Molecular Dynamics Simulation Study on the Binding and Stabilization

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Molecular dynamics simulations study on the binding and stabilization mechanism of antiprion compounds to the “hot spot” region of PrPC Shuangyan Zhou, Xuewei Liu, Xiaoli An, Xiao-Jun Yao, and Huanxiang Liu ACS Chem. Neurosci., Just Accepted Manuscript • DOI: 10.1021/acschemneuro.7b00214 • Publication Date (Web): 10 Aug 2017 Downloaded from http://pubs.acs.org on August 12, 2017

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ACS Chemical Neuroscience

Molecular dynamics simulation study on the binding and stabilization mechanism of antiprion compounds to the “hot spot” region of PrPC Shuangyan Zhou,a Xuewei Liu,b Xiaoli An,b Xiaojun Yao,bc Huanxiang Liu*a a

School of Pharmacy, Lanzhou University, Lanzhou 730000, China

b

State Key Laboratory of Applied Organic Chemistry and Department of Chemistry, Lanzhou

University, Lanzhou 730000, China c

State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied

Research in Medicine and Health, Macau University of Science and Technology, Taipa, Macau, China

* Corresponding author Tel.: +86-931-891-2578 Fax: +86-931-891-2582 E-mail address: [email protected]

1

ACS Paragon Plus Environment


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Abstract Structural transitions in the prion protein from the cellular form, PrPC, into the pathological isoform, PrPSc, are regarded as the main cause of the transmissible spongiform encephalopathies, also known as prion diseases. Hence, discovering and designing effective antiprion drugs that can inhibit PrPC to PrPSc conversion is regarded as a promising way to cure prion disease. Among several strategies to inhibit PrPC to PrPSc conversion, to stabilize the native PrPC via specific binding is believed to be one of the valuable approach and many antiprion compounds have been reported based on this strategy. However, the detailed mechanism to stabilize the native PrPC is still unknown. As such, to unravel the stabilizing mechanism of these compounds to PrPC is valuable for the further design and discovery of antiprion compounds. In this study, by molecular dynamics simulation method, we investigated the stablizing mechanism of several antiprion compounds on PrPC that were previously reported to specific binding to the “hot spot” region of PrPC. Our simulation results reveal that the stabilization mechanism of specific binding compounds can be summarized as: I. to stabilize both the flexible C-terminal of α2 and the hydrophobic core, such as BMD42-29 and GN8; II. to stabilize the hydrophobic core, such as J1 and GJP49; III. to stabilize the overall structure of PrPC by high binding affinity, as NPR-056. In addition, as indicated by the H-bond analysis and decomposition analysis of binding free energy, the residues N159 and Q160 play an important role in the specific binding of the studied compounds and all these compounds interact with PrPC in similar way with the key interacting residues L130 in β1 strand, P158, N159, Q160 etc in α1-β2 2


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loop and H187, T190, T191 etc in α2 C-terminus although the compounds have large structural difference. As a whole, our obtained results can provide some insights into the specific binding mechanism of main antiprion compounds to the “hot spot” region of PrPC at the molecular level and also provide guidance to the effective antiprion drug design in the future.

Key words: prion disease, antiprion compound, specific binding, molecular dynamics simulation.

Introduction The misfolding and aggregation of prion protein cause numbers of prion diseases in humans and animals, including Creutzfeldt-Jakob disease, kuru, bovine spongiform encephalopathy, scrapie, etc. Presently, three initiation modes of prion disease pathology were largely reported, known as: sporadic, hereditary, and acquired.1 All these disease modes are known to share the same pathogenic mechanism with the conformational conversion from the native form PrPC to the pathogenic form PrPSc.2 Consequently, preventing the conversion from PrPC to PrPSc may provide a promising way to cure prion disease. And to date, extensive efforts have focused on the drug discovery aiming at the conformational conversion process from PrPC to PrPSc and quite a number of compounds have been reported to reduce the PrPSc formation.3-8 To inhibit the PrPSc formation, five potential strategies for antiprion drug discovery were proposed as follows: I. to block the PrPC synthesis, II. to stabilize the 3



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native conformation of PrPC, III. to enhance the PrPSc clearance, IV. to interfere with the binding of PrPC to PrPSc, and V. to prevent binding of protein X to PrPC.9, 10 Among these strategies, stabilizing the native conformation of PrPC is believe to be one promising approach, as this strategy can maintain the normal functions of PrPC in reducing the rate of conversion to PrPSc at the same time. Moreover, the detailed mechanism of conformational conversion from PrPC to PrPSc is still unclear, thus PrPC could be a more appropriate molecular target for drug discovery of prion disease.2, 8 Based on this theory, many antiprion compounds were reported to specific binding or nonspecific binding to PrPC, acting as “medical chaperones”, to stabilize the native structure.8, 11-14 These compounds include quinacrine, benzoxazole compound, GJP derivatives, and others,11, 13, 15-17 and some of them are reported to bind specially to a region referred as “hot spot” region of PrPC. The “hot spot” region was firstly defined by Kuwata et al.8 One compound, termed GN8, specifically binding to this region was found to strongly stabilize native conformation of PrPC and efficiently reduce PrPSc. The specific binding site of the “hot spot” region, specified as N159, V189, T192, K194, and E196, was proposed to play a key role in preventing the pathogenic conversion process of prion protein. They believe that drug discovery focusing on this region of PrPC will open a way to develop new antiprion drugs in the future. For instance, based on the pharmacophore model of PrPC-GN8 complex structure, Hyeon et al discovered two compounds that exhibited obvious PrPSc inhibition, especially for the molecule termed BMD42-29, which was reported to show strong binding affinity and specifically stabilize the PrPC.13 Since to 4


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stabilize the native structure is a promising way for antiprion drug design as we declared above, to uncover the specific binding mechanisms of antiprion compounds to the “hot spot” pocket may provide a valuable clue to the discovery of antiprion drug. However, how do these small molecules interact with prion and then make PrPC more stable and prevent PrPC misfolding? It is still unclear for most of molecules. To discover the interaction mechanism between PrPC and small molecules, the crystallization method is very useful. However, it is difficult to obtain every complex. Even though we can obtain the crystal of the complex formed by PrP and small molecules, it just provides the static information. From only the static structural information, we can’t deduce the mechanism to stabilize the PrPC. Compared to the conventional experiment method, molecular dynamics (MD) simulation can provide more detailed and dynamic interaction information between protein and small molecules. Additionally, it is also very convenient to find the key residues of proteins to interact with small compounds by combining the molecular dynamics simulation and binding free energy analysis.18, 19 Moreover, the induced structural change of protein by small molecules can be also observed easily by checking the MD simulation trajectory. Based on these reasons, molecular dynamics simulations have been widely and successfully used to study the inhibition mechanism of small molecule inhibitors to targets especially related to protein misfolding and aggregation.4, 20-23 In this work, to study the specific binding mechanism of antiprion molecules to 5



