note that the flexibility of the βH1-βI1 loop of the N-terminal domain and the βD2-βE2 loop of the C-terminal domain where the protein and DNA binds increases when bound to full Fen 1 compared to Fen1 peptide bound simulations. The flexibility in the residues located in IDCL and C-terminal end of PCNA has been reported in previous Fen1 bound PCNA MD simulations.32

Analysis of large scale motion in PCNA dynamics: Our goal in this section is to analyze if the dominant motion reflected by the dynamics of the free PCNA shows similarity to the dominant motion when PCNA is bound to the peptides or the full partner protein. This would show if there were conformation selection when the peptides or proteins bind to PCNA. We performed the Principal Component Analysis (PCA) to examine the most important motion in the unbound PCNA dynamics and compare this to peptide and protein bound PCNA dynamics. The procedure of PCA is described in the Methods section. Here we have compared the collective movements in the free PCNA monomer to that of peptide bound PCNA monomer to understand if the principal components of free PCNA dynamics resemble the principal components of peptide bound PCNA. PCA analysis shows that the top two principal components (PC1 and PC2) cover over 40% of the cumulative variance as shown in Figure S2 of the Supporting Information. We first analyzed the collective motion of PCNA when it is bound to two different orientations of Fen1 (active and inactive as shown in Figure S1) in the PCNA-Fen1 complex.


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The regions of PCNA involved in PC1 are shown in Figure 7. The two overlapping green structures shown in Figures 7a and 7b are the conformations from the extreme ends of the PC1 space. The regions of PCNA structure shown in red and blue in Figures 7a and b highlight the regions that show significant change in PC1 space. The movement in these two regions signifies closing of the IDCL on the PIP pocket concurrent with a shift in the βH1-βI1 loop to facilitate contact with DNA. The movement of the IDCL loop starting with the red loop shows contraction of the PIP box region tightening the contacts with the partner protein and ending with the IDCL conformation shown in blue. The movement of the βH1-βI1 loop is shown starting from the conformation shown in red and ending up with the loop where the DNA binds in blue. Figure 7c shows the extent of movement in the PC1 direction with a box and whisker plot. The red line in the middle of the box is the median that divides the entire range of PC1 coordinates into half and the box represents the middle half of the data (between 25th and 75th quartile) when we divide the spread in the PC1 values into four quarters. The positive and negative units in the principal component 1 shown in the box and whisker plot in Figure 7c, signifies the extent to which the IDCL loop moves in opposite directions with respect to the structure that marks the redline in the figure. The red line in the middle of the box is the median that divides the data into half and the box represents the middle half of the data (between 25th and 75th quartiles) when we divide the spread in the PC1 values into four quarters. The positive unit in PC1 coordinates signifies movement of IDCL and the βH1-βI1 loop in a direction that tightens the binding of the partner protein and the DNA respectively. The negative PC1 coordinate shows the opposite effect. We find that this collective and coordinated movement in the PC1 space is observed most frequently in both the inactive state conformation (away from DNA) of Fen1 bound PCNA as well as active state (closer to the DNA) conformation of Fen1 bound PCNA simulations. Another important



