Toward Understanding the Molecular Recognition of Albumin by p53

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Towards Understanding the Molecular Recognition of Albumin by p53 Activating Stapled-Peptide ATSP-7041 Garima Tiwari, and Chandra S. Verma J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.6b09900 • Publication Date (Web): 03 Jan 2017 Downloaded from http://pubs.acs.org on January 4, 2017

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The Journal of Physical Chemistry

Towards Understanding the Molecular Recognition of Albumin by p53 Activating StapledPeptide ATSP-7041 Garima Tiwari1* and Chandra S Verma1, 2,3* 1

Bioinformatics Institute, A*STAR (Agency for Science, Technology and Research), 30 Biopolis

Street, #07-01 Matrix, Singapore 138671 2

Department of Biological sciences, National University of Singapore, 14 Science Drive 4,

Singapore 117543 3

School of Biological sciences, Nanyang Technological University, 50 Nanyang Drive,

Singapore 637551

Address correspondence to: Garima Tiwari Bioinformatics Institute, A*STAR (Agency for Science, Technology and Research), 30 Biopolis Street, #07-01 Matrix, Singapore 138671 Tel: (65) 6478 8312; Fax: (65) 6478 9048; E-mail: [email protected] Chandra S Verma Bioinformatics Institute, A*STAR (Agency for Science, Technology and Research), 30 Biopolis Street, #07-01 Matrix, Singapore 138671 Tel: (65) 6478 8273; Fax: (65) 6478 9048; E-mail: [email protected]

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ABSTRACT: Reactivation of tumor suppressing activity of p53 protein by targeting its negative regulator MDM2/MDMX has been pursued as a potential anticancer strategy. A promising dual inhibitor of MDM2/MDMX that has been developed and is currently in clinical trials is the stapled-peptide ATSP-7041. The activity of this molecule is reported to be modulated in the presence of serum. Albumin is the most abundant protein in serum and is known to bind reversibly to several molecules. To study this interaction, we develop a protocol combining molecular modeling, docking and simulations. Exhaustive docking of the peptide with representative simulated structures of Human Serum Albumin (HSA) led to the identification of probable binding sites on the surface of the protein including both known canonical and novel binding sites. Sequence differences at putative peptide binding sites in human and mouse albumin result in differing interaction energies with the peptide and enable us to rationalize the observed differences in vivo. In general, the findings should help in guiding the designing in features into such peptides that may impact upon their distribution and cell permeability, opening a new window in structure guided design strategies.


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INTRODUCTION Protein-protein interactions (PPIs) are critical to most cellular processes and proper functioning/malfunction of their networks are central to health/disease1-3. This has resulted in substantial attention being paid towards the development of PPI modulators as molecular targets. PPI interfaces are generally large and relatively flat and therefore not easily targeted by small molecules resulting in limited success 4; however this scenario is changing with more sensitive screening technologies and now they are beginning to enter the clinic5-6. In recent years, peptide based modulators have gained a lot of attention because they can attain specificity through several weak interactions7. However, peptides are not suitable as therapeutics because of their low proteolytic and conformational stability, issues of serum half-life and cellular permeability89

. This has partially been overcome with the development of cyclization schemes that appear to

have partly overcome some of these issues10-11. One such technique is that of stapling, whereby stabilization of peptides is achieved by covalent linking of the peptides, particularly helical ones, and is beginning to find increased popularity12. A remarkable and yet enigmatic feature is that several of these stapled peptides are able to permeabilize cells and demonstrate biological functionality13-14. Successful application of stapling has been demonstrated by the development of stapled-peptide inhibitors of various PPIs such as p53-MDM2/MDMX15-19, eIF4E20, βcatenin21, ERα-coactivator protein22 etc. One of the stapled peptides, ATSP-7041, developed to be a dual inhibitor of MDM2/MDMX, has unambiguously been shown to effectively enter a panel of human cancer cell lines and activate p53 with great potency; this peptide has progressed to clinical trials17. ATSP-7041 showed improved target binding properties as compared to other stapled peptides in the presence of serum16-17.



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However, retention of the peptides in serum is necessary to ensure proper pharmacokinetics in the body. Hence, a detailed molecular-level understanding of the interactions of these peptides with albumin can provide guidance for rational design strategies that can manipulate serum interactions with peptides to yield an optimal balance between their distribution, half-life and potency. A major component of serum is the protein Human Serum Albumin (HSA) which binds reversibly to various ligands23. The ability of HSA to bind such a diverse range of molecules unsurprisingly modulates the pharmacokinetic (distribution and half-lives) behavior of many drugs24-26. HSA is a monomeric protein of 66 kDa comprising of 585 amino acids with three similar α-helical domains namely I, II and III arranged in the shape of a heart27-28 (Figure 1). Each domain is further divided into subdomains A and B which contain six α-helices and four αhelices respectively. Several drug binding sites on HSA have been reported24. In the 1970s, Sudlow et al had proposed two canonical drug binding sites29-30 and these were later shown crystallographically to be located in subdomains IIA and IIIA (and termed Sudlow’s Sites I and II) respectively. Sudlow’s Site I is known to bind bulky heterocyclic anions such as warfarin whereas aromatic carboxylates like ibuprofen and diazepam are found at Sudlow’s Site II31. Recently a third binding site located in subdomain IB was revealed by circular dichroism studies32-33. Wang et al (2013) also showed that several oncology drugs bind to this third drug binding site34. In addition, drugs are also reported to bind non-specifically at other regions on HSA, which overlap with known fatty acid binding sites24, 35. There are nine such known fatty acid binding sites as revealed by crystallographic studies out of which seven seem to prefer long chain fatty acids (FA 1-7) and two prefer short chain fatty acids (FA8 and FA9)27, 36.