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the “hot spot” region and uncover their potential stabilization mechanism on the native PrPC structure, molecular dynamic (MD) simulations were applied. Several compounds which have been previously reported to bind specifically to the “hot spot” region and stabilize the native structure of PrPC effectively were studied,11, 13, 16, 17 including the widely studied compound GN8.8, 24, 25 We also expect to find some common interaction models as well as key interaction elements among different antiprion compounds, which may provide guidance for further drug design or the structural modification of present inhibitors. The structures of these antiprion compounds were shown in Figure 1. The mouse PrPC protein (PDB entry: 1AG2) was employed as target protein as it is the most frequently used PrPC model for antiprion drug screening. Besides, for most compounds in this work, the crystal structure 1AG2 were also ever used as binding target in experimental research, except NPR-056. For NPR-056, to keep the same conditions with the previous study, the human prion protein (PDB entry: 2LSB) was used. All the initial structures of PrP-complexes were displayed in Figure 2, and the residues used for docking in the “hot spot” region were labeled in green as shown in Figure 2 in the Apo structure. The obtained results in our work may reveal the potential specific stabilization mechanism of antiprion molecules on the native PrPC and provide valuable guidance for the future antiprion drug design.

Results and discussion The overall structural properties of PrPC To monitor the equilibration of studied systems, the RMSDs of backbone atoms 6


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for the globular domain of PrPC were calculated for all systems. As can be seen from Figure 3a, the RMSDs of Apo protein experiences the largest fluctuation and all complex systems keep relatively stable in the last 100 ns. Hence, the binding of all antiprion compounds can indeed stabilize the overall conformation at a certain degree. Furthermore, to characterize the influence of the binding molecules on the compactness of native prion protein, the radius of gyration (Rg) of each system was calculated and the results were shown in Figure 3b. From Figure 3b, the fluctuations of all complex systems are quite small, which mean that the global protein structures in complex systems are well preserved during simulations. In comparison, for the Apo protein, there is a significant fluctuation and Rg values in the last 80 ns are obviously larger than all the complex systems. Therefore, our simulations reveal that the existence of antiprion compounds can make the native structure of prion more compact. To further study the overall stability of PrPC, the root-mean-square fluctuations (RMSF) of Cα atoms from the initial structures were measured to evaluate the flexibility of protein structure. As shown in Figure 3c, the tendency of RMSFs for all systems is quite similar. That is, the residues in the three loops (loop β1-α1, loop β2-α2, and loop α2-α3) and the C-terminal of α2 have quite large RMSFs, indicating that these regions are very flexible. This fluctuation tendency is also in accordance with our previously MD study.26 Interestingly, we find that in some complex systems, including BMD42-29, GN8, and J1, all the specific binding site residues (N159, V189, T192, K194, and E196) reported by Kuwata et al8 have smaller RMSFs than that in 7



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Apo protein, meaning that the binding of these compounds can reduce the flexibility of these residues. Similarly, in NPR-056 and GJP49, most of residues at binding site have smaller RMSFs than that in Apo protein, except for residues K194 and E196. But in comparison to the Apo system, both NPR-056 and GJP49 indeed reduced the overall flexibility of residues from loop β2-α2 to the α3 C-terminus. The result indicates that the specific binging can reduce the flexibility of the “hot spot” region but the reduced degrees of different compounds are different.

The local structural characteristics of PrPC The analysis of overall structure of PrPC indicates the binding of all the studied small molecules can increase the structural stability of PrPC. But how do the binding of inhibitors increase the stability of PrPC? To answer this question, we further examined the local structure properties of PrPC. The recent study proposed that α1 in the structured C-terminal domain (CTD, residues 121 to 231) of PrPC appears to act as a gate-keeper sub-domain controlling conformational conversion.27 That is, the unraveling of α1 is the rate-limiting step in conformational change, during which the α1 may act as a gate-keeper sub-domain by preventing hydrophobic surface of α2-α3 subdomain from becoming hydrated.27-29 Moreover, previous studies have reported that many pathologic mutations also lead to the α1 moving away from the α2-α3 plane.30-32 Hence, in this work, we assessed the movements of α1 along different directions by measuring the moving vectors of the α1 N-terminus (residues 144 to 147) with respect to the initial position as described before.32 The obtained results in Figure 8


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4 show that compared to the systems with inhibitor, the largest movements along the X direction (outward movements) and the Z direction (moving toward the center of protein) of α1 were observed in Apo system as expected, meaning that the largest tendency of moving away from α2-α3 plane. Therefore, it is possible to infer that antiprion compounds in this study can truly stabilize α1 by reducing the outward movements. As mentioned above, α1 may act as a gate-keeper to prevent hydrophobic surface of α2-α3 subdomain from becoming hydrated. Thus here, the distributions of solvent accessible surface area (SASA) of the hydrophobic core, consisting of residues 134, 137, 139, 141, 158, 161, 175, 176, 179, 180, 184, 198, 203, 205, 206, 209, 210, and 213–215,33 were further measured. During the calculation, only the last 100 ns of trajectories were considered and the obtained result was shown in Figure 5. As can be seen, relative to the Apo system, the SASA distributions of all the complex systems shift toward smaller values, despite that only slight move was found in NPR-056 system. And among these compounds, J1 and GJP49 have the smallest peak values, followed by BMD42-29 and GN8. This result also agrees well with the tendency of the outward movements of α1. Thus, all the binding molecules can stabilize the hydrophobic core of PrPC, and stabilization effects of J1 and GJP49 are most obvious. As a whole, from the decreased SASA values in hydrophobic core, we believe that the outward shift of α1 will indeed result in the hydration of hydrophobic surface and the specific binding of antiprion inhibitor will surely stabilize the hydrophobic core. Except for the influence on the shift of α1 and the stabilization of hydrophobic 9



