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Electrostatics of Prokaryotic Ribosome and Its Biological Implication
Journal Pre-proof Electrostatics of Prokaryotic Ribosome and its Biological Implication Jun Wang, Chitra Karki, Yi Xiao, Lin Li PII:
S0006-3495(20)30047-3
DOI:
https://doi.org/10.1016/j.bpj.2020.01.014
Reference:
BPJ 10266
To appear in:
Biophysical Journal
Received Date: 15 August 2019 Accepted Date: 9 January 2020
Please cite this article as: Wang J, Karki C, Xiao Y, Li L, Electrostatics of Prokaryotic Ribosome and its Biological Implication, Biophysical Journal (2020), doi: https://doi.org/10.1016/j.bpj.2020.01.014. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Biophysical Society.
Electrostatics of Prokaryotic Ribosome and its Biological Implication Jun Wang1, Chitra Karki2, Yi Xiao1* and Lin Li2* 1
School of Physics, Huazhong University of Science and Technology, Wuhan 430074,
Hubei, China 2
Physic Department, University of Texas at El Paso, El Paso, TX, US. 79968
*Corresponding authors
Abstract Ribosomes are essential machines for protein synthesis in cells. Their structures are very complex but conserved in different species. Since most parts of a ribosome are composed of negatively charged RNAs, its electrostatics should play a fundamental role in the realization of its functions. However, a complete picture of the electrostatics of ribosomes is still absent at present. Here, assisted by the latest version of DelPhi (Version: 8.4), we illustrate a picture of the electrostatics of a prokaryotic ribosome as well as its molecular chaperones. The revealed electrostatics features are well consistent with available experimental data as well as the functions of the ribosome and its molecular chaperones and provides a basis for further studying the mechanism underlying these functions.
Statement of Significance Ribosomes are complex molecular machines that make proteins and also help protein folding. It has been known for a long time that electrostatics play important roles in these functions of ribosomes. However, a complete picture of the ribosome electrostatics is absent at present since traditional theoretical and experimental methods are difficult to treat such larger molecules. In this work, assisted by the latest
version of DelPhi updated by one of the coauthor and his colleague, we present a picture for a prokaryotic ribosome as well as its molecular chaperones. It provides a basis for understanding the mechanism underlying the functions of ribosomes.
Introduction It is well known that the ribosome is a molecular machine for protein synthesis in cells. During protein synthesis, not only two subunits of ribosome need to bind to each other, but also many auxiliary proteins and RNAs bind at appropriate stages of protein synthesis, e.g., translational initiation factors, tRNAs, and chaperons. However, the physical mechanism of these interactions is not well understood. On the other hand, it was shown recently that ribosomes might assist in the folding of nascent polypeptides recently(1). The protein folding problem has been studied for over 50 years, but the mechanism of the protein folding is still not well understood(2). For the folding of nascent polypeptides in cells is affected by the environment, including interactions with the ribosome, chaperon molecules (3). Therefore, to make clear the mechanism of both protein synthesis and folding, we need to take the role of ribosome and related proteins into consideration. The ribosome is composed of two subunits: large and small subunits. In the eukaryotic ribosome (80S), they are called 60S and 40S, respectively; while in the prokaryotic ribosome (70S) they are named as 50S and 30S, respectively. The structures of eukaryotic and prokaryotic ribosomes are similar, but their compositions are quite different, though they are all composed of proteins and RNAs. In the 70S ribosome, the 30S subunit is formed by 16S rRNA and about 21 ribosome proteins, and the 50S subunit is composed of 23S rRNA, 15S rRNA, 5S rRNA, and 34 ribosomal proteins. In the 80S ribosome, the 40S subunit includes 18S rRNA and 33 ribosome proteins, while the 60S subunit includes 25S rRNA (or 28S rRNA), 5S rRNA, and 49 ribosome proteins. Consequently, the eukaryotic ribosome is larger and more complex than the prokaryotic ribosome. In this work, we mainly focus on 70S ribosomes from bacteria. The ribosome is among the most complex molecular machines which differ in
composition and structure than any other ones: Firstly, ribosome consists of large RNAs and many proteins and thus contains a large number of atoms (about several million atoms); These RNAs and proteins are strongly coupled with each other. Secondly, the ribosome is not sufficiently rigid. Inside the large subunit, there is a “ribosomal exit tunnel” from which newly synthesized peptide chains emerge (4). This particular tunnel is not just a simple tube for nascent peptides to exit the ribosome. It also plays a significant role in the folding and elongation process of nascent peptides (5-10). It is known that RNA molecules are negatively charged, so electrostatics of the ribosome should play fundamental roles in its structure and dynamics, its interactions with other molecules, and its functions. Up to now, only a few studies of electrostatics features of the ribosome have been accomplished by experiments and computations (11-15). However, these studies mainly focused on one aspect of the electrostatics of the ribosome. For example, Baker et al. computed the electrostatic potential of the ribosome surface and their possible relations with the protein translation process(11). Lu et al. experimentally measured the electrostatic potentials along the ribosomal exit tunnel(14) and studied their effect on the translation rate(15). In this paper, we aim to give a complete picture of the electrostatics of a prokaryote ribosome as well as the bound proteins utilizing a recently updated version of DelPhi and discuss their possible relations with the functions of the ribosome.
Methods We searched the PDB for all ribosome structures and found the one with an intact structure, which has the highest resolution. The crystal structure we studied here comes from the thermophilic bacteria (PDB ID 4V5D(16), see Fig. 1), which includes the 30S and 50S subunits with a resolution of 3.5 Å. Moreover, on its 30S subunit, there are structures of an mRNA, A-site, P-site, E-site tRNAs, and some magnesium ions. Such a high resolution and intact structure provide an excellent opportunity for us to perform high accuracy simulations and therefore obtain reliable analyses. In order to calculate the electrostatic potential of this ribosome structure correctly,
we optimized the structure by AMBER14(17) to eliminate the stereo clash. Firstly, we removed the hydrogen atoms in the crystal structure but preserved all the magnesium ions to reproduce the “real” potential of the ribosome as possibly as we can. Then we used Antechamber module of AMBER14 to model several non-standard residues and calculated their partial charges with the AM1-BCC method(18,19). After that, topology and coordinates were generated using the LeaP program, and the force field we used for optimization was ff14SB(20) and gaff(21). In this process, we also added the magnesium to neutralize the ribosome and TIP3P(22)waters. The number of magnesium ions to be added is determined by the charge of the ribosome and crystallized ions, while the location of the added ions is determined by the lowest potential calculated by tLEaP in AMBER14. Finally, we got a box containing more than 1.7 million atoms. Then, we employed a two-stage minimization strategy: firstly, the energy minimization was performed with the ribosome atoms constrained; Then, we minimize the whole system, with the ribosomal atoms relaxed. In each stage, we ran 1000 steps using the steepest descent method and then 1000 steps using the conjugate gradient method. In the simulation process, the ribosome atoms were constrained by a large spring potential (100kcal/mol). After heating for 50ps and running the MD simulation for 150ps, we obtained the final optimized structure. We then calculated the electrostatic potential of the whole ribosome using the DelPhi program(23-25), which has high accuracy and computational speed that enabled us to calculate the electrostatics of the ribosome quickly and accurately. The nonlinear elliptic Poisson-Boltzmann equation (PBE) is given by ∇ ∙ ൫ߝሺݔሻ∇߶ሺxሻ൯ − ݇ሺݔሻଶ sinh൫߶ሺxሻ൯ = −4ߨߩሺݔሻ,
(1)
Where ϕ is the electrostatic potential, ε is the spatial dielectric function, k is a modified Debye-Huckel parameter, and ρ is the charge distribution function. DelPhi firstly grids the space around the molecule and then determines the dielectric at each grid. The charge distribution is determined by the charges of each atom, and the given concentration of given ions. Finally, DelPhi can solve the PBE to get the potential of each grid efficiently in parallel.
The parameters we used are as follows: the iteration steps are determined by DelPhi automatically with the convergence condition set to 0.0001 kT/e. The space occupation of the ribosome is 60% of the calculation box. The dielectric constant inside the ribosome was 4.0, and for water, 80.0 was used. We used the dipolar boundary condition, which calculates the approximate boundary potential by a Debye-Huckel potential that is equivalent to the charge of the molecule. The concentration of implicit monovalent ions added by DelPhi was 0.15M, and their radius is set to 2.0 Å. In some calculations, the magnesium was added to neutralize the net charge of the ribosome, and the radius of them is from AMBER force field. The probe radius used to determine the geometric surface of the ribosome was 1.4 Å, and the grid spacing of coordinates was 1.0 Å. This process takes only 261 seconds on a single computational node, which has two “Intel Xeon E5-2680 v2 @ 2.80 GHz” CPUs (20 cores totally) to complete. To better model the ion effect, the new ion treatment approach is used in the newest DelPhi version(v8.4), which implements a Gaussian-based smooth dielectric function to treats mobile ions via Boltzmann distribution with an added de-solvation penalty. The approach is benchmarked against the experimental salt dependence of binding free energies on seven protein-protein complexes and 12 DNA-protein complexes, which achieved a high accuracy(26). When the DelPhi calculations were done, we compared the results with experiments. Firstly, we found the coordinates of the centerline of the exit tunnel and calculated the potentials of these points. To eliminate the errors, we averaged the potential values over a plane, which is perpendicular to the direction of the tunnel at that position. In this process, we used 3-dimensional linear interpolation to make our results more accurate. In our research, we used PyMol(27), VMD(28), ChimeraX(29) and Chimera(30) to perform the visualization. All the data was processed by matplotlib[42], and the trajectories of the simulation were processed by cpptraj(31) of AMBER14. The exit tunnel was extracted from the ribosome structure by CAVER(32).