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Given that HSA interactions are critical for the efficacy of drugs, it is desirable to define a protocol to model how a drug interacts with HSA37-39. Such models hold the potential to help understand whether two different drugs will compete for the same site if administered simultaneously, thereby reducing their efficacies. This could then provide additional parameters for redesigning drug molecules or for planning drug dosage regimens. Given that ATSP-7041 is the first stapled-peptide to enter clinical trials and has been shown to interact with HSA17, we aim to model the molecular details of the interactions between the stapled-peptide ATSP-7041 and HSA. We combined exhaustive docking and refinement with molecular dynamics (MD) simulations to develop a protocol for modeling the binding of such molecules to HSA, and identify two potential binding sites of the stapled-peptide on HSA. One of these is found to partially overlap with the Sudlow’s Site II whereas the other site appears to be a novel binding site. Both these regions accommodate the peptide through the formation of a binding pocket and the molecular association is driven primarily by hydrophobic interactions between the protein and the peptide, engaging the hydrocarbon linker of the stapled-peptide. We further used this information to rationalize the observed differential binding of ATSP-7041 to human and mouse albumin17.

MATERIALS AND METHODS Generating Representative Structures of HSA for Docking. The starting coordinates for HSA were retrieved from the Protein Data Bank40 (PDB ID: 1E78 (2.6 Å)41). The structure contains two molecules in the unit cell of which we selected chain A to represent the apo state since the biologically active state of albumin is a monomer and also because this chain has relatively more resolved atoms than chain B. The crystallographic water molecules were 5 ACS Paragon Plus Environment


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removed because of their very high B-factor values (30-50 Å2). The structure was then subjected to 50 ns MD simulation in order to generate multiple representative states for docking. Details of the simulation protocol and parameters are described in the section below in the section titled “MD simulations”. The ensemble of structures generated from the 50 ns trajectory was clustered into distinct sets using the average-linkage algorithm42 with the desired cluster number set to five. Pairwise RMSD between the structures was used as a distance matrix. The clustering method was applied to the backbone heavy atoms of the protein. A total of 10000 structures for the apo state HSA were used for clustering. The structures were extracted at equal intervals over the entire range of the simulation trajectory. The five structures along with the starting state crystal structure were then used as representative structural states of HSA for docking. Docking HSA with the Stapled-Peptide ATSP-7041. The only available crystal structure of the stapled-peptide ATSP-7041 is that of its complex with MDMX (PDB ID: 4N5T, (1.7 Å)17). This was downloaded from the PDB and chain B corresponding to the peptide (L17-T-F-R8-E-YW-A-Q-Cba-S5-S-A-A30; R8 and S5 depicts hydrocarbon linker, Cba is modified Leucine) was extracted from the complex. The molecular docking program ATTRACT43-44 was used to dock the stapled-peptide (ATSP-7041) against all six representative structures of HSA. This program has recently been shown to successfully identify known peptide binding sites on protein surfaces45-46. The docking program was first validated by redocking a fragment of the neonatal Fc receptor (FcRn) that has been crystallized bound to HSA. FcRn is a heterodimer of MHC class I-like α chain and β2-microglubulin. The structure of the HSA-FcRn complex (PDB ID: 4K71 (2.4 Å)47) was downloaded from the PDB and chain A corresponding to HSA was chosen as the receptor and chains B and C corresponding to the FcRn heterodimer were selected as one molecular entity to be docked on to HSA. Of the resulting docked conformations, the top hit was


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very close to the crystal structure (Supplementary Figure S1). With a benchmark established suggesting that ATTRACT may be suitable for docking peptides on to HSA, we next docked ATSP-7041 on to HSA. The hydrocarbon linker (the staple) of ATSP-7041 had to be parameterized by using equivalent atoms types belonging to the standard amino acids as reference. A blind docking strategy was used to generate ~24000 docking solutions for each of the six receptor states. All the generated docked conformations were grouped into different clusters using the K-means clustering algorithm48 which resulted in a total of ~40 clusters for each receptor. A representative structure for each cluster was chosen based on the criteria that the peptide had the lowest RMSD from the centroid of the cluster. These receptor-peptides complexes were then subjected to 5 ns implicit solvent MD simulation each (details mentioned below in the section titled “MD simulations”) to examine and filter out the probable weak/bad binders from the complexes i.e. if a peptide in a certain conformation would dissociate from the starting state during the simulations, that conformation was discarded. The resulting set of stably bound docked conformations from all six systems was pooled together and clustered into distinct regions on the protein surface (Supplementary Figure S2a). The four highly populated regions, namely R1, R2, R3 and R4, were considered as potential binding sites. A representative stapledpeptide:HSA complex structure was selected from each of the four identified regions and subjected to 100 ns of all atom explicit solvent MD simulations in triplicates. The criteria for choosing the representative stapled-peptide:HSA complex structure is explained in the figure legends (Supplementary Figures S2b & S2c). The detailed overall protocol followed for the identification of binding sites on HSA is shown in Supplementary Figure S3. MD Simulations.

MD simulations were carried out using the AMBER1249 simulation

package and ff99SB force field parameters50. Each structure was solvated in a box with TIP3P



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water molecules such that the sides of the box were at least 10 Å from any protein atom. The systems were neutralized by adding appropriate numbers of ions and subjected to three rounds of energy minimization using 500 steps each of steepest descent followed by conjugate gradient algorithms. The first two minimization rounds were carried out by imposing positional restraints on the protein and solvent heavy atoms respectively followed by a fully unrestrained minimization of the whole system. The system was then gradually heated to 300 K under NVT conditions and equilibrated to 1 atm using the NPT ensemble for a period of 500 ps. Langevin dynamics51-52 with a collision frequency of 1 ps-1 was used to regulate the temperature and a weak coupling algorithm53 was employed to maintain the pressure with a relaxation time of 1 ps. The equilibrated system was finally subjected to production dynamics under NPT conditions. A cut-off of 8 Å was used to compute non-bonded interactions and Particle Mesh Ewald (PME)54 was employed for computing long-range electrostatic interactions. To constrain all bonds involving hydrogen atoms, the SHAKE algorithm55 was used, enabling an integration time step of 2 ps. The implicit solvent simulations were carried out by imposing positional restraints on backbone heavy atoms of HSA and the solvent effect was represented by using a generalized born solvation model56. The following systems were subjected to MD simulations using the protocol described above. 1. HSA and ATSP-7041: HSA Complex. The parameters for the hydrocarbon linker in ATSP-7041 were derived using the protocol published by Tan et. al.57. The N- and C-termini of HSA were capped with ACE (acetyl) and NME (N-methylamide) respectively. The N-terminal of the stapled-peptide ATSP-7041 was acetylated (ACE) whilst the C-terminal was amidated (NHE). All 17 native disulphide bonds were maintained in the HSA structure using the bond command in the tLeap module of AMBER12.