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core, the specific binding of small molecules may also directly influence the behavior of the key salt-bridges Arg156-Glu196 and Arg156-Asp202, which play an important role in connecting α1 and the plane of α2-α3, and maintain the stability of the native prion structure as well.34, 35 From our simulation trajectories, three relative statuses of salt-bridges were found in residues Arg156, Glu196, and Asp202. The representative structures were shown in Figure 6a and the calculated results of salt-bridge calculations were shown in Figure 6b. As can be seen from Figure 6b, it is clear that except for GJP49, salt-bridge Arg156-Glu196 in all other complex systems is more stable than the Apo protein, meaning that these antiprion compounds can keep good link between the C-terminal of α1 and the α2-α3 loop. Relatively, the salt-bridge Arg156-Asp202 in all complex systems remains quite stable than the Apo system, which ensures the stable link with α3. Both salt-bridges in BMD42-29 and GN8 are extremely stable, indicating the most evident stabilization role of these two molecules to these two key salt-bridges. Accordingly, we deduced that the specific binding of antiprion compounds can anchor the platform of α1 with α2-α3 by stabilizing the key salt-bridges Arg156-Glu196 and Arg156-Asp202 and increase the structural rigid of flexible α2 C-terminus as a result. Although the stabilization effect of GJP49 to salt bridge Arg156-Glu196 isn’t evident, it indeed stabilizes the hydrophobic core of prion protein and decrease the outward movement of the N-terminal of α1. Moreover, according to earlier studies, the C-terminal of α2, especially the sequence stretch TVTTTT, has a high tendency to form β-sheet36 and the stabilization of the C-terminal of α2 can completely abolish PrP misfolding and 10


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oligomerization at low pH.37 Therefore, to further characterize the effect of these antiprion compounds, the secondary structure analysis of the α2 C-terminus with sequence TVTTTT was performed and the obtained result was shown in Figure 7. As shown in Figure 7a, it is obvious that the total helix structure contents, including α-helix and 3-10 helix, in the complexes of PrPC with BMD42-29 (86.91%) and GN8 (86.19%) are larger than that in Apo system (80.69%). Besides, compared to that in the Apo protein, turn structure in the complexes of PrPC with BMD42-29 and GN8 is 11.81% and 12.49%, respectively, which is obviously lower than that in the Apo with 17.85%, indicating that helix structure of α2 C-terminus in the Apo system is easier to convert into disordered turn structure than that in the complexes of PrPC of BMD42-29 and GN8. In comparison, the helix contents in the complexes of PrPC with J1, NPR-056 and GJP49 are 80.30%, 80.17% and 71.22%, respectively, which is similar or lower to that in the apo system. Consequently, it is obviously that BMD42-29 and GN8 can stabilize the C-terminal of α2 effectively, which further verify the above result of the increased rigid of this region. By contrast, the effect of other compounds on this region isn’t well as BMD42-29 and GN8. To gain the detailed structural change of each residue in sequence TVTTTT, the contents of the main secondary structure of each residue were further measured as shown in Figure 7b, 7c, and 7d. As can be seen, in all systems, helix structure of T188 and V189 are well preserved, and turn structure are mainly formed in residues T190, T191, T192 and T193, proving that the instability of the α2 C-terminus is highly correlated with the residues T190, T191, T192 and T193 with their helix structure 11



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transformed into the disordered structure easily. Besides, from Figure 7b, it is clear that helix structure contents of all residues in BMD42-29 and GN8 are apparently higher than that in the Apo system, indicating that helix structure of residues in the C-terminal of α2 is well maintained by specific binding to these two compounds. While helix structure contents of residues in the C-terminal of α2 in J1, NPR-056, and GJP49 systems are similar or even lower than that of in the Apo protein. Moreover, the tendency of turn structure formation of corresponding residues in J1, NPR-056 and GJP49 system is relative high, which mean the low stabilization of these compounds in the C-terminal of α2. We thus deduce that both BMD42-29 and GJP48 can specifically stabilize the C-terminal of α2, but the stabilization effect of other three antiprion compounds on this region is not evident.

The mechanism of antiprion compounds to stabilize PrPC The above analysis reveal that the specific binding of antiprion molecules in this study can stabilize the overall structure or the local structure of PrPC more or less, and the potential stabilization mechanism of different molecules may display a little difference. As indicate above, the binding of BMD42-29 and GN8, can stabilize the hydrophobic core of PrPC on one hand. On the other hand, they can stabilize α2 C-terminus by stabilizing the key salt-bridges Arg156-Glu196 and Arg156-Asp202 and keeping well the helix structure of it. In comparison, J1 and GJP49 can greatly stabilize the hydrophobic core of the native PrPC. Thus here, to further explore the mechanism of these compounds with different type effects on PrPC, the detailed 12


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interactions between several inhibitors and native PrPC were analyzed. Firstly, since hydrogen bonds (H-bonds) contribute a lot to the specific binding between PrPC and antiprion molecule,8, 13 thus to evaluate the binding of protein and antiprion compounds, H-bond occupancy between them was firstly calculated. The last 100 ns trajectories were used and the obtained results were shown in Figure 8a. Here, only the H-bonds with occupancy larger than 5% were displayed. It is obviously that for most antiprion compounds, H-bonds between small molecules and residues N159 and Q160 have high occupancies, which mean the important role of these two residues in the specific binding of antiprion molecule. In addition, as we described above that the specific binding of BMD42-29 and GN8 can stabilize the C-terminal of α2, H-bonds between these two molecules and the residues in the C-terminal of α2 are observed, including H-bond formed between BMD42-29 and residue H187 (19.50%) and H-bonds formed between GN8 and residues K194 (7.91%) and E196 (8.24%). However, no H-bond is found to be formed between other antiprion compounds and the residues in the α2 C-terminus, which explain the above result well that the stabilization effect on the C-terminal of α2 of J1, GJP49 and NPR-056 is not evident as BMD42-29 and GN8. As for J1 and GJP49, which were found to stabilize the hydrophobic core of PrPC, only two H-bonds involving residues N159 and Q160 were observed to be formed between J1 and PrPC, and no stable H-bond was found in GJP49 during the last 100 ns MD simulation. Thus, we speculate that H-bond may not the main contributor to stabilize the hydrophobic core for two molecules. In case of NPR-056, five H-bonds were found to be formed, indicating the good binding of 13



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NPR-056 to the pocket of PrPC. To further characterize the binding property of antiprion compounds, the clustering analysis was performed by the self-organizing maps (SOM) algorithm with the last 100 ns trajectories. The extracted representative structures of each complex system were shown in Figure 8b, 8c, 8d, 8e, 8f, for BMD42-29, GN8, J1, NPR-056, and GJP49, respectively. It is clear that in all complexes, the salt-bridges Arg156-Glu196 and Arg156-Asp202 are observed. This result fits well with the above analysis that the specific binding of antiprion compound can stabilize the key salt-bridges Arg156-Glu196 and Arg156-Asp202 more or less, which play an important role in linking the C-terminal of α1 and the plane of α2-α3. From the representative structure of PrPC-BMD42-29 complex (Figure 8b), four H-bonds are found and three residues are involved, including N159, Q160, and H187 (H187 locating at the C-terminal of α2), which is in good accordance with the above H-bond occupancy analysis. In addition, H-bonds formed between GN8 and the residue N159, and the residue E196 (locate in the α2-α3 loop) were observed (Figure 8c), which agrees very well with the binding sites (N159 and E196) of PrPC-GN8 complex reported before.8, 25 As such, we speculate that the interaction of BMD42-29 and GN8 with the C-terminal of α2 of PrPC can enhance the stabilization of the C-terminal of α2. And this kind of stabilization mainly reflects in two aspects: stabilizing salt-bridges Arg156-Glu196 and Arg156-Asp202 (increase the rigid of α2 C-terminus) and stabilizing the helix structure of α2 C-terminus. For J1 and GJP49, which mainly stabilize the hydrophobic core of PrPC, the interactions between them and the 14