Results
Residue population We have counted the number of nucleotides in this structure and found that the proportion of G+C is more than 60%. Although the RNA helix is mainly stabilized by stacking interactions, each G:C pair contributes three hydrogen bonds, while A:U pairs contribute only two. The higher content of G+C than A+U increases the stability of the ribosome, which should provide a stable framework for peptide translation. In this structure, many magnesium ions are found, which help to stabilize the different local structures in this translation machine. Thus, these magnesium ions cannot be ignored when the electrostatic features of the ribosome are studied. The framework of the ribosome structure is provided by 16S, 5S, and 23S ribosomal RNA. The gaps and holes in the RNA are filled with ribosomal proteins (see Figure 1). The analysis of the contents of different residues in this structure (see Table 1) shows that there are significantly more positively charged residues (about 39.2% and 35.2% in the 30S and 50S, respectively) than negatively charged ones (about 5.1% in both subunits) in both 30S and 50S subunits. It is very reasonable to speculate that the dominant population of positively charged residues can help to neutralize the negative charges of RNAs and thus increase the stability of the whole ribosome. Therefore, from the electrostatic point of view, the roles played by ribosomal proteins are crucial for the process of translation.
Table 1. The counts and percentages (%) of different types of residues around the ribosome RNA (5.0 Å radius) in the Thermus thermophiles ribosome. Polar
Non-polar
Charged(-)
Charged(+)
Total
30S
185(12.4%)
298(34.1%)
44(5.1%)
339(39.2%)
866
50S
294(19.7%)
600(40.1%)
76(5.1%)
526(35.2%)
1496
70S
416(19.0%)
829(37.9%)
124(5.7%)
819(37.4%)
2188
Electrostatic surface potential of the ribosome The electrostatic potential of the ribosome was calculated using DelPhi and is displayed in Figure 2, which clearly shows that most parts of the interface between
the 30S and 50S are in negative potential, except the regions where the ribosomal proteins are located. These regions include the surface forming the binding interfaces and the contact points that bind with tRNA. The calculated electrostatic distribution agrees well with the results of Baker et al.(11). In their work, the calculation was completed by APBS(33,34) in a cluster consisted of 343 processors. The 50S subunit from Haloarcula marismortui (PDB ID 1FFK(35)) and the 30S subunit from Thermus thermophilus (PDB ID 1FJG(36)) are used. This suggests that these positively charged regions can help the interaction of 30S-50S subunits and the binding of the tRNA and mRNA to the ribosome. In our work, the circled area in Figure 2(b) shows the binding site of tRNA in the 30S ribosome subunit. The inclusion of magnesium ions has not empowered the strength of positive potential. Instead, it changes the overall potential of the whole interface. The changes are favored by the binding of two subunits if we check the potentials at the interface of the 50S subunit. From Figure S1, we can see the electrostatic potential at the tRNA head(the binding site of the 30S and tRNA) is nearly neutral due to the modified nucleotides. The primary free energy preference comes from the binding of the tRNA and the mRNA. So, the binding site of tRNA on the 30S subunit is, in fact, not favorable compared with the other parts of the interface. The difference of blue circled parts in Figure 3(b) and 3(e) is also neglectable, for the most binding free energy comes from the complicated interaction between the 30S and 50S. From Figure 2(e), we see that the potential at the back of the 30S subunit is not as negative as that of the 30S-50S interface. The potential at the mRNA entrances (blue circle), the exit of mRNA (yellow circle), and top regions in the figure (green circle), are covered by a lot of positive potentials (see Figure 1(d)). These areas are the positions where the positively charged residues are located. Some molecular chaperones and small molecules may bind to these regions when the translation is underway. Comparing the results with and without magnesium ions in Figure 2, we find that the differences are apparent. Although the distribution of magnesium ions around the back of the 30S is quite sparse and that of the interface is dense (see Figure
S2 and Figure S3), the overall electrostatic potential of the back changes a lot with the presence of magnesium ions. This indicated the importance of magnesium ions in the mechanism of the ribosome.
Although the interface of the 50S subunit is mostly negatively charged, the back of this subunit is decorated with positive potential. The previous study has found that the strong negative potential around the outlet of the ribosomal exit tunnel can prevent the nascent peptide from folding into the wrong conformations(13). The yellow circle in Figure 3(e) marks the 5S rRNA, and there are many proteins (L5, L16, L18, L25, L27, and L30) around it (see Figure 4). The surfaces of these proteins are mostly positively charged, which can stabilize their binding to 23S rRNA. Around the exit of the ribosomal tunnel, the addition of magnesium ions increases the positive potential, especially at the surface. This charge distribution may significantly affect the folding dynamics of the newly synthesized peptide chain.
Electrostatic surface potential of molecular chaperones Many molecular chaperones bind to the ribosome when peptide chains are formed, and those molecules are indispensable(37). The most common chaperone is Trigger Factor (TF), which binds to the exit of the ribosomal tunnel to act as a holder of the newly synthesized proteins to avoid the interference of the surrounding environment when the translation is going on(38,39). This dynamical process is as follow: firstly, the TF in the cell binds with L23 and L29 protein; then, the head and tail of TF encase the exit of ribosomal tunnel; after that, the TF interacts with nascent peptide and forms a compact structure; at last, the TF leaves ribosome and goes into the next cycle (38). In order to understand the role played by ribosomal electrostatics in this process, we used the crystal structure of TF binding to the 50S ribosome (PDB ID: 1W26) and the partial structure of TF which binds to ribosomal proteins (PDB ID: 1W2B)(38) to construct the integrated complex and calculated its electrostatic potential (see Figure 5). From (a) and (e), we find the tail of TF is majorly covered with positive potential, which is in contrast with that of the interface at the ribosome
(see (d)). Thus, we infer that the binding of TF to the ribosome is mostly promoted by very strong electrostatic interactions. Moreover, the head of TF is separated from the ribosome by the tight interaction between the tail of TF and ribosome. The left and right arms of TF have no preference for positive or negative potential because of the diversity of peptide chains they must bind to.
To study the interactions between the ribosome and the chaperone, electrostatic force calculations were performed using DelPhiForce(40,41). Figure 6 shows the forces between chaperone and ribosome. In order to visualize the long-range force between them, the chaperone was shifted away from the ribosome. The distance between them is from 0 Å (light grey) to 40 Å (dark grey) with a step of 4 Å. At each position, the electrostatic force on the chaperone was calculated and displayed. The electrostatic binding force from the ribosome attracts the chaperone. Such a long-range force can help the ribosome and the chaperone to bind together even they are at a distance of less than 40 Å. The directions of the forces at different distances are shown in Figure 6, while the magnitudes of these forces are shown in Figure S4 as well as in Table 2. At each position, the binding force is projected on the direction of the displacement from the mass center of the ribosome to the chaperone. Such projected forces are shown in Table 2. The projected binding forces are close to their responsible binding forces without projections because the direction of the electrostatic binding force is approximately along the direction of the displacement from the mass center of chaperone to the mass center of the ribosome.
Table 2. The magnitude of binding forces on the chaperone when the chaperone is at different distances from the ribosome. Distance (Å) 0 4 8 12 16
Binding force (kT/Å) -9.72 -6.99 -4.81 -0.89 -0.69
Projected binding force* (kT/Å) -8.63 -6.16 -2.46 -0.87 -0.67
20 24 28 32 36 40
-0.41 -0.26 -0.15 -0.09 -0.07 -0.04
-0.40 -0.24 -0.14 -0.09 -0.06 -0.04
*The binding force projected on the direction towards the mass centers of ribosome and chaperone.
In addition to TF, many other chaperones bind to the ribosome to promote or to enhance the translation process, including initiation factor (IF), release factor (RF), and elongation factor (EF). A recent Cryo-EM structure shows IF bound to the 70S ribosome (42), as is shown in Figure 7. The IF2 binds between the 30S and 50S subunit (see (a) of Figure 7), and catalyzes their binding to each other. IF2’s head is mainly composed of alpha helixes, and the tail is mostly formed by beta sheets (see Figure 7(b)), which are covered by a lot of positively charged residues (see Figure 7(c)). The subplots (d), (e), and (f) illustrate that the binding sites of IF2 on the 50S are nearly covered by positively potential, too. We suggest that the electrostatic interactions help the binding of the two subunits when the translation process is started.
Electrostatic potential along the ribosomal exit tunnel The inner part of the large subunit of the ribosome is not filled by atoms, and there is an exit tunnel through which nascent peptides get out and enter into the cytoplasm. We extracted the exit tunnel from the ribosome using CAVER(32) and displayed it in Figure 8. The colors represent the B-factor at the corresponding points. The radius of the ribosomal exit tunnel (as a green tube) varies along its length, which is consistent with the results of previous works(4). It is quite rigid nearby the exit of the tunnel but much more flexible at the surface of the ribosome and the inner surface of the exit tunnel where L1, L7/L12, and the CP region are located. It is quite clear that the inner part of the ribosome is very rigid, and only a small part of the wall of the exit tunnel is flexible.