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point to note is that in the box and whisker plot of the Fen1 bound PCNA simulations, the top 3 quartiles are greater than 0.5 in the principal component PC1 space, demarked by the thick red line. This suggests that there is a link between a positive projection in the PC1 space and PCNAFen1 bound protein dynamics. Using this knowledge we projected each of the trajectories of peptide bound PCNA along the same principal components as free PCNA and Fen1-PCNA complex to better assess the extent of overlap in the PC space of the free PCNA compared to peptide bound PCNA and Fen1 bound PCNA simulations. The box and whisker plots of these projections are shown in Figure 8. Again the positive value of PC1 denotes the extent of movement in IDCL and βH1-βI1 loop that favor the binding of the partner protein/peptide and DNA respectively. We observe that in all the peptide bound PCNA simulations the projections in PC1 favor collective motions in the negative or opposing direction to that shown by PCNA-Fen1 complex (Figures 7a-c). The peptide bound projections show that the βH1-βI1 loop move away from the DNA and that the peptides are able to restrict the PCNA motion to conformations that are not conducive to protein or DNA binding. Indeed even the simulation with the Fen1 derived peptide does not exhibit the same preference as the full Fen1 bound PCNA simulations in the PC1 motion. We analyzed the PC1 motion in the five independent simulations performed for the PCNA trimer with no peptide or protein bound. The analysis in PC1 was done for each monomer trajectory extracted from the trimer simulations. The box and whisker plots for the projections in PC1 are shown in Figure 9a. The PCNA trimer simulations without any peptide bound, show a peculiar trend, when the projections of the principal components of each monomer are compared. In all the five simulations two of the three monomers showed PC1 movement similar to Fen1PCNA complex, although to a limited range. However, it is interesting to note that one of the


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three monomers showed PC1 motion similar to the peptide bound PCNA simulations. This PCNA monomer is in a conformation that does not favor partner protein or DNA binding. We see in Figure 9a, that this ratio of “bound” to “unbound” protein state difference is observed in the majority of the 5 simulations. Incidentally, the crystal structure of trimeric PCNA bound to the full Fen1, also shows that two monomers of PCNA bind to full Fen1 in what we labeled as the active conformation because it puts Fen1 closer to the DNA (shown in yellow in Figure 9c), while the third monomer binds to the inactive conformation of Fen1 as shown in cyan in Figure 9c. This difference in the dynamic behavior of one of the three monomers in the free PCNA trimer could may account for the tilt observed in the DNA when bound to the PCNA toroid ring70. Interestingly, the monomer that behaves differently from the other two monomers of PCNA in the trimer simulations is not always the same monomer. This observation supports the proposed model by Mayanagi et al54 that PCNA acts as a “revolver” in which the single PCNA trimer could switch the monomers to bind to different partner proteins to work sequentially. Combined with the collective motions observed in the PC1 space, the PCNA dynamics suggests that the conformation that PCNA takes in the peptide bound state is also sampled in the unbound PCNA. Thus when no protein partner is present PCNA will show collective motions that favor binding in the two monomers that interfaces with the DNA, as indicated by the βH1-βI1 loop. Furthermore, when the βH1-βI1 loop motion is observed through contact with DNA PCNA will present the closed loop structure more conducive to tight protein binding.

Conclusions PCNA is an adaptor protein and therefore binds to multiple partner proteins to enable these proteins to carry out different DNA metabolic processes. Although it is known that PCNA



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interacts with its partner proteins through the PIP box sequence the structural basis of such differential interactions is not known. This is because the crystal structures of peptide bound PCNA are incomplete and hence not sufficient to rationalize the differential binding of peptides. Understanding of how PCNA binds differentially to different partner proteins is important, to understand how different partners compete for binding and exert their enzymatic and regulatory functions. The extensive MD simulations that we performed here on unbound and several peptide bound PCNA and Fen1-PCNA protein complex have provided insights into (a) the structural basis of binding of PCNA to its partner proteins with varying affinities and (b) the similarities between the intrinsic conformational dynamics of unbound PCNA to that of peptide bound PCNA complexes. We show the peptide binding energies calculated using atomic forcefield and averaged over the entire dynamics trajectories correlate well with the measured binding affinities. We have rationalized the role of the residues in the IDCL through their frequency of hydrogen bonds and van der Waals contacts formed with each peptide. Another important observation is that the full protein Fen1 binding to PCNA showed that Fen1 binding causes correlated motion in the DNA binding βH1-βI1 and βD2-βE loop regions. Such motion in the DNA binding region was not observed when PCNA is bound to just the peptides showing that peptides have little influence on the flexibility of IDCL and therefore have little long range influence on both βH1-βI1 and βD2-βE loops. Analysis of the collective motions derived from the principal components provides insights into how free PCNA undergoes conformational changes even in the absence of bound peptides. Remarkably, two of the three monomers in the dynamics of the trimeric unbound PCNA show conformational sampling that is different when compared to the third monomer. These two monomers are the ones that bind to the DNA and possibly bring the bound protein