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C-terminal of α2 of PrPC are weak since there is no direct contact between these two molecules and the C-terminal of α2 of PrPC (Figure 8d and 8f). As for the PrPC-NPR-056, three H-bonds were observed (Figure 8e), involving residues N159 and Q160, in accordance with the result of H-bond occupancy analysis. Combing with the above obtained results for NPR-056, the stabilization effect to the C-terminal of α2 and to the hydrophobic core is not evident as the others, but it indeed binds well within the pocket by forming several stable H-bonds. We thus speculate that the specific binding of NPR-056 may have other stabilization mechanism as Ishibashi et al reported that the interaction mechanism of NPR-056 is different with GN8.17 Further, to check the binding ability of these antiprion compounds, the binding free energies of the PrPC-complex were then calculated with the MM-GBSA method.38-45 Only the last 100 ns trajectories were considered. The obtained results were listed in Table 1. The results of ∆Gbind support that all the antiprion compounds in this work can bind with the “hot spot” region of PrPC and the ranking of binding free energies of PrPC-complex is -18.92 (NPR-056) < -13.11 (BMD42-29) < -7.89 (J1) < -5.73 (GN8) < -2.50 (GJP49) kcal/mol. It is obviously that NPR-056 has the largest binding affinity with the van der Waals contributed most (-45.57 kcal/mol), which is in good accordance with the conclusion that the van der Waals interactions play an important role in binding of NPR-056 to PrPC.17 What’s more, the electrostatic interactions (-35.33 kcal/mol) also contribute a lot to the total binding free energy. We therefore can conclude that the high binding affinity of NPR-056 may contribute a lot to the overall stability of native PrPC as indicated by the results of RMSD analysis and 15



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Rg calculation. Interestingly, although NPR-056 has the highest binding affinity, the stabilization effect on PrPC is not most evident. On the contrary, the above structure analysis indicate that BMD42-29 and GN8 can stabilize both the hydrophobic core and the flexible α2 C-terminus, but their binding affinity is not the highest. This can be explained by the viewpoint that only a moderate correlation may exist between binding affinities and antiprion activities.11 That is, the binding affinity can be treated as an indicator for inhibition activity but it is not absolutely proportional to the antiprion activity of antiprion compounds. Identifying the key residues is very important for the future drug design and discovery. Thus, to identify the key residues of PrPC for the specific binding of antiprion molecule, the decomposition analysis of binding free energy was then calculated, the obtained results were shown in Figure 9 and the residues with large contributions (> 1 kcal/mol) were labeled in the diagram. It is obviously that the residues with large contribution to the binding of small molecules mainly locate in three regions. The first part is residue L130 located in the β1 strand. The second region is α1-β2 loop, including residues P158, N159, Q160 etc. The third region is the C-terminal of α2, including residues H187, T190, T191 etc. All these key residues were located near around the “hot spot” region of PrPC. Besides, according to the above RMSF results, the flexibility of these key residues also decreased compared that in the Apo system. We also find that only two key residues (Q186, H187) located at the α2 C-terminus for the binding of J1 and just one key residue (Q186) for GJP49 binding, further proving the weak interaction of these two molecules with the 16


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C-terminal of α2 and their weak stabilization effect on this region. From the result of decomposition analysis of binding free energy, we can conclude that the overall interactions between these antiprion inhibitors and PrPC have some similar features despite of the structural difference of antiprion compounds. That is, the binding of these antiprion compounds can anchor the β1 strand, the α1-β2 loop and the C-terminal of α2 by interacting with key residues and reduce the structural flexibility of PrPC as a result. To identify the key pharmacological feature and provide more direct guidance for drug design, the pharmacophore analysis was performed by using Discovery Studio 2.0.46 For BMD42-29, GN8 and for J1, GJP49, the common feature-based pharmacophore model was built. The structures of compounds used for pharmacophore analysis were extracted from the corresponding representative complexes shown in Figure 8. As for NPR-056 with different stabilization mechanism to other compounds, the receptor-ligand interaction-based pharmacophore model was built based on the complex of NPR-056 with PrPC (which structure was shown in Figure 8e). The obtained results were shown in Figure 10. As depicted in Figure 10a, three common features were identified for compounds BMD42-29 and GN8, including two hydrophobic centers (cyan) and one hydrogen bond acceptor feature (green). On one hand, one hydrogen bond acceptor interacts with “hot spot” residue N159. On the other hand, two hydrophobic elements at lower right in Figure 10a can stabilize the hydrophobic core through the hydrophobic interaction, since the “hot spot” binding pocket almost locate at the surface of hydrophobic core. In addition, 17



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although both BMD42-29 and GN8 can form H-bond with residue in the α2 C-terminus, no common H-bond element (H-bond acceptor or H-bond donor) is found within this region. In details, BMD42-29 forms H-bond with residue H187 while GN8 forms H-bond with E196. Overall, the stabilization of BMD42-29 and GN8 on both hydrophobic core and flexible α2 C-terminus can attribute to the efficient hydrophobic interaction on the binding pocket and H-bond interaction on both the pocket (with residue N159) and the α2 C-terminus (with H187 in BMD42-29 and E196 in GN8). As for J1 and GJP49, the most prominent features are four common hydrophobic elements, which can explain well their excellent stabilization on the hydrophobic core of PrPC. In comparison, one H-bond acceptor and one H-bond donor involving the residues N159 and Q160 are found from the pharmacophore model of NPR-056, which was obtained based on the binding mode of NPR-056 with PrPC (see Figure 10c). Only one hydrophobic element is observed around the binding pocket, which may explain the less stabilization of this compound on hydrophobic core than others. These findings will be valuable to modify NPR-056 by introducing some hydrophobic feature and removing some useless moieties.