In order to verify our results, we compared the potentials along the exit tunnel with the experimental results of Lu et al. (14). They measured the potentials of 5 points along the exit tunnel by novel probes and strategies developed by them. The distances between these points and the ribosomal peptidyl transferase center (PTC) are about 18, 40, 60, 80, and 102 Å, respectively. Their potentials are about -8, -19, -14, -22 and -19 mV, respectively. It is noted that in their measurement, only a small set of specific points along the exit tunnel were measured, and the locations of these points in the tunnel were approximated using the index of amino acids.
In the translation process, the 30S and 50S subunits bind together to form the 70S particle and separate again when the process is completed. To investigate the changes of the electrostatic potential of the ribosomal exit tunnel when the small and large subunits are bound and unbound, we separately calculated the electrostatic potential of 70S (consisting of 50S and 30S) and of 50S subunits, and compared the potentials at the corresponding positions in the exit tunnel that Lu’s measurements were calculated. The results plotted in Figure 9 demonstrate that our calculations agree with experimental results very well up to the points near the exit of the tunnel in the 70S. More interestingly, the potential changes from negative to positive near the exit. Nevertheless, this is not caused by the aggregation of magnesium ions around the exit. This can be proven by Figure S5. In this figure, the net charge is calculated at each position of the tunnel by summing all the atom charges within a sphere with a radius of 30 angstroms. From about 78 angstroms to 85 angstroms, the net charge decreases, then it increases to positive value until 92 angstroms. And then the net charge decreases to about 0. The number of magnesium ions is counted in the same way. However, the number of magnesium ions decreases continuously until about 140 angstroms from PTC. We suggest two reasons for that: 1) the environment of the experiment is much more complicated than calculations. In real life, there are many chaperones, such as TF bound to the exit of this tunnel; 2) the flexibility of the ribosomal proteins and RNAs around the tunnel’s exit is much larger than that of the buried half. Besides that, our calculations agree well with the experiment at all other
positions. At the beginning of the exit tunnel (about 20 Å from PTC) in the 70S ribosome, the potential is quite low. This is because only a small portion of the metal ions can enter the interface of the 30S and 50S subunits. The variation of the potentials along the exit tunnel may induce the subsequent translation pause or translation arrest(15) when some kinds of peptide sequences are encountered. At the distance of 40 Å from the PTC along with the tunnel, the potential increases due to the influence of the L4 and L22 proteins. The electrostatic potentials of L4 and L22 are quite high near the exit tunnel, as is shown in Figure 10. The potential increases until the distance to PTC along with the tunnel, reaches about 65 Å. Between 65 Å and about 80 Å from the PTC, the potential quickly increases above zero, which is still caused by the existence of ribosome proteins around the exit of the tunnel.
For the 50S subunit, there is a significant difference between our computational results and experimental results and the computational results for the 70S. Although we only removed the 30S subunit from 70S, this significantly affected the electrostatic potentials around the exit of the tunnel. It is evident that the potential of the exit tunnel changes a lot before and after 30S binding to 50S (see Figure 9).
Discussion The significant improvement of computer hardware and software makes it possible to study the electrostatic potential of macromolecule like ribosomes on a desktop workstation with the help of DelPhi. We have done some more in-depth research on the electrostatics of the ribosome to uncover the importance of the unique character in a trial. Our results are reasonable comparing with the experiment and have proven the usability when studying the electrostatic potential of large molecules. However, the calculation and experiment are still simplified relative to the real environment and the dynamics in the cell, which is the main reason that causes the diversity of quantity from real data. In addition to this, the reduced model in PBE has restricted the accuracy in macromolecules, although we can choose a smaller grid size. Moreover, the protein folding problem, protein binding problem, protein-RNA
binding problem, and RNA-RNA binding problem in the life cycle of the ribosome is complicated due to the complex interaction in vivo, even in vitro. Ions are essential to most of the biological processes. The conventional method of handling ions in molecular dynamics simulation or PBE solvation is treating them as charged beads or continuous solvation. The polar characters of ions, especially the magnesium ions, are usually neglected because of the unaffordable time cost. This has limited our understanding of the great importance of ions behind the biological process. In the future work, we think the calculation should be done deeper by introducing the dynamics of ribosome structure and the various molecules binding to it. In the study of the protein folding problem, the importance of ribosome and related molecules should not be neglected due to its particular structure and electrostatic potential. We think it is necessary to improve the accuracy of PBE solver or develop some new methods to help us elucidate the underlying physics in many biological problems.
Conclusions The electrostatics of the ribosome revealed above indicates that the electrostatic interactions play essential roles in protein synthesis and nascent peptide folding. At the interface between the 30S and 50S subunits, some regions are complementary in electrostatic potential distribution, which can decrease the potential barrier between the bound and unbound states of the 30S and 50S. The positively charged PTC can hold the tail of tRNA easily, which is quite crutial for the synthesis of the peptide bond in the translation process. The various chaperones bound to the ribosome are quite specific at the distribution of electrostatic potential. This is because they need to bind to different parts of the ribosome to function correctly. The electrostatic potential, along with the ribosomal exit tunnel, is vital to translation pausing and proper folding of the nascent peptide as it emerges from the tunnel. On the other hand, magnesium ions affect the electrostatic potential around the ribosome. They help the rRNA to form compact structures and promote the binding of
the 30S and 50S. Therefore, the revealed electrostatics are well consistent with the functions of the ribosome and its molecular chaperones and provides a basis for further studying the mechanism of these functions. However, the details of the role of electrostatics of the ribosome in protein synthesis and nascent peptide folding still need further studies, such as how the electrostatic potential affects the movement of nascent peptides along the exit tunnel and their folding within the tunnel. Further research is needed to elucidate the mechanisms behind these complex processes.
Author contributions Y.X. and L.L. designed research; J.W. performed most of calculations and analysis; C.K. performed part of calculations and analysis; L.L. contributed analytic tools; Y.X., L.L.and J.W. wrote the manuscript.
Acknowledgment This work is supported by the NSFC under Grant No. 11874162 and 31570722.
References 1. 2. 3. 4.
5.
6.
7. 8.
Kaiser, C.M. and Liu, K. (2018) Folding up and Moving on-Nascent Protein Folding on the Ribosome. Journal of molecular biology, 430, 4580-4591. Dill, K.A. and MacCallum, J.L. (2012) The protein-folding problem, 50 years on. Science, 338, 1042-1046. Zhou, H.X. (2008) Protein folding in confined and crowded environments. Arch Biochem Biophys, 469, 76-82. Voss, N.R., Gerstein, M., Steitz, T.A. and Moore, P.B. (2006) The geometry of the ribosomal polypeptide exit tunnel. Journal of molecular biology, 360, 893-906. Holtkamp, W., Kokic, G., Jager, M., Mittelstaet, J., Komar, A.A. and Rodnina, M.V. (2015) Cotranslational protein folding on the ribosome monitored in real time. Science, 350, 1104-1107. Wang, E., Wang, J., Chen, C. and Xiao, Y. (2015) Computational evidence that fast translation speed can increase the probability of cotranslational protein folding. Scientific reports, 5, 15316. Chen, C.J., Wang, E.C., Liu, P.Y. and Xiao, Y. (2013) Simulation study of the role of the ribosomal exit tunnel on protein folding. Phys Rev E, 87. Kudva, R., Pardo-Avila, F., Sandhu, H., Carroni, M., Bernstein, H.D. and Von Heijne, G.J.b. (2018) The Shape of the Ribosome Exit Tunnel Affects
9.
10.
11.
12.
13.
14.
15. 16.
17. 18.
19.
20.
21.
22. 23.
Cotranslational Protein Folding. 274191. Nilsson, O.B., Hedman, R., Marino, J., Wickles, S., Bischoff, L., Johansson, M., Muller-Lucks, A., Trovato, F., Puglisi, J.D., O'Brien, E.P. et al. (2015) Cotranslational Protein Folding inside the Ribosome Exit Tunnel. Cell reports, 12, 1533-1540. Kaiser, C.M., Goldman, D.H., Chodera, J.D., Tinoco, I., Jr. and Bustamante, C. (2011) The ribosome modulates nascent protein folding. Science, 334, 1723-1727. Baker, N.A., Sept, D., Joseph, S., Holst, M.J. and McCammon, J.A. (2001) Electrostatics of nanosystems: application to microtubules and the ribosome. Proc Natl Acad Sci U S A, 98, 10037-10041. Kliber, J.S., Hoa, G.H., Douzou, P., Graffe, M. and Grunberg-Manago, M. (1976) Implications of electrostatic potentials on ribosomal proteins. Nucleic Acids Res, 3, 3423-3438. Knight, A.M., Culviner, P.H., Kurt-Yilmaz, N., Zou, T., Ozkan, S.B. and Cavagnero, S. (2013) Electrostatic effect of the ribosomal surface on nascent polypeptide dynamics. ACS chemical biology, 8, 1195-1204. Lu, J., Kobertz, W.R. and Deutsch, C. (2007) Mapping the electrostatic potential within the ribosomal exit tunnel. Journal of molecular biology, 371, 1378-1391. Lu, J. and Deutsch, C. (2008) Electrostatics in the ribosomal tunnel modulate chain elongation rates. Journal of molecular biology, 384, 73-86. Voorhees, R.M., Weixlbaumer, A., Loakes, D., Kelley, A.C. and Ramakrishnan, V. (2009) Insights into substrate stabilization from snapshots of the peptidyl transferase center of the intact 70S ribosome. Nat Struct Mol Biol, 16, 528-533. Case, D., Babin, V., Berryman, J., Betz, R., Cai, Q., Cerutti, D., Cheatham Iii, T., Darden, T., Duke, R. and Gohlke, H. (2014) Amber 14. Jakalian, A., Jack, D.B. and Bayly, C.I. (2002) Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation. J Comput Chem, 23, 1623-1641. Jakalian, A., Bush, B.L., Jack, D.B. and Bayly, C.I.J.J.o.c.c. (2000) Fast, efficient generation of high-quality atomic charges. AM1-BCC model: I. Method. 21, 132-146. Maier, J.A., Martinez, C., Kasavajhala, K., Wickstrom, L., Hauser, K.E. and Simmerling, C. (2015) ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB. J Chem Theory Comput, 11, 3696-3713. 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. Price, D.J. and Brooks, C.L., 3rd. (2004) A modified TIP3P water potential for simulation with Ewald summation. J Chem Phys, 121, 10096-10103. Li, L., Li, C., Sarkar, S., Zhang, J., Witham, S., Zhang, Z., Wang, L., Smith, N.,
24.