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2. DZP: HSA Complex. In order to gauge the experimental affinity of ATSP-7041 for HSA, we decided to compute the affinity of diazepam (DZP) for HSA since both its affinity (12 µM)58 and the crystal structure of its complex with HSA is known. The crystal structure of Diazepam (DZP) in complex with HSA was downloaded from PDB (PDB ID: 2BXF (2.95 Å)24). The parameters for the small molecule DZP were assigned using the Antechamber module of AMBER1249. The AM1-BCC method was used to calculate the partial charges and bond length, bond angle, dihedral and van der Waals parameters were obtained by assigning GAFF (Generalized Amber Force Field) atom types59. 3. ATSP-7041: MDM2 and ATSP-7041: MDMX Complexes. Given that the main objective is for the peptides to partition from albumin to their intended intracellular targets MDM2 and MDMX, we decided to compute the binding affinities of ATSP-7041 with the N-terminal domains of MDM2/MDMX. The crystal structures of stapled-peptide:MDM2 (PDB ID: 3V3B (2.0 Å)60) and high affinity p53 peptide:MDMX (PDB ID: 3FDO (1.4 Å)61) complexes were downloaded from the PDB. The stapled-peptide and the high affinity p53 peptide were replaced in their respective complexes by the coordinates of ATSP-7041. Modeling of ATSP-7041-albumin (mouse) Complexes. Binding of ATSP-7041 has been experimentally studied and reported for albumin from human, mouse, rat, dog and monkey17. The fraction of unbound peptide was estimated at 2.8% in human to 7.7% in mouse. Given that this difference is not very large, we wondered whether the peptide bound to similar sites in the albumins from the two species and that small residue differences may account for these differences. So we decided to compare the human with mouse as the mouse albumin (MSA) represents the weakest binding. Since, there are no structures available for MSA, it was modeled using the automated method of SWISS-MODEL62 homology modeling server taking the



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structure of HSA (PDB ID: 1E78 (2.6 Å)41) as template. The GMQE score (number between zero and one) where higher value indicates higher reliability was calculated to be 0.92 indicating that the model is reliable62. MSA shares 72 % sequence identity with HSA23 and the probable binding sites identified for HSA are quite similar in mouse (Supplementary Figure S4), therefore we additionally assumed that the peptides would dock in the same regions in MSA. Hence, the MSA model was superposed onto HSA and then the co-ordinates of the representative peptides from R1, R2, R3 and R4 in the HSA complexes were transferred to MSA resulting in four MSApeptide complexes, representing all four binding regions as identified in the case of HSA. The complexes were refined by explicit MD simulations using the protocol described above in the section titled “MD simulations”. Peptide Mapping and Cavity Volume Calculation. For each albumin-peptide complex, three MD runs starting with different random seeds were carried out for 100 ns each and were combined together to yield a trajectory of 300 ns. The Grid command in the PTRAJ module of AMBER12 was used to generate the occupancy map of the peptides in the selected regions. Grid cells of size 0.5 X 0.5 X 0.5 Å were used for calculating the number of peptide atoms within each grid cell. The results were analyzed using Chimera63. A cut-off isocontour value of 10 was chosen for analyzing the peptide map. The criterion was chosen randomly to map the peptide binding regions in all four potential binding sites. The trj_cavity64 program was used for calculation of cavity volume both in the presence and absence of peptide. A grid spacing of 1.2 Å was used along with other default parameters for calculating the cavity volume. Binding Energy Calculations using MM/GBSA. Binding energy between the peptide and protein was calculated by using the MM/GBSA (Molecular Mechanics / Generalized Born Surface Area)65 method using the MMPBSA.py script66. Regularly spaced snapshots were


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extracted from the last 50 ns of each trajectory giving a total of 500 structures. The Generalized Born solvation model56 was used for the implicit representation of the solvent molecules, with a salt concentration of 0.15 mM. The solvent accessible surface area was computed using a recursive method of approximating a sphere around an atom starting from an icosahedral shape. The estimated binding free energy was computed as the following difference: ∆Gbinding = Gcomplex – Galbumin - Gpeptide

RESULTS Identification of Putative Binding Site(s) of ATSP-7041 on HAS. Exhaustive molecular docking of ATSP-7041 against representative simulated and X-ray structures of HSA followed by a rigorous refinement protocol (Figure 2 & Supplementary Figure S3) lead to the identification of four potential binding sites (termed R1, R2, R3 and R4) on HSA; these sites are found to be located in specific or overlapping regions of the subdomains in the protein. R1 is located in IIIA, R2 was found to locate to a region which overlapped between IIIA and IIIB, R3 lies specifically in IA and R4 locates mostly in IIB and in parts of IIIA (Supplementary Figure S2a). Interestingly subdomain IIIA which harbors the known Sudlow’s Site II in HSA was found to be part of three (R1, R2 and R4) potential ATSP-7041 binding sites. MD simulations of the representative protein-peptide complexes initiated from each of these four identified regions indicate that the peptide from R3 (subdomain IA) dissociated as observed by a dispersed peptide occupancy (Figure 3). This suggests that the region does not stably accommodate the peptide. In contrast, peptides in R1, R2 and R4 were stable with distinct peptide occupancy maps (Figure 3). The peptide occupancy map in R2 is also dispersed