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closer to the DNA for repair. The third monomer in the free trimer PCNA simulations favors a conformational state rarely sampled by the protein bound PCNA state. The collective motion links movements in the DNA contacting βH1-βI1 loop of PCNA to the PIP box binding site. This result provides a rationale for the selective binding that PCNA can achieve. The coupling of the DNA interaction promoting movement of the βH1-βI1 loop with the contraction of the PIP box binding site provides a rationale for recruitment of partner proteins by PCNA. We are able to deduce from the Fen1 protein bound simulations that this movement correlates with protein binding and not peptide binding. The peptide bound simulations suggest that peptides are poor surrogates for PCNA binding partners and may in fact disruptive increase their disruptive efficacy by combining direct inhibition of the PIP-box binding site with suppression of internal PCNA dynamics. Moreover, the pattern shown by the unbound PCNA indicates an internal bias of PCNA towards Fen1. This provides a mechanism through which we can explain how the lower affinity Fen1 protein is able to displace the tightly binding p21 during DNA replication. Overall these computational models of the PCNA structure not only provide a rationale for various protein binding to PCNA, but also provide insight into how PCNA is able to interact with its many partners. Supporting Information The Supporting Information file contains: Table S1: List of human PCNA structures available in the protein data bank; Table S2: PCNA structures studied in this work; Table S3: Summary of MD simulations performed; Figure S1: Comparative analysis of PCNA crystal structures; Figure S2: Cumulative variance in principal components.



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ACKNOWLEDGEMENTS: The Beckman Research Institute of the City of Hope funded this work.

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Figures

Figure 1: Crystal structure of PCNA sliding camp (PDB ID:1VYM). (a) The three identical monomers of PCNA are colored in green, cyan, and magenta; these monomers assemble to form a toroid shape. (b) A side view of the clamp structures shows the leading edge of the protein. The leading edge of the protein exposes the βH1-βI1 loop and βD2-βE2 loop towards DNA. The trailing edge of the protein contains the PIP box. (c) The tilted orientation of PCNA toroid when bound to DNA.


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Figure 2: Details of the PCNA protein binding domain. (a) monomer structure of PCNA. The carboxy terminus of PCNA is shown in red and the inter-domain connecting loop (IDCL) is shown in yellow. These two regions border a binding pocket where proteins containing PCNA interacting protein (PIP) sequences interact with PCNA. (b) The crystal structure of p21 bound PCNA (pdbID 1AXC) showing the interaction with PIP region in PCNA. The p21 peptide shown in magenta, as with most PIP containing peptides adopts a 310 helix. The hydrophobic pocket where the PIP motif is inserted shown in red surface and labeled as the PIP box.



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Figure 3: The first column shows the crystal structure of PCNA (green) bound to peptides from various partner proteins (cyan). The portion of the peptides resolved in the crystal structures are shown in cyan. In the middle column we show the modeled missing regions of PCNA from its crystal structure and that of the peptides in red. In the third column the representative structure


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of the peptide folded over the PCNA extracted from the MD simulations are shown in blue. This shows the folding of the modeled regions of the peptides (blue) onto the PCNA structure. This conformation is a representative structure of the most populated conformation cluster extracted from the 500ns MD simulations.


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Frequency of hydrogen bond contacts


Figure 4: Hydrogen bonds formed between residues in the bound peptide and the residues in the IDCL of PCNA. The plot shows the frequency of hydrogen bonds observed between the residues 120-134 of the IDCL and each bound peptide in the MD simulations. The hydrogen bond types are color coded blue (backbone-backbone), red (side chain-side chain), green (backbone of peptide to side chain of PCNA), and yellow (side chain of peptide to backbone of PCNA).