25.
26.
27.
28. 29.
30.
31.
32.
33.
34.
35.
36.
37.
Petukh, M. and Alexov, E. (2012) DelPhi: a comprehensive suite for DelPhi software and associated resources. BMC biophysics, 5, 9. Sarkar, S., Witham, S., Zhang, J., Zhenirovskyy, M., Rocchia, W. and Alexov, E. (2013) DelPhi Web Server: A comprehensive online suite for electrostatic calculations of biological macromolecules and their complexes. Commun Comput Phys, 13, 269-284. Li, L., Li, C., Zhang, Z. and Alexov, E. (2013) On the Dielectric "Constant" of Proteins: Smooth Dielectric Function for Macromolecular Modeling and Its Implementation in DelPhi. J Chem Theory Comput, 9, 2126-2136. Jia, Z., Li, L., Chakravorty, A. and Alexov, E. (2017) Treating ion distribution with Gaussian-based smooth dielectric function in DelPhi. J Comput Chem, 38, 1974-1979. Rigsby, R.E. and Parker, A.B. (2016) Using the PyMOL application to reinforce visual understanding of protein structure. Biochem Mol Biol Educ, 44, 433-437. Humphrey, W., Dalke, A. and Schulten, K. (1996) VMD: visual molecular dynamics. Journal of molecular graphics, 14, 33-38. Goddard, T.D., Huang, C.C., Meng, E.C., Pettersen, E.F., Couch, G.S., Morris, J.H. and Ferrin, T.E. (2018) UCSF ChimeraX: Meeting modern challenges in visualization and analysis. Protein Sci, 27, 14-25. Pettersen, E.F., Goddard, T.D., Huang, C.C., Couch, G.S., Greenblatt, D.M., Meng, E.C. and Ferrin, T.E. (2004) UCSF Chimera--a visualization system for exploratory research and analysis. J Comput Chem, 25, 1605-1612. Roe, D.R. and Cheatham, T.E., 3rd. (2013) PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data. J Chem Theory Comput, 9, 3084-3095. Petrek, M., Otyepka, M., Banas, P., Kosinova, P., Koca, J. and Damborsky, J. (2006) CAVER: a new tool to explore routes from protein clefts, pockets and cavities. BMC Bioinformatics, 7, 316. Dolinsky, T.J., Nielsen, J.E., McCammon, J.A. and Baker, N.A. (2004) PDB2PQR: an automated pipeline for the setup of Poisson-Boltzmann electrostatics calculations. Nucleic Acids Res, 32, W665-667. Jurrus, E., Engel, D., Star, K., Monson, K., Brandi, J., Felberg, L.E., Brookes, D.H., Wilson, L., Chen, J., Liles, K. et al. (2018) Improvements to the APBS biomolecular solvation software suite. Protein Sci, 27, 112-128. Ban, N., Nissen, P., Hansen, J., Moore, P.B. and Steitz, T.A. (2000) The complete atomic structure of the large ribosomal subunit at 2.4 A resolution. Science (New York, N.Y.), 289, 905-920. Carter, A.P., Clemons, W.M., Brodersen, D.E., Morgan-Warren, R.J., Wimberly, B.T. and Ramakrishnan, V. (2000) Functional insights from the structure of the 30S ribosomal subunit and its interactions with antibiotics. Nature, 407, 340-348. Hartl, F.U., Bracher, A. and Hayer-Hartl, M. (2011) Molecular chaperones in protein folding and proteostasis. Nature, 475, 324-332.
38.
39.
40.
41.
42.
Ferbitz, L., Maier, T., Patzelt, H., Bukau, B., Deuerling, E. and Ban, N. (2004) Trigger factor in complex with the ribosome forms a molecular cradle for nascent proteins. Nature, 431, 590-596. Merz, F., Boehringer, D., Schaffitzel, C., Preissler, S., Hoffmann, A., Maier, T., Rutkowska, A., Lozza, J., Ban, N., Bukau, B. et al. (2008) Molecular mechanism and structure of Trigger Factor bound to the translating ribosome. The EMBO journal, 27, 1622-1632. Zhao, F., Yu, C.H. and Liu, Y. (2017) Codon usage regulates protein structure and function by affecting translation elongation speed in Drosophila cells. Nucleic acids research, 45, 8484-8492. Li, L., Chakravorty, A. and Alexov, E. (2017) DelPhiForce, a tool for electrostatic force calculations: Applications to macromolecular binding. J Comput Chem, 38, 584-593. Sprink, T., Ramrath, D.J.F., Yamamoto, H., Yamamoto, K., Loerke, J., Ismer, J., Hildebrand, P.W., Scheerer, P., Burger, J., Mielke, T. et al. (2016) Structures of ribosome-bound initiation factor 2 reveal the mechanism of subunit association. Sci Adv, 2.
Figure Captions Figure 1. The overall structure of the Thermus thermophiles 70S ribosome and its two subunits. (a) is the whole structure of the ribosome, and (b) is the same as (a) after rotation of 180 degrees. (c) is the interface of the 30S bound to 50S. (d) is the other side of the 30S compared with (c). (e) is the interface of the 50S bound with the 30S. (f) is the other side of (e). The ribosomal proteins and tRNAs are drawn in cartoon, and the ribosomal RNAs are represented by surface. The different colors in the figure represent different parts of the charged residues. The 16S rRNA is in silver. The 5S rRNA is in orange color. The 23S rRNA in gold color. The A-, P- and E-sites are in yellow, cyan and purple, respectively. For the proteins on the ribosome, the uncharged residues are in dark meat color, the negatively charged residues are in red and the positively charged residues are in blue colors.
Figure 2. The structure and the electrostatic potential of the 30S. (a) and (d) are the cartoon representations of the interface of the 30S bound to 50S. (d) is the back views of (a). (b), (c), (e) and (f) show the electrostatic surface potential of the 30S. The (b) and (c) display the interface, (e) and (f) displays the back views of (b) and (c). (b) and
(e) contain no magnesium, (c) and (f) include magnesium. In (a) and (d), the 16S rRNA is in silver, the proteins are in orange, the A-, P- and E-site tRNAs are in red, blue and green, respectively. In (b), (c), (e), and (f), the blue and red color represent the positive (>5kT/e) and negative potential (<-5kT/e), respectively.
Figure 3. The structure and electrostatic potential of the 50S subunit. (a), (b) and (c) are the interface of it. (d), (e) and (f) are the back views of (a), (b), and (c), respectively. (b) and (e) don not include ions. (c) and (f) contain magnesium ions. The colors are the same as in Figure 2.
Figure 4. 5S rRNA and the electrostatic potential of its surrounding proteins. The RNA is in orange, and protein names are denoted in the figure.
Figure 5. The modelled structure of the Trigger Factor binding to ribosome and its electrostatics potential. (a) The potential of TF. (b) The cartoon representation of TF(green), L23 and L29(yellow). (c) is the same as (b) except the TF is represented in surface plot. (d) the binding interface of L23 and L29. (e) the binding interface of TF. The 23S rRNA is in silver, and the other proteins are in magenta
Figure 6. The electrostatic forces on chaperone calculated by DelPhiForce. The orange arrows show the electrostatic forces performed on the chaperone, which is separated from 0 Å (blue) to 40 Å (grey) with step of 4 Å.
Figure 7. The structure and electrostatics potential of the IF2 bound to yeast ribosome. (a) The overall structure, with the IF2 is in surface plot. (b) The cartoon representation of the IF2. (c) The electrostatic potential of the IF2. (d) The binding interface of the IF2, seen from the 30S. (e) The binding interface of the IF2, seen from the 50S. (f) The binding site of the IF2 to the P-site tRNA. In this figure, the rRNAs are in silver and magenta color, and the ribosome proteins are in green color.
Figure 8. The ribosomal exit tunnel in detail. The path of the tunnel is displayed by a bold line in chocolate color. The ribosome is plotted by surface representation, and the color of it is determined by B-factor. The colors changed from blue to red as the values of B-factor grow. The 23s rRNA and the proteins resides around the tunnel are labeled, respectively.
Figure 9. The averaged electrostatic potential of the 50S and 70S. The red circles in the plot are the experimental results. The blue line and the green line represents the values of the 70S and 50S, respectively. The vertical line at each point is the standard error at the corresponding position. The exit of the ribosomal tunnel is located at a distance of about 80 Å from the PTC.