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between subdomains IIIA and IIIB and some parts of subdomain IB. In addition, the R2 region overlaps with the known binding site of the FcRn receptor which is involved in the recycling of albumin67. We hypothesize that under physiological conditions, the peptides bound in R2 would largely be competed out by the indigenous receptor; and in any case, the peptides do not show particularly strong binding in this region (Supplementary Figure S5). Taken together, we believe that regions R1 and R4 are more likely to be the preferred sites for specific and strong binding of ATSP-7041. Characterization of Specific ATSP-7041 Binding Sites on HAS. Region 1 (R1). The region R1 is observed to be the most densely populated site in terms of the number of peptides clustered and overlaps with the known Sudlow’s Site II in subdomain IIIA29-30. The peptide docks into a hollow cavity which has a “floor” made up of hydrophobic residues (L387, I388, L398, G399, F403, L407, G431, L430, V433, G434, A449, L453, V455, V456, L457) and the “entrance” lined by polar residues (E383, N386, Q390, N391, E393, Q397, R410, Y411, K414, R485, S489, E492) (Figure 4a). This cavity covers a wider space as compared to the drug binding pocket of this region which is relatively narrow (Figure 4b). The binding energy of the peptide in this region as computed from multiple simulated trajectories is found to be favorable at –30.74±6.9 kcal/mol (Table 1). This is comparable to the computed binding energy of -36.33±2.3 kcal/mol calculated for the small molecule Diazepam bound to Sudlow’s Site II (PDB ID: 2BXF24), suggesting that the peptide probably binds to this region with micromolar affinity (the affinity of diazepam for HSA has been reported to be 12 µM58). Both electrostatics and van der Waals energy components are found to contribute significantly towards the total binding energy, which suggests that the peptide is stabilized in the bound state conformation by both hydrophobic and hydrophilic interactions. The hydrocarbon linker of


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ATSP-7041 is found to make very significant molecular contacts with the protein residues (Figure 5 and Table 2). The three critical residues (F19, W23 and Cba26) which are important for the interaction of this peptide with MDM215, 68 are also observed to be involved in forming hydrophobic interactions with HSA. W23 occupies a cleft in the cavity and is the most predominant residue involved in the association. It is very interesting to observe that the mode and nature of the molecular recognition (formed by the staple, F19, W23 and Cba26) between the stapled-peptide and HSA is very similar to that observed when it docks into the hydrophobic pocket of MDM2. The peptide also forms specific hydrophilic interactions primarily involving residue R410 which may gate the accessibility of the peptide to this cavity69. In the bound state of the peptide, R410 is found to form a hydrogen bond interaction with the backbone carbonyl oxygen of residue A24 in ATSP-7041. R410 is known to form hydrophilic interactions with drugs that are found to be complexed at Sudlow’s Site II24. The other specific hydrophilic interaction involves the hydrogen-bond between the side-chain hydroxyl group of S28 and the side-chain carbonyl oxygen of E492 and may be a site that could be subject to mutations to modulate the affinity; it will be interesting to see if variants of ATSP-7041 at the C-terminal end and at S28 differ in their affinities for HSA. The stapled-peptide as mentioned above docks into a cavity whose volume increases when the peptide is bound to the protein (Supplementary Figure S6). This observation indicates that the residues lining the entrance of the cavity should have a significant role in modulating the size of the cavity (Figure 6a). We computed the distance between residue pairs which are present at the “entrance” of the cavity and observed that residue pairs L394-A406, N391-R410 and Q390R410 show significant differences in their contact distances between the complexed and uncomplexed states of the protein. All these residue pairs are in relatively closer proximity in the



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uncomplexed state as indicated by their lower separations (Figure 6b). The residue pair Q390R410 has already been reported in the literature to play a crucial role in gating access to Sudlow’s Site II69. Thus, we see that the binding region is highly plastic which enables it to modulate the cavity in the region in order to accommodate the peptide favorably. Region 4 (R4). The region R4 is the second highest populated site in terms of the number of peptides clustered here and overlaps between subdomain IIB and some parts of subdomain IIIA (Supplementary Figure S2a). The residues present at the binding region of R4 consist of both hydrophobic and polar residues (L305, A306, Y334, R337, H338, Y341, A371, K372, F374, D375, F377, K378, V381, E382, Q385, E442, A443, M446) (Figure 7a). This binding interface does not possess a well-defined cavity as was seen in region R1 and the surface is relatively flat. However, a shallow binding groove is formed/induced at the binding interface on the surface of albumin in the presence of the peptide. This interface is novel as no drugs or other ligands have yet been reported to specifically interact with HSA in this region. The binding energy of the peptide in this groove -43.68±5.7 kcal/mol is quite favorable (Table 3), and is stronger than in R1 (–30.74 ± 6.9 kcal/mol). Unlike in R1, the van der Waals energy is found to dominate the total estimated binding free energy in R4, which suggests that hydrophobic interaction is the major driving force for the stability of the bound state of the peptide in this region (Table 3). This is also indicated in the residue contact analysis of this region where significant molecular contacts are made with the hydrophobic residues. The hydrocarbon linker fits nicely into a groove formed on the protein surface and hence is involved in extensive hydrophobic interactions with HSA (Figure 7b and Table 4). The other residues which are predominant in the interaction are F19 and W23 which are again two of the three critical residues involved in the interaction of this stapled-peptide with