Conclusion In this work, we employed the molecular dynamics simulations to investigate the molecular mechanism of several reported antiprion compounds binding to the “hot spot” region to stabilize the native PrPC. By examining the overall conformational change of the native PrPC, we find that all the binding antiprion molecules can indeed 18


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stabilize the ensemble structure of native PrPC. The local structural characteristic analysis of PrPC indicates that the stabilization effects of different antiprion compounds have some differences and can be classified into three cases. The first one is to both stabilize the hydrophobic core and the flexible α2 C-terminus by hydrophobic interaction and forming stable H-bonds with residues (H187 with BMD42-29 and K194, E196 with GN8) in the α2 C-terminus as BMD42-29 and GN8. Besides, the stabilization effects of these two antiprion compounds on the C-terminal of α2 mainly reflect in two aspects, including stabilizing the key salt-bridges Arg156-Glu196 and Arg156-Asp202, which link the C-terminal of α1 with α2-α3 plane and increase the structural rigid of α2 C-terminus, and stabilizing the helix structure as results. The second is to stabilize the hydrophobic core of PrPC by preventing the outward movements of the N-terminal of α1 and thus preventing the hydrophobic core from becoming hydrated as we declared above. Our results reveal that J1 and GJP49 have the most obvious effect on stabilizing the hydrophobic core and hydrophobic interaction play an important role. The third is to stabilize the overall native PrPC with high binding affinity as NPR-056, through van der Waals and electrostatic interactions despite the stabilization on local structure of PrPC is not obvious as others. In addition, although three mechanisms were classified, there are also some common features. As revealed by the H-bond analysis and decomposition analysis of binding free energy, residues N159 and Q160 play an important role in the specific binding of antiprion compound into the “hot spot” region of PrPC. Besides, in all complex systems, all key residues locate near round the “hot spot” region, 19



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including β1 strand (L130), α1-β2 loop (P158, N159, Q160 et al) and C-terminal of α2 (H187, T190, T191 et al). Accordingly, our results reveal that although the structures of studied compounds are quite different, they have similar binding features. As a whole, in this work, the proposed binding mechanism of these antiprion compounds as well as the identified key pharmacophoric features of these antiprion compounds may provide valuable guidance for the design of effective antiprion drug in the future.

Materials and methods Preparation of the complexes of PrPC and antiprion compounds In this work, the initial complexes between PrPC and the studied small molecules were obtained by molecular docking performed in Schrödinger.47 The NMR structure of mouse PrPC (PDB entry: 1AG2) was chosen as target for the docking of these small molecules. The docking focused on the “hot spot” region as done by Kuwata et al.8 The binding site mainly includes 14 amino acid residues and they are M129, G131, N159, V161, Y162, D178, C179, T183, I184, L185, H187, T190, G195 and E196. All the defined binding site residues were displayed in Figure 2 with green color in Apo protein. For molecular docking, a flexible-ligand/rigid-receptor approach was used with extra precision (XP) based on Glide module in the software of Schrödinger. The obtained complex conformation which fit well with the reported binding model were then chosen as the initial simulation structures and the corresponding representative complex structures were shown in Figure 2. 20


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Details of the molecular dynamics simulation The structures of antiprion compounds were firstly optimized by the Gaussian 09 software48 at the Hartree-Fock level with the 6-31G* basis set, and the atomic partial charges were assigned by the restrained electrostatic potential (RESP) fitting technique.49 The general amber force field (GAFF)50 was then used to describe the compounds. The Amber ff99SB force field was adopted to describe the protein.51 All the molecular dynamics simulations were performed by the Amber 14 package.52 Each system was placed into a cubic periodic box with the box edges set at least 10 Å around solute. The TIP3P water model53 was used to imitate the solvent effect and Na+ was added as counterions to maintain the electroneutrality of systems. The prepared systems were then minimized to eliminate unnatural collision. Then, each system was heated from 0 to 310.0 K in the NVT ensemble with all the solute atoms constrained by 5.0 kcal/(mol·Å2) harmonic restraint force and after that six steps equilibration MD were carried out in the NPT ensemble with decreased restraint force applied to all solute atoms from 5.0 to 0 kcal/(mol·Å2) to release all the restraints. Subsequently, 200 ns MD simulations were performed in the NPT ensemble without any restraint at a temperature of 310 K and a pressure of 1 atm. During the simulations, the temperature of systems was regulated by the Langevin thermostat, SHAKE algorithm54 was employed to constrain hydrogen-involved bonds. The equations of motion were integrated with time step of 2 fs. The non-bonded cutoff distance was set to 10.0 Å, and Particle Mesh Ewald (PME) method was used to 21



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calculate long-range electrostatic interactions. Overall, six separate 200 ns simulations, including five runs for the complexes of PrPC with antiprion compounds and one for PrPC without antiprion molecule referred as Apo, were performed.

MD trajectory analysis To explore the mechanism of antiprion compounds to stabilize the native structure of PrPC, we analyzed the obtained MD trajectories from the structural and energy perspectives. All the trajectory analysis was performed in Amber52 and VMD55 programs. Firstly, the root-mean-square deviations (RMSDs) of backbone atoms relative to the initial structure were monitored for the globular domain (residue 128 to 225) of prion protein to evaluate the conformational fluctuation and the stability of MD trajectories as well. Solvent-accessible surface areas (SASAs) of the hydrophobic core of prion protein were calculated using the VMD55 to assess the stability of hydrophobic core of PrPC. Salt-bridge was considered to be formed if the distance between the center of mass of the nitrogen atoms in basic side chain and the center of mass of the oxygen atoms in the acidic side chain is within 4 Å as done by Guo et al.26 To evaluate the binding property of small molecules, the hydrogen bond occupancies between ligand and receptor were calculated and the hydrogen bond was considered to be formed if the hydrogen-acceptor distance was less than 3.5 Å and the donor-hydrogen-acceptor angle was large than 150°. The representative conformation of each system was extract by clustering analysis to intuitively monitor the interaction between antiprion molecules and PrPC, and the self-organizing maps (SOM) 22


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algorithm was used. Furthermore, the binding free energy between small compounds and native PrPC was calculated by the MM-GBSA method based on the snapshots extracted from the last 50 ns to evaluate their binding affinity. Lastly, the pharmacophore model was conducted by Discovery Studio 2.046 to extract key pharmacophoric feature elements responsible for their specific binding.