Figure 10. The electrostatic potential of the L4, L22, and L32 proteins near the ribosomal exit tunnel. The tunnel is in green color, and the 23S rRNA is in silver color.
S0006-3495(20)30047-3
DOI:
https://doi.org/10.1016/j.bpj.2020.01.014
Reference:
BPJ 10266
To appear in:
Biophysical Journal
Received Date: 15 August 2019 Accepted Date: 9 January 2020
Please cite this article as: Wang J, Karki C, Xiao Y, Li L, Electrostatics of Prokaryotic Ribosome and its Biological Implication, Biophysical Journal (2020), doi: https://doi.org/10.1016/j.bpj.2020.01.014. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Biophysical Society.
Electrostatics of Prokaryotic Ribosome and its Biological Implication Jun Wang1, Chitra Karki2, Yi Xiao1* and Lin Li2* 1
School of Physics, Huazhong University of Science and Technology, Wuhan 430074,
Hubei, China 2
Physic Department, University of Texas at El Paso, El Paso, TX, US. 79968
*Corresponding authors
Abstract Ribosomes are essential machines for protein synthesis in cells. Their structures are very complex but conserved in different species. Since most parts of a ribosome are composed of negatively charged RNAs, its electrostatics should play a fundamental role in the realization of its functions. However, a complete picture of the electrostatics of ribosomes is still absent at present. Here, assisted by the latest version of DelPhi (Version: 8.4), we illustrate a picture of the electrostatics of a prokaryotic ribosome as well as its molecular chaperones. The revealed electrostatics features are well consistent with available experimental data as well as the functions of the ribosome and its molecular chaperones and provides a basis for further studying the mechanism underlying these functions.
Statement of Significance Ribosomes are complex molecular machines that make proteins and also help protein folding. It has been known for a long time that electrostatics play important roles in these functions of ribosomes. However, a complete picture of the ribosome electrostatics is absent at present since traditional theoretical and experimental methods are difficult to treat such larger molecules. In this work, assisted by the latest
version of DelPhi updated by one of the coauthor and his colleague, we present a picture for a prokaryotic ribosome as well as its molecular chaperones. It provides a basis for understanding the mechanism underlying the functions of ribosomes.
Introduction It is well known that the ribosome is a molecular machine for protein synthesis in cells. During protein synthesis, not only two subunits of ribosome need to bind to each other, but also many auxiliary proteins and RNAs bind at appropriate stages of protein synthesis, e.g., translational initiation factors, tRNAs, and chaperons. However, the physical mechanism of these interactions is not well understood. On the other hand, it was shown recently that ribosomes might assist in the folding of nascent polypeptides recently(1). The protein folding problem has been studied for over 50 years, but the mechanism of the protein folding is still not well understood(2). For the folding of nascent polypeptides in cells is affected by the environment, including interactions with the ribosome, chaperon molecules (3). Therefore, to make clear the mechanism of both protein synthesis and folding, we need to take the role of ribosome and related proteins into consideration. The ribosome is composed of two subunits: large and small subunits. In the eukaryotic ribosome (80S), they are called 60S and 40S, respectively; while in the prokaryotic ribosome (70S) they are named as 50S and 30S, respectively. The structures of eukaryotic and prokaryotic ribosomes are similar, but their compositions are quite different, though they are all composed of proteins and RNAs. In the 70S ribosome, the 30S subunit is formed by 16S rRNA and about 21 ribosome proteins, and the 50S subunit is composed of 23S rRNA, 15S rRNA, 5S rRNA, and 34 ribosomal proteins. In the 80S ribosome, the 40S subunit includes 18S rRNA and 33 ribosome proteins, while the 60S subunit includes 25S rRNA (or 28S rRNA), 5S rRNA, and 49 ribosome proteins. Consequently, the eukaryotic ribosome is larger and more complex than the prokaryotic ribosome. In this work, we mainly focus on 70S ribosomes from bacteria. The ribosome is among the most complex molecular machines which differ in
composition and structure than any other ones: Firstly, ribosome consists of large RNAs and many proteins and thus contains a large number of atoms (about several million atoms); These RNAs and proteins are strongly coupled with each other. Secondly, the ribosome is not sufficiently rigid. Inside the large subunit, there is a “ribosomal exit tunnel” from which newly synthesized peptide chains emerge (4). This particular tunnel is not just a simple tube for nascent peptides to exit the ribosome. It also plays a significant role in the folding and elongation process of nascent peptides (5-10). It is known that RNA molecules are negatively charged, so electrostatics of the ribosome should play fundamental roles in its structure and dynamics, its interactions with other molecules, and its functions. Up to now, only a few studies of electrostatics features of the ribosome have been accomplished by experiments and computations (11-15). However, these studies mainly focused on one aspect of the electrostatics of the ribosome. For example, Baker et al. computed the electrostatic potential of the ribosome surface and their possible relations with the protein translation process(11). Lu et al. experimentally measured the electrostatic potentials along the ribosomal exit tunnel(14) and studied their effect on the translation rate(15). In this paper, we aim to give a complete picture of the electrostatics of a prokaryote ribosome as well as the bound proteins utilizing a recently updated version of DelPhi and discuss their possible relations with the functions of the ribosome.
Methods We searched the PDB for all ribosome structures and found the one with an intact structure, which has the highest resolution. The crystal structure we studied here comes from the thermophilic bacteria (PDB ID 4V5D(16), see Fig. 1), which includes the 30S and 50S subunits with a resolution of 3.5 Å. Moreover, on its 30S subunit, there are structures of an mRNA, A-site, P-site, E-site tRNAs, and some magnesium ions. Such a high resolution and intact structure provide an excellent opportunity for us to perform high accuracy simulations and therefore obtain reliable analyses. In order to calculate the electrostatic potential of this ribosome structure correctly,
we optimized the structure by AMBER14(17) to eliminate the stereo clash. Firstly, we removed the hydrogen atoms in the crystal structure but preserved all the magnesium ions to reproduce the “real” potential of the ribosome as possibly as we can. Then we used Antechamber module of AMBER14 to model several non-standard residues and calculated their partial charges with the AM1-BCC method(18,19). After that, topology and coordinates were generated using the LeaP program, and the force field we used for optimization was ff14SB(20) and gaff(21). In this process, we also added the magnesium to neutralize the ribosome and TIP3P(22)waters. The number of magnesium ions to be added is determined by the charge of the ribosome and crystallized ions, while the location of the added ions is determined by the lowest potential calculated by tLEaP in AMBER14. Finally, we got a box containing more than 1.7 million atoms. Then, we employed a two-stage minimization strategy: firstly, the energy minimization was performed with the ribosome atoms constrained; Then, we minimize the whole system, with the ribosomal atoms relaxed. In each stage, we ran 1000 steps using the steepest descent method and then 1000 steps using the conjugate gradient method. In the simulation process, the ribosome atoms were constrained by a large spring potential (100kcal/mol). After heating for 50ps and running the MD simulation for 150ps, we obtained the final optimized structure. We then calculated the electrostatic potential of the whole ribosome using the DelPhi program(23-25), which has high accuracy and computational speed that enabled us to calculate the electrostatics of the ribosome quickly and accurately. The nonlinear elliptic Poisson-Boltzmann equation (PBE) is given by ∇ ∙ ൫ߝሺݔሻ∇߶ሺxሻ൯ − ݇ሺݔሻଶ sinh൫߶ሺxሻ൯ = −4ߨߩሺݔሻ,
(1)
Where ϕ is the electrostatic potential, ε is the spatial dielectric function, k is a modified Debye-Huckel parameter, and ρ is the charge distribution function. DelPhi firstly grids the space around the molecule and then determines the dielectric at each grid. The charge distribution is determined by the charges of each atom, and the given concentration of given ions. Finally, DelPhi can solve the PBE to get the potential of each grid efficiently in parallel.
The parameters we used are as follows: the iteration steps are determined by DelPhi automatically with the convergence condition set to 0.0001 kT/e. The space occupation of the ribosome is 60% of the calculation box. The dielectric constant inside the ribosome was 4.0, and for water, 80.0 was used. We used the dipolar boundary condition, which calculates the approximate boundary potential by a Debye-Huckel potential that is equivalent to the charge of the molecule. The concentration of implicit monovalent ions added by DelPhi was 0.15M, and their radius is set to 2.0 Å. In some calculations, the magnesium was added to neutralize the net charge of the ribosome, and the radius of them is from AMBER force field. The probe radius used to determine the geometric surface of the ribosome was 1.4 Å, and the grid spacing of coordinates was 1.0 Å. This process takes only 261 seconds on a single computational node, which has two “Intel Xeon E5-2680 v2 @ 2.80 GHz” CPUs (20 cores totally) to complete. To better model the ion effect, the new ion treatment approach is used in the newest DelPhi version(v8.4), which implements a Gaussian-based smooth dielectric function to treats mobile ions via Boltzmann distribution with an added de-solvation penalty. The approach is benchmarked against the experimental salt dependence of binding free energies on seven protein-protein complexes and 12 DNA-protein complexes, which achieved a high accuracy(26). When the DelPhi calculations were done, we compared the results with experiments. Firstly, we found the coordinates of the centerline of the exit tunnel and calculated the potentials of these points. To eliminate the errors, we averaged the potential values over a plane, which is perpendicular to the direction of the tunnel at that position. In this process, we used 3-dimensional linear interpolation to make our results more accurate. In our research, we used PyMol(27), VMD(28), ChimeraX(29) and Chimera(30) to perform the visualization. All the data was processed by matplotlib[42], and the trajectories of the simulation were processed by cpptraj(31) of AMBER14. The exit tunnel was extracted from the ribosome structure by CAVER(32).