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MDM2. In addition, the side-chain amide nitrogen of W23 forms a hydrogen-bond with the hydroxyl group of Y334 which is the only significant hydrophilic interaction observed. Origin of the Differences in Binding of ATSP-7041 to MSA and HAS. Experimental evidence suggests that there are differences in the specificity of ATSP-7041 binding between human and other mammalian albumins, with the most significant variation observed between human and mouse17. This is demonstrated by the difference in terms of peptide unbound fractions, reported at 2.8% and 7.7% in the case of HSA and MSA respectively17. HSA and MSA are homologous proteins with a high sequence identity of ~72% which suggests similar structural and functional properties. In order to investigate the molecular basis of this difference between the two molecules, we modeled the molecular structure of MSA using HSA (PDB ID: 1E78) as the template. If we compare the regions of HSA where the ATSP-7041 is bound with the homologous regions in MSA, we see that they are quite similar (Supplementary Figure S4). Given this similarity, we hypothesize that the MSA would most likely have the same preferred binding interfaces for ATSP-7041 as was observed for HSA, albeit with differences in specificity. The selected peptide co-ordinates from all the identified regions (R1, R2, R3 and R4) of HSA were then transferred to the modeled structure of MSA and subjected to multiple explicit solvent MD simulations. During the simulations it was observed that the peptides from regions R2 and R3 dissociate rapidly (Supplementary Figure S7) which indicates that these two sites likely do not accommodate the peptide, as was the case with HSA. On the other hand, the peptides were found to be bound to the protein in the regions R1 and R4 and we hypothesize that these two sites are, as in the case of HSA, more likely to act as the specific docking sites for the peptide.



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During the MD simulations, ATSP-7041 remains bound in these regions, and the occupancy maps in both R1 and R4 are quite similar to the corresponding maps generated for HSA (Figure 8) with the region R1 characterized by a somewhat smaller volume in MSA (Supplementary Figure S8a). The binding energy of the peptide is favorable for both R1 and R4, but is consistently less favorable for mouse compared to human in all the replicate simulations (Supplementary Figure S8b & S8c). Thus, modeling suggests that ATSP-7041 has a lower affinity for MSA compared to HSA and is in qualitative agreement with the experimental observations of a higher fraction of peptides bound to human compared to mouse albumin17. Dissecting the Molecular Determinants Responsible for Differences in Binding Region 1 (R1). The residues in region R1 which contribute significantly towards the peptide binding energy are all conserved in HSA and MSA except for Q390T, L407I and E492T substitutions (Supplementary Figure S9a). The electrostatic surface potential of R1 in both HSA and MSA suggest that the binding interface is mainly positively charged and makes it optimal for negatively charged peptides (Supplementary Figure S9a). E492T results in a less negatively charged pocket in MSA. In both human and mouse albumins, the contacting residues of ATSP7041 are the same but due to change in the optimum mode of binding the contacting residues differ (Supplementary Table S1). The hydrophobic residues namely, the staple chain, W23, F19, Cba26 and A24 are the major contributors in binding to albumin but they are more favorable in HSA as compared to MSA (Figure 9a & Supplementary Table S2). Further, the contacting residues from albumin i.e. L387, L394, F403, L407 and S489 contribute more in HSA than in MSA (Supplementary Table S1 & S2, Figure 9a& 9b). Due to the change in binding mode there are few favorable interactions observed in the case of MSA i.e. E21-R410 and Cba26-N386 out of which only E21-R410 makes a significant contribution towards the total binding (Figure 9a & 16 ACS Paragon Plus Environment

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9b). Cba26 contributes almost equally in both HSA and MSA (Supplementary Table S2). S28 is one of the major discriminators in both human and mouse as it doesn’t interact with MSA while it makes significant contributions in the case of HSA. Only L407I seems to play a direct role in modulating the binding of the peptide to albumin; of course, it is possible that Q390T and E492T affect the cavity volume and hence the affinity in MSA. Overall, the energetic contributions from the three critical residues F19, W23, Cba26 and the hydrocarbon staple chain are reduced in the case of MSA resulting in the lower overall affinity. Region 4 (R4). The residues that contribute significantly to the peptide-protein interactions in region R4 are also largely conserved between HSA and MSA (Supplementary Figure S9b). Unlike in R1, here the surface is mostly hydrophobic surrounded by red patches (negatively charged regions), which are more in the case of MSA (Supplementary Figure S9b). Hence, in the case of MSA R4 will not be an electrostatically favored binding site for a negatively charged peptide, or at least will have altered kinetics of recognition. The binding is mainly driven by hydrophobic interactions. Interestingly, the significant substitution (K372T, D375A, and K378Q) observed between the two proteins are localized on one side of the binding groove relative to the peptide. It involves mutation of charged residues from HSA to either polar or hydrophobic residues in MSA (Figure 10a & 10b). The charged residues in HSA can interact favorably with the solvent as compared to hydrophobic residues in MSA. This results in greater plasticity of the binding interface in HSA and hence the formation of a more pronounced peptide-induced binding groove in HSA (Figure 10b). The number of contacting residue pairs are almost similar in both human and mouse (Supplementary Table S3) but the optimum binding modes are different. Consequently, the optimum mode of binding of the peptide in HSA is more favorable in terms of the binding energy contributions of W23 and the hydrocarbon staple chain, which



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acts as a dominant factor for the higher affinity for HSA (Supplementary Table S4 and Figure 10a & 10b). Thus, in spite of the fact that the putative peptide binding regions are mostly conserved between HSA and MSA, the subtle variations observed in terms of the mutations present in and around the binding regions likely influence the binding and hence provide a compelling reason for at least partly accounting for the experimentally observed differences in specificity of ATSP-7041 binding to HSA and MSA.