Binding free energy calculation The MM-GBSA method38-45 has been applied to estimate the binding affinity of antiprion compounds to PrPC. Herein, a total of 500 snapshots from the last 50 ns were extracted with a time interval of 100 ps. For each extracted snapshot, the free energy is estimated as follows:

∆Gbind = Gcomplex − (Greceptor+Gligand)

(1)

G = Egas + Gsol − TS

(2)

Egas = Evdw + Eele + E int

(3)

Gsol = Gsol_np + Gsol_polar

(4)

Gsol_np = γ ⋅ SASA

(5)

Where Gcomplex, Greceptor and Gligand are the free energy of complex of PrPC with antiprion compounds, PrPC and antiprion compounds, respectively. Egas represents for the gas-phase energy; Eint is the internal energy; Eele and Evdw are the electrostatic term and van der Waals energies, respectively. Gsol represents for the solvation free energy and can be resolved into the polar (Gsol_polar) and nonpolar contributions (Gsol_np). The polar contribution was calculated by solving the generalized Born equation.56 The 23



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solvent is described as a continuum medium with a fixed dielectric constant (i.e. 80 for water), and low internal dielectric constant is specified to the solute (i.e. 1 for proteins). The nonpolar solvation term Gsol_np is estimated from a linear relation to the solvent accessible surface area (SASA) determined by using a water probe radius of 1.4 Å and the surface tension constant γ of 0.0072 kcal/(mol⋅Å2).57

24


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References 1. Collinge, J. (2001) Prion diseases of humans and animals: their causes and molecular basis, Annu. Rev. Neurosci. 24, 519-550. 2. Cohen, F. E., Pan, K.-M., Huang, Z., Baldwin, M., Fletterick, R. J., and Prusiner, S. B. (1994) Structural clues to prion replication, Science 264, 530-531. 3. Dinkel, K. D., Stanton, J. B., Boykin, D. W., Stephens, C. E., Madsen-Bouterse, S. A., and Schneider, D. A. (2016) Antiprion Activity of DB772 and Related Monothiophene-and Furan-Based Analogs in a Persistently Infected Ovine Microglia Culture System, Annu. Rev. Neurosci. 60, 5467-5482. 4. Herrmann, U. S., Schütz, A. K., Shirani, H., Huang, D., Saban, D., Nuvolone, M., Li, B., Ballmer, B., Åslund, A. K., and Mason, J. J. (2015) Structure-based drug design identifies polythiophenes as antiprion compounds, Sci. Transl. Med. 7, 299ra123-299ra123. 5. Berry, D. B., Lu, D., Geva, M., Watts, J. C., Bhardwaj, S., Oehler, A., Renslo, A. R., DeArmond, S. J., Prusiner, S. B., and Giles, K. (2013) Drug resistance confounding prion therapeutics, Proc. Natl. Acad. Sci. U.S.A. 110, E4160-E4169. 6. Dollinger, S., Löber, S., Klingenstein, R., Korth, C., and Gmeiner, P. (2006) A chimeric ligand approach leading to potent antiprion active acridine derivatives: design, synthesis, and biological investigations, J. Med. Chem. 49, 6591-6595. 7. Bolognesi, M. L., Bongarzone, S., Aulic, S., Ai Tran, H. N., Prati, F., Carloni, P., 25



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

and Legname, G. (2015) Rational approach to an antiprion compound with a multiple mechanism of action, Future Med. Chem. 7, 2113-2120. 8. Kuwata, K., Nishida, N., Matsumoto, T., Kamatari, Y. O., Hosokawa-Muto, J., Kodama, K., Nakamura, H. K., Kimura, K., Kawasaki, M., and Takakura, Y. (2007) Hot spots in prion protein for pathogenic conversion, Proc. Natl. Acad. Sci. U.S.A. 104, 11921-11926. 9. Perrier, V., Wallace, A. C., Kaneko, K., Safar, J., Prusiner, S. B., and Cohen, F. E. (2000) Mimicking dominant negative inhibition of prion replication through structure-based drug design, Proc. Natl. Acad. Sci. U.S.A. 97, 6073-6078. 10. Koster, T., Singh, K., Zimmermann, M., and Gruys, E. (2003) Emerging therapeutic agents for transmissible spongiform encephalopathies: a review, J Vet. Pharmacol. Ther. 26, 315-326. 11. Hosokawa-Muto, J., Kamatari, Y. O., Nakamura, H. K., and Kuwata, K. (2009) Variety of antiprion compounds discovered through an in silico screen based on cellular-form prion protein structure: Correlation between antiprion activity and binding affinity, Antimicrob. Agents Ch. 53, 765-771. 12. Kamatari, Y. O., Hayano, Y., Yamaguchi, K. i., Hosokawa‐Muto, J., and Kuwata, K. (2013) Characterizing antiprion compounds based on their binding properties to prion proteins: implications as medical chaperones, Protein Sci. 22, 22-34. 13. Hyeon, J. W., Choi, J., Kim, S. Y., Govindaraj, R. G., Hwang, K. J., Lee, Y. S., An, S. S. A., Lee, M. K., Joung, J. Y., and No, K. T. (2015) Discovery of novel 26


Page 26 of 48

Page 27 of 48

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


anti-prion compounds using in silico and in vitro approaches, Sci. Rep. 5, 14944. 14. Pagadala, N. S., Perez-Pineiro, R., Wishart, D. S., and Tuszynski, J. A. (2015) In silico studies and fluorescence binding assays of potential anti-prion compounds reveal an important binding site for prion inhibition from PrP C to PrP Sc, Eur. J. Med. Chem. 91, 118-131. 15. Doh-Ura, K., Iwaki, T., and Caughey, B. (2000) Lysosomotropic agents and cysteine

protease

inhibitors

inhibit

scrapie-associated

prion

protein

accumulation, J. Virol. 74, 4894-4897. 16. Ferreira, N. C., Marques, I. A., Conceição, W. A., Macedo, B., Machado, C. S., Mascarello, A., Chiaradia-Delatorre, L. D., Yunes, R. A., Nunes, R. J., and Hughson, A. G. (2014) Anti-prion activity of a panel of aromatic chemical compounds: in vitro and in silico approaches, PloS one 9, e84531. 17. Ishibashi, D., Nakagaki, T., Ishikawa, T., Atarashi, R., Watanabe, K., Cruz, F., Hamada, T., and Nishida, N. (2016) Structure-based drug discovery for prion disease using a novel binding simulation, EBioMedicine 9, 238-249. 18. Musyoka, T. M., Kanzi, A. M., Lobb, K. A., and Bishop, Ö. T. (2016) Structure Based Docking and Molecular Dynamic Studies of Plasmodial Cysteine Proteases against a South African Natural Compound and its Analogs, Sci. Rep. 6,23690. 19. Kenneth Morrow, J., and Zhang, S. (2012) Computational prediction of protein hot spot residues, Curr. Pharm. Design 18, 1255-1265. 27