Results
Residue population We have counted the number of nucleotides in this structure and found that the proportion of G+C is more than 60%. Although the RNA helix is mainly stabilized by stacking interactions, each G:C pair contributes three hydrogen bonds, while A:U pairs contribute only two. The higher content of G+C than A+U increases the stability of the ribosome, which should provide a stable framework for peptide translation. In this structure, many magnesium ions are found, which help to stabilize the different local structures in this translation machine. Thus, these magnesium ions cannot be ignored when the electrostatic features of the ribosome are studied. The framework of the ribosome structure is provided by 16S, 5S, and 23S ribosomal RNA. The gaps and holes in the RNA are filled with ribosomal proteins (see Figure 1). The analysis of the contents of different residues in this structure (see Table 1) shows that there are significantly more positively charged residues (about 39.2% and 35.2% in the 30S and 50S, respectively) than negatively charged ones (about 5.1% in both subunits) in both 30S and 50S subunits. It is very reasonable to speculate that the dominant population of positively charged residues can help to neutralize the negative charges of RNAs and thus increase the stability of the whole ribosome. Therefore, from the electrostatic point of view, the roles played by ribosomal proteins are crucial for the process of translation.
Table 1. The counts and percentages (%) of different types of residues around the ribosome RNA (5.0 Å radius) in the Thermus thermophiles ribosome. Polar
Non-polar
Charged(-)
Charged(+)
Total
30S
185(12.4%)
298(34.1%)
44(5.1%)
339(39.2%)
866
50S
294(19.7%)
600(40.1%)
76(5.1%)
526(35.2%)
1496
70S
416(19.0%)
829(37.9%)
124(5.7%)
819(37.4%)
2188
Electrostatic surface potential of the ribosome The electrostatic potential of the ribosome was calculated using DelPhi and is displayed in Figure 2, which clearly shows that most parts of the interface between
the 30S and 50S are in negative potential, except the regions where the ribosomal proteins are located. These regions include the surface forming the binding interfaces and the contact points that bind with tRNA. The calculated electrostatic distribution agrees well with the results of Baker et al.(11). In their work, the calculation was completed by APBS(33,34) in a cluster consisted of 343 processors. The 50S subunit from Haloarcula marismortui (PDB ID 1FFK(35)) and the 30S subunit from Thermus thermophilus (PDB ID 1FJG(36)) are used. This suggests that these positively charged regions can help the interaction of 30S-50S subunits and the binding of the tRNA and mRNA to the ribosome. In our work, the circled area in Figure 2(b) shows the binding site of tRNA in the 30S ribosome subunit. The inclusion of magnesium ions has not empowered the strength of positive potential. Instead, it changes the overall potential of the whole interface. The changes are favored by the binding of two subunits if we check the potentials at the interface of the 50S subunit. From Figure S1, we can see the electrostatic potential at the tRNA head(the binding site of the 30S and tRNA) is nearly neutral due to the modified nucleotides. The primary free energy preference comes from the binding of the tRNA and the mRNA. So, the binding site of tRNA on the 30S subunit is, in fact, not favorable compared with the other parts of the interface. The difference of blue circled parts in Figure 3(b) and 3(e) is also neglectable, for the most binding free energy comes from the complicated interaction between the 30S and 50S. From Figure 2(e), we see that the potential at the back of the 30S subunit is not as negative as that of the 30S-50S interface. The potential at the mRNA entrances (blue circle), the exit of mRNA (yellow circle), and top regions in the figure (green circle), are covered by a lot of positive potentials (see Figure 1(d)). These areas are the positions where the positively charged residues are located. Some molecular chaperones and small molecules may bind to these regions when the translation is underway. Comparing the results with and without magnesium ions in Figure 2, we find that the differences are apparent. Although the distribution of magnesium ions around the back of the 30S is quite sparse and that of the interface is dense (see Figure
S2 and Figure S3), the overall electrostatic potential of the back changes a lot with the presence of magnesium ions. This indicated the importance of magnesium ions in the mechanism of the ribosome.
Although the interface of the 50S subunit is mostly negatively charged, the back of this subunit is decorated with positive potential. The previous study has found that the strong negative potential around the outlet of the ribosomal exit tunnel can prevent the nascent peptide from folding into the wrong conformations(13). The yellow circle in Figure 3(e) marks the 5S rRNA, and there are many proteins (L5, L16, L18, L25, L27, and L30) around it (see Figure 4). The surfaces of these proteins are mostly positively charged, which can stabilize their binding to 23S rRNA. Around the exit of the ribosomal tunnel, the addition of magnesium ions increases the positive potential, especially at the surface. This charge distribution may significantly affect the folding dynamics of the newly synthesized peptide chain.
Electrostatic surface potential of molecular chaperones Many molecular chaperones bind to the ribosome when peptide chains are formed, and those molecules are indispensable(37). The most common chaperone is Trigger Factor (TF), which binds to the exit of the ribosomal tunnel to act as a holder of the newly synthesized proteins to avoid the interference of the surrounding environment when the translation is going on(38,39). This dynamical process is as follow: firstly, the TF in the cell binds with L23 and L29 protein; then, the head and tail of TF encase the exit of ribosomal tunnel; after that, the TF interacts with nascent peptide and forms a compact structure; at last, the TF leaves ribosome and goes into the next cycle (38). In order to understand the role played by ribosomal electrostatics in this process, we used the crystal structure of TF binding to the 50S ribosome (PDB ID: 1W26) and the partial structure of TF which binds to ribosomal proteins (PDB ID: 1W2B)(38) to construct the integrated complex and calculated its electrostatic potential (see Figure 5). From (a) and (e), we find the tail of TF is majorly covered with positive potential, which is in contrast with that of the interface at the ribosome
(see (d)). Thus, we infer that the binding of TF to the ribosome is mostly promoted by very strong electrostatic interactions. Moreover, the head of TF is separated from the ribosome by the tight interaction between the tail of TF and ribosome. The left and right arms of TF have no preference for positive or negative potential because of the diversity of peptide chains they must bind to.
To study the interactions between the ribosome and the chaperone, electrostatic force calculations were performed using DelPhiForce(40,41). Figure 6 shows the forces between chaperone and ribosome. In order to visualize the long-range force between them, the chaperone was shifted away from the ribosome. The distance between them is from 0 Å (light grey) to 40 Å (dark grey) with a step of 4 Å. At each position, the electrostatic force on the chaperone was calculated and displayed. The electrostatic binding force from the ribosome attracts the chaperone. Such a long-range force can help the ribosome and the chaperone to bind together even they are at a distance of less than 40 Å. The directions of the forces at different distances are shown in Figure 6, while the magnitudes of these forces are shown in Figure S4 as well as in Table 2. At each position, the binding force is projected on the direction of the displacement from the mass center of the ribosome to the chaperone. Such projected forces are shown in Table 2. The projected binding forces are close to their responsible binding forces without projections because the direction of the electrostatic binding force is approximately along the direction of the displacement from the mass center of chaperone to the mass center of the ribosome.
Table 2. The magnitude of binding forces on the chaperone when the chaperone is at different distances from the ribosome. Distance (Å) 0 4 8 12 16
Binding force (kT/Å) -9.72 -6.99 -4.81 -0.89 -0.69
Projected binding force* (kT/Å) -8.63 -6.16 -2.46 -0.87 -0.67
20 24 28 32 36 40
-0.41 -0.26 -0.15 -0.09 -0.07 -0.04
-0.40 -0.24 -0.14 -0.09 -0.06 -0.04
*The binding force projected on the direction towards the mass centers of ribosome and chaperone.
In addition to TF, many other chaperones bind to the ribosome to promote or to enhance the translation process, including initiation factor (IF), release factor (RF), and elongation factor (EF). A recent Cryo-EM structure shows IF bound to the 70S ribosome (42), as is shown in Figure 7. The IF2 binds between the 30S and 50S subunit (see (a) of Figure 7), and catalyzes their binding to each other. IF2’s head is mainly composed of alpha helixes, and the tail is mostly formed by beta sheets (see Figure 7(b)), which are covered by a lot of positively charged residues (see Figure 7(c)). The subplots (d), (e), and (f) illustrate that the binding sites of IF2 on the 50S are nearly covered by positively potential, too. We suggest that the electrostatic interactions help the binding of the two subunits when the translation process is started.
Electrostatic potential along the ribosomal exit tunnel The inner part of the large subunit of the ribosome is not filled by atoms, and there is an exit tunnel through which nascent peptides get out and enter into the cytoplasm. We extracted the exit tunnel from the ribosome using CAVER(32) and displayed it in Figure 8. The colors represent the B-factor at the corresponding points. The radius of the ribosomal exit tunnel (as a green tube) varies along its length, which is consistent with the results of previous works(4). It is quite rigid nearby the exit of the tunnel but much more flexible at the surface of the ribosome and the inner surface of the exit tunnel where L1, L7/L12, and the CP region are located. It is quite clear that the inner part of the ribosome is very rigid, and only a small part of the wall of the exit tunnel is flexible.