DISCUSSION One of the major challenges in the current development of stapled-peptides as drugs is the paucity of insights on understanding the detailed mechanisms of their cellular uptake which greatly restricts the design and development of these inhibitors for potential therapeutic applications8. It is clear that a variety of stapled peptides do enter cells70 and elicit the intended biological response; ATSP-7041, a potent and specific dual inhibitor of MDM2 and MDMX with efficient cell penetrating and p53 activating properties has shown strong efficacy in multiple human cancer cell lines17 and is a prototype71 of an analogue that is currently undergoing clinical trials (ClinicalTrials.gov identifier NCT02264613). Yet the mechanisms that port them into cells remain enigmatic and even as the search for such agents is underway10, attempts are ongoing in enhancing the transport of the peptides into cells using other forms of delivery methods72. Albumin, the major protein component of plasma, is taken up preferentially in tumor and inflamed tissues, thus making it an ideal candidate as a vehicle for drugs targeting tumor cells73. It has been reported to act as a potential carrier for polypeptide and protein-based drugs73. Towards this we have developed molecular models of hypothetical modes of interactions between the stapled-peptide ATSP-7041 and albumin using a protocol of exhaustive molecular 18 ACS Paragon Plus Environment

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docking and simulations. This resulted in the identification of two probable ATSP-7041 binding regions on HSA, namely R1 located in subdomain IIIA and R4, which is found to cover a region that extends between subdomain IIB and some parts of subdomain IIIA. The subdomain IIIA in albumin has previously been reported as being one of the most preferred sites of binding for peptides, although there is no structural data available. Circular dichroism studies have shown that the amino terminal peptide FP-I of HIV-I gp41 protein binds to subdomain IIIA74. HSA has been found to play a major role in preventing aggregation of Alzheimer’s Aβ peptide by binding to Aβ oligomers75. Although NMR suggests that the Aβ oligomer binding site is evenly distributed across the three albumin domains i.e. I, II and III, the affinity of subdomains IIIA and IIIB lies in the sub-µM range76. Modified peptides like cyclic tetrapeptide and cationic antimicrobial peptide were also shown to bind to subdomain IIIA of HSA69, 77 and have affinity in the micromolar range. The region R1 comprises of a pre-formed hydrophobic cavity lined by polar residues and it overlaps with Sudlow’s Site II which is known to bind small organic molecules24. The R1 binding cavity is seen to be highly dynamic and adaptable which thereby enables it to efficiently accommodate the stapled-peptide. Taken together, we believe that region R1 located in subdomain IIIA of albumin would be one of the most preferred sites of binding for ATSP-7041 peptide, and in analogy with the known binder Diazepam at this region, we speculate that the peptide will also bind with micromolar affinity. The other identified region R4 is a potentially novel binding site as there is no information regarding any known molecules interacting at this site. Unlike R1, there is no pre-formed cavity in this region and the R4 binding surface is mostly flat. However, the interface is also very plastic which enables the peptide to induce a shallow binding groove on the surface for interaction. The other significant difference between R1 and R4 is in the nature of the chemical interaction in both regions: in R1 the



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complexation is driven by both hydrophobic and hydrophilic interactions while in R4, it is predominantly hydrophobically driven. Interestingly, the mode and nature of the hydrophobic interactions (mediated by the staple chain, F19, W23 and Cba26) between the stapled-peptide and albumin is very similar to that observed in the case of ATSP-7041:MDM2/MDMX protein complexes17. To investigate this in some detail, we carried out MD simulations of ATSP-7041 complexed to MDM2 and to MDMX and find that the overall binding energies are -68.16 kcal/mol and -66.19 kcal/mol respectively; these are clearly stronger than the affinities for HSA (-30.74 kcal/mol and -43.67 kcal/mol respectively at the two sites R1 and R4) with the binding driven predominantly by van der Waals packing interactions. Decomposition of the overall binding energies into contributions from individual residues of ATSP-7041 (Figure 11) show that interactions which enable the peptide to bind tighter to MDM2/MDMX originate in F19, Y22, W23 and Cba26, all being driven by stronger packing interactions (Supplementary Figure S10); in contrast the staple interactions with HSA are stronger. This strongly indicates that the triad of hydrophobic residues responsible for the specificity of the interaction between the stapled-peptide and MDM2/MDMX is also critical for the association with albumin; with the staples interacting stronger with HSA, it will be interesting to see what the future studies of HSA interactions with peptides carrying different staples14 will reveal. The ATSP-7041 peptide has been shown to have differential specificity towards albumin from different organisms with the largest variation observed between HSA and MSA17. The identification of these potential binding sites on HSA could serve as a reference to understand the possible factors for the differences seen in the association of ATSP-7041 between the human and mouse proteins17. We observe that as in HSA, the peptide also binds favorably to the structurally homologous regions (of R1 and R4) in MSA. The binding interfaces in both R1 and


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R4 are largely conserved between human and mouse except for some specific amino acid differences which affect the nature of the surface either in terms of reducing the cavity volume as in R1 or affecting the plasticity of the interfacial region as in R4. Both these factors significantly influence the peptide’s mode of docking in the region and hence, we speculate the binding specificity and affinity. These models thus provide a possible rationale for the observed differences reported in the binding of ATSP-7041 between the two organisms17. The major contributions made by the stapled peptide towards binding to albumin engage the residues critical for binding to MDM2/MDMX, the targets of the stapled peptides. This places a constraint on their modifications for any modulation of binding to HSA. However, the residue S28 makes sidechain interactions with the protein and thus offer a region of the peptide where suitable modifications may enable the desired affinity for HSA without affecting binding to MDM2/MDMX. There are nine known and well characterized fatty acid binding sites on albumin and none of the known fatty acid binding sites overlap with R4. Hence, the interaction of the stapled-peptide with albumin at this site should not be directly affected by the presence or absence of fatty acid. However, any conformational changes and long range allosteric effect due to the presence of the fatty acid cannot be ruled out. On the other hand, it is clear that at R1 the binding sites of two known fatty acids do overlap with that of ATSP-7041 suggesting that the interaction of the stapled-peptide with albumin at this site may be directly affected by the presence of the fatty acid (Figure 12). Under conditions where fatty acid is present, it is likely that R4 will be the preferred site of binding for the stapled peptide. This immediately suggests a testable hypothesis that the fraction of stapled-peptide bound to albumin would likely decrease in the presence of fatty acid.