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

20. Wang, Q., Zhou, S., Wei, W., Yao, X., Liu, H., and Hu, Z. (2015) Computational insights into the inhibition and destabilization of morin on the oligomer of full-length human islet amyloid polypeptide, Phys. Chem. Chem. Phys. 17, 29103-29112. 21. Mo, Y., Lei, J., Sun, Y., Zhang, Q., and Wei, G. (2016) Conformational Ensemble of hIAPP Dimer: Insight into the Molecular Mechanism by which a Green Tea Extract inhibits hIAPP Aggregation, Sci. Rep. 6, 33076. 22. Zhang, T., Xu, W., Mu, Y., and Derreumaux, P. (2013) Atomic and Dynamic Insights into the Beneficial Effect of the 1, 4-Naphthoquinon-2-yl-l-tryptophan Inhibitor on Alzheimer’s Aβ1–42 Dimer in Terms of Aggregation and Toxicity, ACS Chem. Neurosci. 5, 148-159. 23. Jiang, P., Li, W., Shea, J.-E., and Mu, Y. (2011) Resveratrol inhibits the formation of multiple-layered β-sheet oligomers of the human islet amyloid polypeptide segment 22–27, Biophys. J. 100, 1550-1558. 24. Yamamoto, N., and Kuwata, K. (2009) Regulating the conformation of prion protein through ligand binding, J. Phys. Chem. B 113, 12853-12856. 25. Ishikawa, T., Ishikura, T., and Kuwata, K. (2009) Theoretical study of the prion protein based on the fragment molecular orbital method, J. Comput. Chem.30, 2594-2601. 26. Guo, J., Ren, H., Ning, L., Liu, H., and Yao, X. (2012) Exploring structural and thermodynamic stabilities of human prion protein pathogenic mutants D202N, E211Q and Q217R, J. Struct. Biol. 178, 225-232. 28


Page 28 of 48

Page 29 of 48

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


27. Sabareesan, A., and Udgaonkar, J. B. (2016) Pathogenic Mutations within the Disordered Palindromic Region of the Prion Protein Induce Structure Therein and Accelerate the Formation of Misfolded Oligomers, J. Mol. Biol. 428, 3935-3947. 28. De Simone, A., Zagari, A., and Derreumaux, P. (2007) Structural and hydration properties of the partially unfolded states of the prion protein, Biophys. J. 93, 1284-1292. 29. De Simone, A., Dodson, G. G., Verma, C. S., Zagari, A., and Fraternali, F. (2005) Prion and water: tight and dynamical hydration sites have a key role in structural stability, Proc. Natl. Acad. Sci. U.S.A.102, 7535-7540. 30. Guo, J., Ning, L., Ren, H., Liu, H., and Yao, X. (2012) Influence of the pathogenic mutations T188K/R/A on the structural stability and misfolding of human prion protein: Insight from molecular dynamics simulations, BBA-Gen. Subjects 1820, 116-123. 31. Chen, W., van der Kamp, M. W., and Daggett, V. (2010) Diverse effects on the native β-sheet of the human prion protein due to disease-associated mutations, Biochemistry 49, 9874-9881. 32. van der Kamp, M. W., and Daggett, V. (2010) Pathogenic mutations in the hydrophobic core of the human prion protein can promote structural instability and misfolding, J. Mol. Biol. 404, 732-748. 33. Riek, R., Wider, G., Billeter, M., Hornemann, S., Glockshuber, R., and Wüthrich, K. (1998) Prion protein NMR structure and familial human spongiform 29



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

encephalopathies, Proc. Natl. Acad. Sci. U.S.A. 95, 11667-11672. 34. Ning, L., Guo, J., Jin, N., Liu, H., and Yao, X. (2014) The role of Cys179–Cys214 disulfide bond in the stability and folding of prion protein: insights from molecular dynamics simulations, J. Mol. Model.20, 1-8. 35. Zhang, J. (2011) The structural stability of wild-type horse prion protein, J. Biomol. Struct. Dyn. 29, 369-377. 36. Dima, R., and Thirumalai, D. (2002) Exploring the propensities of helices in PrP C to form β sheet using NMR structures and sequence alignments, Biophys. J.83, 1268-1280. 37. Singh, J., Kumar, H., Sabareesan, A. T., and Udgaonkar, J. B. (2014) Rational stabilization of helix 2 of the prion protein prevents its misfolding and oligomerization, J. Am. Chem. Soc. 136, 16704-16707. 38. Hou, T., Wang, J., Li, Y., and Wang, W. (2011) Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations, J. Chem. Inf. Model 51, 69-82. 39. Hou, T., Wang, J., Li, Y., and Wang, W. (2011) Assessing the performance of the molecular mechanics/Poisson Boltzmann surface area and molecular mechanics/generalized Born surface area methods. II. The accuracy of ranking poses generated from docking, J. Comput. Chem. 32, 866-877. 40. Liu, H., and Yao, X. (2009) Molecular basis of the interaction for an essential subunit PA− PB1 in influenza virus RNA polymerase: insights from molecular 30


Page 30 of 48

Page 31 of 48

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


dynamics simulation and free energy calculation, Mol. Pharm. 7, 75-85. 41. Chen, F., Liu, H., Sun, H., Pan, P., Li, Y., Li, D., and Hou, T. (2016) Assessing the performance of the MM/PBSA and MM/GBSA methods. 6. Capability to predict protein–protein binding free energies and re-rank binding poses generated by protein–protein docking, Phys. Chem. Chem. Phys. 18, 22129-22139. 42. Sun, H., Li, Y., Shen, M., Tian, S., Xu, L., Pan, P., Guan, Y., and Hou, T. (2014) Assessing the performance of MM/PBSA and MM/GBSA methods. 5. Improved docking performance using high solute dielectric constant MM/GBSA and MM/PBSA rescoring, Phys. Chem. Chem. Phys. 16, 22035-22045. 43. Sun, H., Li, Y., Tian, S., Xu, L., and Hou, T. (2014) Assessing the performance of MM/PBSA and MM/GBSA methods. 4. Accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data set, Phys. Chem. Chem. Phys. 16, 16719-16729. 44. Xu, L., Zhang, Y., Zheng, L., Qiao, C., Li, Y., Li, D., Zhen, X., and Hou, T. (2014) Discovery of novel inhibitors targeting the macrophage migration inhibitory factor via structure-based virtual screening and bioassays, J. Med. Chem. 57, 3737-3745. 45. Xu, L., Sun, H., Li, Y., Wang, J., and Hou, T. (2013) Assessing the performance of MM/PBSA and MM/GBSA methods. 3. The impact of force fields and ligand charge models, J. Phys. Chem. B 117, 8408-8421. 31