In order to verify our results, we compared the potentials along the exit tunnel with the experimental results of Lu et al. (14). They measured the potentials of 5 points along the exit tunnel by novel probes and strategies developed by them. The distances between these points and the ribosomal peptidyl transferase center (PTC) are about 18, 40, 60, 80, and 102 Å, respectively. Their potentials are about -8, -19, -14, -22 and -19 mV, respectively. It is noted that in their measurement, only a small set of specific points along the exit tunnel were measured, and the locations of these points in the tunnel were approximated using the index of amino acids.
In the translation process, the 30S and 50S subunits bind together to form the 70S particle and separate again when the process is completed. To investigate the changes of the electrostatic potential of the ribosomal exit tunnel when the small and large subunits are bound and unbound, we separately calculated the electrostatic potential of 70S (consisting of 50S and 30S) and of 50S subunits, and compared the potentials at the corresponding positions in the exit tunnel that Lu’s measurements were calculated. The results plotted in Figure 9 demonstrate that our calculations agree with experimental results very well up to the points near the exit of the tunnel in the 70S. More interestingly, the potential changes from negative to positive near the exit. Nevertheless, this is not caused by the aggregation of magnesium ions around the exit. This can be proven by Figure S5. In this figure, the net charge is calculated at each position of the tunnel by summing all the atom charges within a sphere with a radius of 30 angstroms. From about 78 angstroms to 85 angstroms, the net charge decreases, then it increases to positive value until 92 angstroms. And then the net charge decreases to about 0. The number of magnesium ions is counted in the same way. However, the number of magnesium ions decreases continuously until about 140 angstroms from PTC. We suggest two reasons for that: 1) the environment of the experiment is much more complicated than calculations. In real life, there are many chaperones, such as TF bound to the exit of this tunnel; 2) the flexibility of the ribosomal proteins and RNAs around the tunnel’s exit is much larger than that of the buried half. Besides that, our calculations agree well with the experiment at all other
positions. At the beginning of the exit tunnel (about 20 Å from PTC) in the 70S ribosome, the potential is quite low. This is because only a small portion of the metal ions can enter the interface of the 30S and 50S subunits. The variation of the potentials along the exit tunnel may induce the subsequent translation pause or translation arrest(15) when some kinds of peptide sequences are encountered. At the distance of 40 Å from the PTC along with the tunnel, the potential increases due to the influence of the L4 and L22 proteins. The electrostatic potentials of L4 and L22 are quite high near the exit tunnel, as is shown in Figure 10. The potential increases until the distance to PTC along with the tunnel, reaches about 65 Å. Between 65 Å and about 80 Å from the PTC, the potential quickly increases above zero, which is still caused by the existence of ribosome proteins around the exit of the tunnel.
For the 50S subunit, there is a significant difference between our computational results and experimental results and the computational results for the 70S. Although we only removed the 30S subunit from 70S, this significantly affected the electrostatic potentials around the exit of the tunnel. It is evident that the potential of the exit tunnel changes a lot before and after 30S binding to 50S (see Figure 9).
Discussion The significant improvement of computer hardware and software makes it possible to study the electrostatic potential of macromolecule like ribosomes on a desktop workstation with the help of DelPhi. We have done some more in-depth research on the electrostatics of the ribosome to uncover the importance of the unique character in a trial. Our results are reasonable comparing with the experiment and have proven the usability when studying the electrostatic potential of large molecules. However, the calculation and experiment are still simplified relative to the real environment and the dynamics in the cell, which is the main reason that causes the diversity of quantity from real data. In addition to this, the reduced model in PBE has restricted the accuracy in macromolecules, although we can choose a smaller grid size. Moreover, the protein folding problem, protein binding problem, protein-RNA
binding problem, and RNA-RNA binding problem in the life cycle of the ribosome is complicated due to the complex interaction in vivo, even in vitro. Ions are essential to most of the biological processes. The conventional method of handling ions in molecular dynamics simulation or PBE solvation is treating them as charged beads or continuous solvation. The polar characters of ions, especially the magnesium ions, are usually neglected because of the unaffordable time cost. This has limited our understanding of the great importance of ions behind the biological process. In the future work, we think the calculation should be done deeper by introducing the dynamics of ribosome structure and the various molecules binding to it. In the study of the protein folding problem, the importance of ribosome and related molecules should not be neglected due to its particular structure and electrostatic potential. We think it is necessary to improve the accuracy of PBE solver or develop some new methods to help us elucidate the underlying physics in many biological problems.
Conclusions The electrostatics of the ribosome revealed above indicates that the electrostatic interactions play essential roles in protein synthesis and nascent peptide folding. At the interface between the 30S and 50S subunits, some regions are complementary in electrostatic potential distribution, which can decrease the potential barrier between the bound and unbound states of the 30S and 50S. The positively charged PTC can hold the tail of tRNA easily, which is quite crutial for the synthesis of the peptide bond in the translation process. The various chaperones bound to the ribosome are quite specific at the distribution of electrostatic potential. This is because they need to bind to different parts of the ribosome to function correctly. The electrostatic potential, along with the ribosomal exit tunnel, is vital to translation pausing and proper folding of the nascent peptide as it emerges from the tunnel. On the other hand, magnesium ions affect the electrostatic potential around the ribosome. They help the rRNA to form compact structures and promote the binding of
the 30S and 50S. Therefore, the revealed electrostatics are well consistent with the functions of the ribosome and its molecular chaperones and provides a basis for further studying the mechanism of these functions. However, the details of the role of electrostatics of the ribosome in protein synthesis and nascent peptide folding still need further studies, such as how the electrostatic potential affects the movement of nascent peptides along the exit tunnel and their folding within the tunnel. Further research is needed to elucidate the mechanisms behind these complex processes.
Author contributions Y.X. and L.L. designed research; J.W. performed most of calculations and analysis; C.K. performed part of calculations and analysis; L.L. contributed analytic tools; Y.X., L.L.and J.W. wrote the manuscript.
Acknowledgment This work is supported by the NSFC under Grant No. 11874162 and 31570722.
References 1. 2. 3. 4.
5.
6.
7. 8.
Kaiser, C.M. and Liu, K. (2018) Folding up and Moving on-Nascent Protein Folding on the Ribosome. Journal of molecular biology, 430, 4580-4591. Dill, K.A. and MacCallum, J.L. (2012) The protein-folding problem, 50 years on. Science, 338, 1042-1046. Zhou, H.X. (2008) Protein folding in confined and crowded environments. Arch Biochem Biophys, 469, 76-82. Voss, N.R., Gerstein, M., Steitz, T.A. and Moore, P.B. (2006) The geometry of the ribosomal polypeptide exit tunnel. Journal of molecular biology, 360, 893-906. Holtkamp, W., Kokic, G., Jager, M., Mittelstaet, J., Komar, A.A. and Rodnina, M.V. (2015) Cotranslational protein folding on the ribosome monitored in real time. Science, 350, 1104-1107. Wang, E., Wang, J., Chen, C. and Xiao, Y. (2015) Computational evidence that fast translation speed can increase the probability of cotranslational protein folding. Scientific reports, 5, 15316. Chen, C.J., Wang, E.C., Liu, P.Y. and Xiao, Y. (2013) Simulation study of the role of the ribosomal exit tunnel on protein folding. Phys Rev E, 87. Kudva, R., Pardo-Avila, F., Sandhu, H., Carroni, M., Bernstein, H.D. and Von Heijne, G.J.b. (2018) The Shape of the Ribosome Exit Tunnel Affects
9.
10.
11.
12.
13.
14.
15. 16.
17. 18.
19.
20.
21.
22. 23.
Cotranslational Protein Folding. 274191. Nilsson, O.B., Hedman, R., Marino, J., Wickles, S., Bischoff, L., Johansson, M., Muller-Lucks, A., Trovato, F., Puglisi, J.D., O'Brien, E.P. et al. (2015) Cotranslational Protein Folding inside the Ribosome Exit Tunnel. Cell reports, 12, 1533-1540. Kaiser, C.M., Goldman, D.H., Chodera, J.D., Tinoco, I., Jr. and Bustamante, C. (2011) The ribosome modulates nascent protein folding. Science, 334, 1723-1727. Baker, N.A., Sept, D., Joseph, S., Holst, M.J. and McCammon, J.A. (2001) Electrostatics of nanosystems: application to microtubules and the ribosome. Proc Natl Acad Sci U S A, 98, 10037-10041. Kliber, J.S., Hoa, G.H., Douzou, P., Graffe, M. and Grunberg-Manago, M. (1976) Implications of electrostatic potentials on ribosomal proteins. Nucleic Acids Res, 3, 3423-3438. Knight, A.M., Culviner, P.H., Kurt-Yilmaz, N., Zou, T., Ozkan, S.B. and Cavagnero, S. (2013) Electrostatic effect of the ribosomal surface on nascent polypeptide dynamics. ACS chemical biology, 8, 1195-1204. Lu, J., Kobertz, W.R. and Deutsch, C. (2007) Mapping the electrostatic potential within the ribosomal exit tunnel. Journal of molecular biology, 371, 1378-1391. Lu, J. and Deutsch, C. (2008) Electrostatics in the ribosomal tunnel modulate chain elongation rates. Journal of molecular biology, 384, 73-86. Voorhees, R.M., Weixlbaumer, A., Loakes, D., Kelley, A.C. and Ramakrishnan, V. (2009) Insights into substrate stabilization from snapshots of the peptidyl transferase center of the intact 70S ribosome. Nat Struct Mol Biol, 16, 528-533. Case, D., Babin, V., Berryman, J., Betz, R., Cai, Q., Cerutti, D., Cheatham Iii, T., Darden, T., Duke, R. and Gohlke, H. (2014) Amber 14. Jakalian, A., Jack, D.B. and Bayly, C.I. (2002) Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation. J Comput Chem, 23, 1623-1641. Jakalian, A., Bush, B.L., Jack, D.B. and Bayly, C.I.J.J.o.c.c. (2000) Fast, efficient generation of high-quality atomic charges. AM1-BCC model: I. Method. 21, 132-146. Maier, J.A., Martinez, C., Kasavajhala, K., Wickstrom, L., Hauser, K.E. and Simmerling, C. (2015) ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB. J Chem Theory Comput, 11, 3696-3713. 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. Price, D.J. and Brooks, C.L., 3rd. (2004) A modified TIP3P water potential for simulation with Ewald summation. J Chem Phys, 121, 10096-10103. Li, L., Li, C., Sarkar, S., Zhang, J., Witham, S., Zhang, Z., Wang, L., Smith, N.,
24.