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Figure 5: The frequency of the van der Waal (vdW) contacts between the bound peptide with the IDCL residues in PCNA, calculated from the MD simulation trajectories. The orange bars represent distance measured under 5Å, the green bars distances under 4Å, and the blue bars distances under 3Å. The conserved PIP sequences are enclosed in the rectangle with the PIP sequence motif shown below. The contacts made outside of the PIP box are essential to rationalize the binding constants of various peptides.



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Figure 6: Fluctuations in the coordinates of each amino acid residue in the unbound PCNA monomer simulation compared to simulations of the PCNA monomer with bound peptides. (a) plot of the per residue backbone RMSF of the backbone atoms observed during the simulations. The unbound PCNA simulation shows slightly lower overall RMSF when compared to the peptide bound simulations. (b) Comparison of the RMSF of PCNA monomer bound to two different conformations of the full protein Fen1.


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Figure 7: The regions of PCNA involved in the collective motion of the principal component 1, PC1 are shown in red and blue colors. The two overlapping green structures are the conformations from the extreme ends of the PC1 space. The high overlap of the two green structures underscore the limited movements observed in the majority of PCNA. The regions of PCNA color in red and blue highlight significant changes in PC1 space. (a) The PIP box is highlighted in yellow. The movement of the IDCL loop starting with the red loop shows contraction of the PIP box region and ending with the blue loop. (b) The movement of the βH1βI1 loop opening up starting from red and ending up with the blue loop where the DNA binds is shown. (c) A box and whisker plot of the projection of each of the Fen1 bound simulations is shown to exemplify the extent of movement in the PC1 direction for the active like Fen1-PCNA conformation and inactive Fen1-PCNA conformation. The red line in the middle of the box is the median that divides the data into half and the box represents the middle half of the data (between 25th and 75th quartile) when we divide the spread in the PC1 values into four quarters.



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Figure 8: Box and whisker plots of the projection of principal component PC1 in each simulation of PCNA with various peptides bound, full Fen1 bound PCNA simulations, free PCNA monomer and PCNA trimer. The vertical red line drawn at 0.5 is shown to highlight the differences in the distributions of the simulations. The red line in the middle of each plotted box is the median that divides the data into half and the box represents the middle half of the data (between the 25th and 75th quartile) when we divide the spread in the PC1 values into four quarters.


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Figure 9: Similarity and differences in the dynamic motion of the three monomers in the unbound PCNA trimer MD simulations. (a) The box and whisker plot showing the extent of the movement along the principal component 1 (PC1) of each of the three monomers calculated from the PCNA trimer MD simulations. In MD simulations 1-4, two of the monomers show sampling of PCNA conformations similar to that of peptide bound PCNA states. The PC1 sampling of the third monomer is different from the other two and is characteristic of the unbound PCNA state. (b) The two monomers of Fen1 show a different conformation when bound to PCNA (shown in yellow) compared to the third one (cyan). This is akin to the conformations of two of the monomers of PCNA observed in the trimer crystal structure of PCNA bound to the full Fen1 protein (PDB ID 1UL1) as shown here. (c) We have projected the DNA through the PCNA trimer and show that in the yellow state conformation the catalytic site represented by the red sphere on Fen 1 is closer to the DNA and hence is in its active conformation. The cyan orientation of Fen 1 keeps the catalytic site away from DNA and hence in an inactive state conformation.



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For Table of Contents Use Only

How does the Proliferating Cell Nuclear Antigen modulate binding specificity to multiple partner proteins? Hubert Li1, Linda Malkas2, Robert Hickey2 and Nagarajan Vaidehi1,* 1 Department of Molecular Immunology, and 2Department of Molecular Medicine, Beckman Research Institute of the City of Hope, 1500, E Duarte Road, Duarte, CA – 91010


How Does the Proliferating Cell Nuclear Antigen ... - ACS Publications

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