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

46. Accelrys Discovery Stuido 3.0 (2010) Accelrys, San Diego, CA. 47. Schrödinger. (2009) Maestro, Version 9.0. Schrödinger LLC, New York NY. 48. Frisch, M. J., Trucks, G. W., Schlegel, H. B., Scuseria, G. E., Robb, M. A., Cheeseman, J. R., Scalmani, G., Barone, V., Mennucci, B., Petersson, G. A. et al. (2009) Gaussian 09, Gaussian, Inc.: Wallingford, CT. 49. Bayly, C. I., Cieplak, P., Cornell, W., and Kollman, P. A. (1992) A well-behaved electrostatic potential based method using charge restraints for deriving atomic charges: the RESP model, J. Phys. Chem. 97, 10269-10280. 50. Wang, J., Wolf, R. M., Caldwell, J. W., Kollman, P. A., and Case, D. A. (2004) Development and testing of a general amber force field, J Comput. Chem. 25, 1157-1174. 51. Hornak, V., Abel, R., Okur, A., Strockbine, B., Roitberg, A., and Simmerling, C. (2006) Comparison of multiple Amber force fields and development of improved protein backbone parameters, Proteins 65, 712-725. 52. Case, D. A., Babin, V., Berryman, J., et al. (2014) AMBER 2014, University of California, San Francisco 53. Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W., and Klein, M. L. (1983) Comparison of simple potential functions for simulating liquid water, J. Chem. Phys. 79, 926-935. 54. Ryckaert, J.-P., Ciccotti, G., and Berendsen, H. J. (1977) Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes, J. Comput. Phys. 23, 327-341. 32


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55. Humphrey, W., Dalke, A., and Schulten, K. (1996) VMD: visual molecular dynamics, J. Mol. Graph. 14, 33-38. 56. Srinivasan, J., Cheatham, T. E., Cieplak, P., Kollman, P. A., and Case, D. A. (1998) Continuum solvent studies of the stability of DNA, RNA, and phosphoramidate-DNA helices, J. Am. Chem. Soc. 120, 9401-9409. 57. Sitkoff, D., Sharp, K. A., and Honig, B. (1994) Accurate calculation of hydration free energies using macroscopic solvent models, J. Phys. Chem. 98, 1978-1988.

33



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Corresponding Author *Mailing address: School of Pharmacy, Lanzhou University, Lanzhou 730000, China. E-mail: [email protected]

Author Contributions H. L. and X. Y. conceived the project. H. L and S. Z designed the experiments. S. Z., X. L. and L. A. carried out the research and analysis of data. S. Z. and H. L. wrote the paper.

Funding This work is supported by the National Nature Science Foundation of China (Grant No. 21675070 and No. 21375054) and the Fundamental Research Funds for the Central Universities (Grant No. lzujbky-2016-146 and No. lzujbky-2017-k24).

Notes The authors declare no competing financial interest.

34


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Table 1. The binding free energies (kcal/mol) of PrPC and antiprion molecules obtained by MM-GBSA method. BMD42-29

GN8

J1

NPR-056

GJP49

△Eele

-29.79

-12.54

-14.48

-35.33

-5.78

△Evdw

-44.42

-39.33

-36.60

-45.57

-26.47

△Eint

0.00

0.00

0.00

0.00

0.00

△Egas

-74.21

-51.87

-51.08

-80.90

-32.25

△Gsol_np

-5.84

-5.32

-5.27

-6.36

-3.79

△Gsol_polar

41.17

26.14

25.73

43.88

15.92

△Gsol

35.34

20.82

20.46

37.52

12.13

△Gpolar

11.39

13.6

11.25

8.55

10.14

△Gnonpolar

-50.26

-44.65

-41.87

-51.93

-30.26

△H

-38.87

-31.05

-30.62

-43.38

-20.13

-T△S

25.76

25.32

22.73

24.46

17.63

△Gbind

-13.11

-5.73

-7.89

-18.92

-2.5

35



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Figure captions: Figure 1. Chemical structures of the studied antiprion compounds in this work. All of these compounds were reported to specifically bind to the “hot spot” region of prion protein. Figure 2. The initial binding model of the complex of PrPC and antiprion compounds, the “hot spot” residues were labeled in green in the native structure of PrPC. Figure 3. The overall structural characteristics of the native PrPC from the MD simulations. (a) The backbone RMSDs of protein relative to the initial structure of the globular domain (from residues 128 to 225). (b) The radius of gyration of protein as a function of simulation time. (c) The Cα RMSFs over the last 100 ns simulations as a function of residue number. Figure 4. Displacement of the N-terminal of α1. The moving vectors of the α1 N-terminus (Cα atoms from residues 144 to 147, colored in purple) relative to its starting position at the end of simulations were calculated in a defined coordinate system: the Cα of Cys214 in α3 is specified as the origin, the X axis goes through the Cα of Val176 in α2, and the Y axis goes through Cα of Met206 in α3. The three Cα atoms are display as yellow balls. Figure 5. The solvent-accessible surface areas (SASA) distributions of the hydrophobic core of prion protein from the last 100 ns. Figure 6. The monitoring of two key salt-bridges Arg156-Glu196 and Arg156-Asp202. (a) The relative position of three residues involving the formation of salt-bridge. (b) Time course of salt-bridge formation between Arg156 and Glu196, 36


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and between Arg156 and Asp202 of each system. Figure 7. The secondary structure analysis of the C-terminal of α2 with sequence TVTTTT. (a) The overall secondary structure analysis of sequence TVTTTT and the secondary structure content of each residue in sequence TVTTTT with (b) helix, (c) turn and (d) coil. Figure 8. The detailed interactions between PrPC and antiprion compounds. (a) Hydrogen bond occupancy between PrPC and antiprion molecules with occupancy larger than 5% listed. The representative complex structures binding with (b) BMD42-29, (c) GN8, (d) J1, (e) NPR-056 and (f) GJP49. The representative structures were extracted by the cluster analysis with the self-organizing maps (SOM) algorithm. Figure 9. The decomposition of binding free energy of each complex system. The residues with energy contribution larger than 1 kcal/mol are labeled. Figure 10. The obtained pharmacophore model of antiprion compounds. (a) The common

pharmacophore

features

of BMD42-29

and

GN8,

(b) common

pharmacophore features of J1 and GJP49. Structures of these compounds were extracted from their corresponding representative complex structures obtained by cluster analysis. (c) Obtained pharmacophore model of NPR-056 based on the binding mode of NPR-056 and PrPC. Green ball represents for H-bond acceptor, pink for H-bond donor and blue for hydrophobic center.

37



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Figure 1

38


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Figure 2

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Figure 3

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Figure 4

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Figure 5

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Figure 6

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Figure 7

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Figure 8

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Figure 9

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Figure 10

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For Table of Contents Use Only

Molecular dynamics simulations study on the binding and stabilization mechanism of antiprion compounds to the “hot spot” region of PrPC Shuangyan Zhou, Xuewei Liu, Xiaoli An, Xiaojun Yao, Huanxiang Liu*


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Molecular Dynamics Simulation Study on the Binding and Stabilization

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