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CONCLUSIONS In summary, the knowledge derived from this study of ATSP-7041 and HSA provide some grounds for speculating the probable binding mechanism between the two molecular entities. It should in general, assist in the modulation of the binding of peptides to HSA by designing in required features (such as tighter or weaker binding) for the appropriate use of HSA as a carrier for peptide distribution and improving its half-life. The nature and specificity of the interaction between the peptide and albumin should also provide a basis to develop an understanding of the observed variation of the degree of potency of the peptides in experiments with serum obtained from different sources. While the higher affinity for MDM2/MDMX compared to that for HSA will ensure that the peptide partitions into the former and elicits the desired biological response, what is not clear is the required optimal ratios of these affinities and the relationship between affinity of the peptide for albumin, its systemic circulation and eventual delivery to the required tissues/cells; such data from experiments is eagerly awaited to begin to design in these subtleties. Of course there are other levels of complexities in understanding the permeability of these peptides such as the role of the FcRN receptor and its interactions with albumin in endosomes78 which will need to be factored in once more experimental data becomes available.

An

interesting insight may be drawn from such studies relates to the observation that the affinity of stapled-peptide is similar to that of diazepam for HSA; such insights may also be used at some stage in guiding the protocols of timing the treatment of patients who are on other medications such as diazepam. Finally, the rigorous process and multi-scale protocol as developed in this study has the potential to be used for the identification of potential binding sites of other stapledpeptides for albumin.


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Supporting Information Available. Benchmarking of docking program (Figure S1); Screening of docking solutions (Figure S2); Protocol for identification of potential binding sites (Figure S3); Sequence alignment of HSA and MSA (Figure S4); Structural superimposition of HSAATSP-7041 (R2) and HSA-FcRn complex (Figure S5); Cavity volume of R1 binding site (Figure S6); Peptide occupancy map of R1, R2. R3 and R4 in MSA (Figure S7); Comparison of cavity volume of R1 between HSA and MSA (Figure S8a); Comparison of the computed MM/GBSA binding energies of ATSP-7041 in R1 and R4 between HSA and MSA (Figure S8b & S8c); Comparison of R1 and R4 binding sites between HSA and MSA (Figure S9, Figure S10 and Tables S1-S4).

Acknowledgements We thank Dr. Dilraj Lama for his guidance and valuable discussions on the manuscript. We thank Dr. Tan Yaw Sing for providing the parameters of staple-peptide ATSP-7041 and Dr. Srinivasaraghavan Kannan for his help and guidance in using ATTRACT package. We also thank all the members of the group for helpful discussions and suggestions. This research was supported by the JCO grant (JCO1231BFG036). We thank A*STAR Computing Resource Centre (A*CRC) for computing facilities.

Notes The authors declare no competing financial interest.



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Table 1. Contributions Made by Electrostatics, van der Waals and Solvation Energy Components to the Total Estimated MM/GBSA Binding Energy Between ATSP-7041 Located in R1 (HSA) and between Diazepam and HSA (the pose taken from the crystal structure 2BXF) vdWa EELb EGBc ESURFd ∆Gsole (kcal/mol) (kcal/mol) (kcal/mol) (kcal/mol) (kcal/mol) R1 Run1 Run2 Run3 2BXF Run1 Run2 Run3

∆GTOTALf (kcal/mol)

-62.43 -55.87 -45.20

-71.20 -59.52 -0.03

111.97 97.10 38.02

-9.09 -7.92 -6.61

102.89 89.18 31.41

-30.74 (±6.9) -26.21 (±6) -13.82 (±5.3)

-41.81 -39.87 -42.55

-12.99 -11.99 -15.23

25.73 24.51 26.72

-5.18 -4.94 -5.27

20.55 19.57 21.45

-34.26 (±2.6) -32.29 (±2.3) -36.33 (±2.3)

Run1, Run2 and Run3 depict three replicates of 100 ns each. avan der Waals contribution; belectrostatic energy; cpolar contribution to the solvation free energy; d nonpolar contribution to the solvation free energy; esolvation free energy=EGB+ESURF; ffinal estimated binding free energy. Table 2. HSA (R1) Residues in Contact with the Residues of ATSP-7041 Peptide Res Albumin Res Occupancy (%)a A24 R410 99 S28 S489 92.2 Staple F403 90.8 W23 Q390 87.2 W23 L387 83 W23 N391 80 Staple A406 79.4 Staple L407 66.6 W23 L394 63.6 F19 L394 63.2 Cba26 Q390 59.2 Staple L394 56.8 Staple S489 54.4 S28 R410 52.2 S28 E492 52 Staple L398 51.2 a

A distance cut-off of 4 Å between any two heavy atoms was used to define a contacting residue pair between albumin and peptide. The contacts have been calculated taking the MD simulated trajectory showing the best binding energy of the three replicates. The occupancy of contacting residue pairs were calculated and only those contacting residue pairs which were present in more than 50% of the albumin−peptide complexes in last 50 ns of the 100 ns MD trajectory are reported.


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Table 3. Contributions Made by Electrostatics, van der Waals and Solvation Energy Components to the Total Estimated MM/GBSA Binding Energy between ATSP7041 Located in R4 and HSA R4 vdWa EELb EGBc ESURFd ∆Gsole ∆GTOTALf (kcal/mol) (kcal/mol) (kcal/mol) (kcal/mol) (kcal/mol) (kcal/mol) -35.07 96.80 -78.93 -4.68 -83.60 -21.87 (± 4.3) Run1 -62.09 77.63 -40.05 -8.26 -48.31 -32.77 (± 5.8) Run2 -69.38 99.11 -64.63 -8.77 -73.40 -43.68 (± 5.7) Run3

Run1, Run2 and Run3 depict three replicates of 100 ns each. avan der Waals contribution; belectrostatic energy; cpolar contribution to the solvation free energy; dnonpolar contribution to the solvation free energy; esolvation free energy=EGB+ESURF; ffinal estimated binding free energy. Table 4. HSA (R4) Residues in Contact with the Residues of ATSP-7041 Peptide Res Albumin Res Occupancy (%)a W23 Y334 99.8 W23 F374 98.2 Staple H338 96.8 W23 F377 89.2 Staple Y334 89 Staple Y341 80.4 W23 V381 79.2 Staple Y334 75.8 Staple F374 75.2 Staple L305 74 W23 K378 72 F19 A371 70.8 F19 F374 67.6 F19 K372 67.2 F19 D375 61 W23 L349 60.6 A29 A443 59.2 Cba26 V381 58 a

A distance cut-off of 4 Å between any two heavy atoms was used to define a contacting residue pair between albumin and peptide. The contacts have been calculated taking the MD simulated trajectory showing the best binding energy of the three replicates. The occupancy of contacting residue pairs were calculated and only those contacting residue pairs which were present in more than 50% of the albumin−peptide complexes in last 50 ns of the 100 ns MD trajectory are reported.