25.
26.
27.
28. 29.
30.
31.
32.
33.
34.
35.
36.
37.
Petukh, M. and Alexov, E. (2012) DelPhi: a comprehensive suite for DelPhi software and associated resources. BMC biophysics, 5, 9. Sarkar, S., Witham, S., Zhang, J., Zhenirovskyy, M., Rocchia, W. and Alexov, E. (2013) DelPhi Web Server: A comprehensive online suite for electrostatic calculations of biological macromolecules and their complexes. Commun Comput Phys, 13, 269-284. Li, L., Li, C., Zhang, Z. and Alexov, E. (2013) On the Dielectric "Constant" of Proteins: Smooth Dielectric Function for Macromolecular Modeling and Its Implementation in DelPhi. J Chem Theory Comput, 9, 2126-2136. Jia, Z., Li, L., Chakravorty, A. and Alexov, E. (2017) Treating ion distribution with Gaussian-based smooth dielectric function in DelPhi. J Comput Chem, 38, 1974-1979. Rigsby, R.E. and Parker, A.B. (2016) Using the PyMOL application to reinforce visual understanding of protein structure. Biochem Mol Biol Educ, 44, 433-437. Humphrey, W., Dalke, A. and Schulten, K. (1996) VMD: visual molecular dynamics. Journal of molecular graphics, 14, 33-38. Goddard, T.D., Huang, C.C., Meng, E.C., Pettersen, E.F., Couch, G.S., Morris, J.H. and Ferrin, T.E. (2018) UCSF ChimeraX: Meeting modern challenges in visualization and analysis. Protein Sci, 27, 14-25. Pettersen, E.F., Goddard, T.D., Huang, C.C., Couch, G.S., Greenblatt, D.M., Meng, E.C. and Ferrin, T.E. (2004) UCSF Chimera--a visualization system for exploratory research and analysis. J Comput Chem, 25, 1605-1612. Roe, D.R. and Cheatham, T.E., 3rd. (2013) PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data. J Chem Theory Comput, 9, 3084-3095. Petrek, M., Otyepka, M., Banas, P., Kosinova, P., Koca, J. and Damborsky, J. (2006) CAVER: a new tool to explore routes from protein clefts, pockets and cavities. BMC Bioinformatics, 7, 316. Dolinsky, T.J., Nielsen, J.E., McCammon, J.A. and Baker, N.A. (2004) PDB2PQR: an automated pipeline for the setup of Poisson-Boltzmann electrostatics calculations. Nucleic Acids Res, 32, W665-667. Jurrus, E., Engel, D., Star, K., Monson, K., Brandi, J., Felberg, L.E., Brookes, D.H., Wilson, L., Chen, J., Liles, K. et al. (2018) Improvements to the APBS biomolecular solvation software suite. Protein Sci, 27, 112-128. Ban, N., Nissen, P., Hansen, J., Moore, P.B. and Steitz, T.A. (2000) The complete atomic structure of the large ribosomal subunit at 2.4 A resolution. Science (New York, N.Y.), 289, 905-920. Carter, A.P., Clemons, W.M., Brodersen, D.E., Morgan-Warren, R.J., Wimberly, B.T. and Ramakrishnan, V. (2000) Functional insights from the structure of the 30S ribosomal subunit and its interactions with antibiotics. Nature, 407, 340-348. Hartl, F.U., Bracher, A. and Hayer-Hartl, M. (2011) Molecular chaperones in protein folding and proteostasis. Nature, 475, 324-332.
38.
39.
40.
41.
42.
Ferbitz, L., Maier, T., Patzelt, H., Bukau, B., Deuerling, E. and Ban, N. (2004) Trigger factor in complex with the ribosome forms a molecular cradle for nascent proteins. Nature, 431, 590-596. Merz, F., Boehringer, D., Schaffitzel, C., Preissler, S., Hoffmann, A., Maier, T., Rutkowska, A., Lozza, J., Ban, N., Bukau, B. et al. (2008) Molecular mechanism and structure of Trigger Factor bound to the translating ribosome. The EMBO journal, 27, 1622-1632. Zhao, F., Yu, C.H. and Liu, Y. (2017) Codon usage regulates protein structure and function by affecting translation elongation speed in Drosophila cells. Nucleic acids research, 45, 8484-8492. Li, L., Chakravorty, A. and Alexov, E. (2017) DelPhiForce, a tool for electrostatic force calculations: Applications to macromolecular binding. J Comput Chem, 38, 584-593. Sprink, T., Ramrath, D.J.F., Yamamoto, H., Yamamoto, K., Loerke, J., Ismer, J., Hildebrand, P.W., Scheerer, P., Burger, J., Mielke, T. et al. (2016) Structures of ribosome-bound initiation factor 2 reveal the mechanism of subunit association. Sci Adv, 2.
Figure Captions Figure 1. The overall structure of the Thermus thermophiles 70S ribosome and its two subunits. (a) is the whole structure of the ribosome, and (b) is the same as (a) after rotation of 180 degrees. (c) is the interface of the 30S bound to 50S. (d) is the other side of the 30S compared with (c). (e) is the interface of the 50S bound with the 30S. (f) is the other side of (e). The ribosomal proteins and tRNAs are drawn in cartoon, and the ribosomal RNAs are represented by surface. The different colors in the figure represent different parts of the charged residues. The 16S rRNA is in silver. The 5S rRNA is in orange color. The 23S rRNA in gold color. The A-, P- and E-sites are in yellow, cyan and purple, respectively. For the proteins on the ribosome, the uncharged residues are in dark meat color, the negatively charged residues are in red and the positively charged residues are in blue colors.
Figure 2. The structure and the electrostatic potential of the 30S. (a) and (d) are the cartoon representations of the interface of the 30S bound to 50S. (d) is the back views of (a). (b), (c), (e) and (f) show the electrostatic surface potential of the 30S. The (b) and (c) display the interface, (e) and (f) displays the back views of (b) and (c). (b) and
(e) contain no magnesium, (c) and (f) include magnesium. In (a) and (d), the 16S rRNA is in silver, the proteins are in orange, the A-, P- and E-site tRNAs are in red, blue and green, respectively. In (b), (c), (e), and (f), the blue and red color represent the positive (>5kT/e) and negative potential (<-5kT/e), respectively.
Figure 3. The structure and electrostatic potential of the 50S subunit. (a), (b) and (c) are the interface of it. (d), (e) and (f) are the back views of (a), (b), and (c), respectively. (b) and (e) don not include ions. (c) and (f) contain magnesium ions. The colors are the same as in Figure 2.
Figure 4. 5S rRNA and the electrostatic potential of its surrounding proteins. The RNA is in orange, and protein names are denoted in the figure.
Figure 5. The modelled structure of the Trigger Factor binding to ribosome and its electrostatics potential. (a) The potential of TF. (b) The cartoon representation of TF(green), L23 and L29(yellow). (c) is the same as (b) except the TF is represented in surface plot. (d) the binding interface of L23 and L29. (e) the binding interface of TF. The 23S rRNA is in silver, and the other proteins are in magenta
Figure 6. The electrostatic forces on chaperone calculated by DelPhiForce. The orange arrows show the electrostatic forces performed on the chaperone, which is separated from 0 Å (blue) to 40 Å (grey) with step of 4 Å.
Figure 7. The structure and electrostatics potential of the IF2 bound to yeast ribosome. (a) The overall structure, with the IF2 is in surface plot. (b) The cartoon representation of the IF2. (c) The electrostatic potential of the IF2. (d) The binding interface of the IF2, seen from the 30S. (e) The binding interface of the IF2, seen from the 50S. (f) The binding site of the IF2 to the P-site tRNA. In this figure, the rRNAs are in silver and magenta color, and the ribosome proteins are in green color.
Figure 8. The ribosomal exit tunnel in detail. The path of the tunnel is displayed by a bold line in chocolate color. The ribosome is plotted by surface representation, and the color of it is determined by B-factor. The colors changed from blue to red as the values of B-factor grow. The 23s rRNA and the proteins resides around the tunnel are labeled, respectively.
Figure 9. The averaged electrostatic potential of the 50S and 70S. The red circles in the plot are the experimental results. The blue line and the green line represents the values of the 70S and 50S, respectively. The vertical line at each point is the standard error at the corresponding position. The exit of the ribosomal tunnel is located at a distance of about 80 Å from the PTC.
Figure 10. The electrostatic potential of the L4, L22, and L32 proteins near the ribosomal exit tunnel. The tunnel is in green color, and the 23S rRNA is in silver color.