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Figure 1. Modular organization of HSA. Cartoon representation of the three dimensional structure of HSA (PDB ID: 1E78) with domains colored separately and labeled accordingly. Drug binding site in subdomain IIA is also referred to as Sudlow’s Site I and in subdomain IIIA is referred to as Sudlow’s Site II.


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Figure 2. Protocol for the identification of ATSP-7041 binding sites on HSA.

Figure 3. Occupancy map of ATSP-7041 on HSA from MD simulations in the identified potential binding sites namely R1, R2, R3 and R4 (see text).



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Figure 4. ATSP-7041 binding site R1 overlaps with Sudlow’s Site II. (a) Pre-formed hydrophobic cavity (yellow) where the entrance is lined by polar residues (cyan). (b) Left panel shows the Diazepam:HSA complex crystal structure where Diazepam is shown as spheres bound in Sudlow’s Site II (surface representation). Right panel shows ATSP-7041 (cartoon representation) bound in the R1 cavity shown with surface representation; this cavity overlaps with Sudlow’s Site II.


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Figure 5. Binding mode of ATSP-7041 in HSA at R1. Stapled-peptide binding interface of R1 shown with surface representation, peptide in cartoon representation and residue side-chains and staple in stick representation. The hydrogen bond/salt-bridge interactions are shown with dashed lines. Green and blue colors are used to indicate interactions between staple and W23 with HSA residues, respectively. Details of contacting residue pairs are given in Table 2. The contacts have been calculated taking the MD simulated trajectory showing the best binding energy of the three replicates.



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Figure 6. Plasticity of R1. (a) ATSP-7041 binding interface (R1) in HSA comprising of preformed hydrophobic cavity (yellow) where the entrance is lined by polar residues (cyan) shown in the presence (left panel) and absence of peptide (right panel). The residues responsible for modulating the size of the cavity are labeled and the dashed line represents the distance measured between them. (b) Bar graph showing the distance between the residues highlighted


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both in the presence and absence of the peptide. The distances have been calculated taking the MD simulated trajectory showing the best binding energy of the three replicates.

Figure 7. The R4 binding interface in HSA and its plasticity. (a) R4 binding interface composed of hydrophobic (yellow) and polar (cyan) residues. (b) Binding mode of ATSP-7041 in R4. Stapled-peptide binding interface of R4 shown with surface representation, peptide in cartoon and staple chain in stick representation. The hydrogen bond interaction is shown with dashed line. Green, blue and maroon colors are used to indicate interactions between staple, W23 and F19 peptide residues with HSA residues, respectively. Details about contacting residue pairs are given in Table 4. The contacts have been calculated taking the MD simulated trajectory showing the best binding energy of the three replicates.



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Figure 8. Comparison of peptide occupancy map on R1 and R4 between HSA and MSA. The map is shown for ATSP-7041 in simulations of ATSP-7041:albumin complex (top panel) representing peptide in R1 in case of HSA and MSA. Albumin is shown with cartoon representation in grey (human) and orange color (mouse). The bottom panel shows the comparative peptide occupancy map of R4 between HSA and MSA.


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Figure 9. Comparison of R1 binding interface of stapled-peptide between HSA and MSA. (a) The binding interface is colored according to the difference in the residue-wise contribution of contacting residues of human and mouse (column 4 of Table S2). (b) Left panel shows the contribution of residues in human and right panel shows for mouse. Albumin is shown in surface and peptide is shown with cartoon representation. The contributing residues with a difference between human and mouse is >= |0.6| are depicted in stick representation. The surface is colored according to their residue-wise contribution calculated using MM/GBSA and the gradient palette is shown in the inset. The calculations have been done taking the MD simulated trajectory showing the best binding energy of the three replicates.



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Figure 10. Comparison of R4 binding interface of stapled-peptide between HSA and MSA. (a) The binding interface is colored according to the difference in the residue-wise contribution of contacting residues of human and mouse (column 4 of Table S4). (b) Left panel shows the contribution of residues in human and right panel shows for mouse. Albumin is shown in surface and peptide is shown with cartoon representation. The contributing residues with a difference between human and mouse is >= |0.6| are depicted in stick representation. The surface is colored according to their residue-wise contribution calculated using MM/GBSA and the gradient palette is shown in the inset. The calculations have been done taking the MD simulated trajectory showing the best binding energy of the three replicates.


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Figure 11. Comparison of the contribution of stapled-peptide residues in ATSP-7041:MDM2, ATSP-7041:MDMX and ATSP-7041:HSA (both R1 and R4) complexes. Protein is shown in surface and peptide is shown with cartoon representation. The three critical contributing residues (F19, W23 and Cba26) and hydrocarbon staple chain are depicted in stick representation. The cartoon is colored according to their residue-wise contribution calculated using MM/GBSA and the gradient palette is shown in the inset. The calculations have been done taking the MD simulated trajectory showing the best binding energy of the three replicates.



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HSA ATSP-7041 (R1) HSA (1E7G) MYR (1E7G)

Figure 12: Superimposition of modeled ATSP-7041: HSA complex with myristic acid bound structure (PDB ID: 1E7G) highlighting the partial overlap of the fatty acid binding with the stapled peptide at site R1.


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TOC GRAPHIC


Toward Understanding the Molecular Recognition of Albumin by p53

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