Identification of potential allosteric communication pathways between functional sites of the bacterial ribosome by graph and elastic network models

Accepted Manuscript Identification of potential allosteric communication pathways between functional sites of the bacterial ribosome by graph and elastic network models

Pelin Guzel, Ozge Kurkcuoglu PII: DOI: Reference:

S0304-4165(17)30289-1 doi: 10.1016/j.bbagen.2017.09.005 BBAGEN 28938

To appear in: Received date: Revised date: Accepted date:

15 April 2017 11 September 2017 12 September 2017

Please cite this article as: Pelin Guzel, Ozge Kurkcuoglu , Identification of potential allosteric communication pathways between functional sites of the bacterial ribosome by graph and elastic network models, (2017), doi: 10.1016/j.bbagen.2017.09.005

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Identification of potential allosteric communication pathways between functional sites of the bacterial ribosome by graph and elastic network models

Pelin Guzel, Ozge Kurkcuoglu*

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Department of Chemical Engineering, Istanbul Technical University, Istanbul, Turkey

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*Corresponding Author, e-mail: [email protected], Tel: +90 212 2853523

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Abstract Background: Accumulated evidence indicates that bacterial ribosome employs allostery throughout its structure for protein synthesis. The nature of the allosteric communication between remote functional sites remains unclear, but the contact topology and dynamics of residues may play role in transmission of a perturbation to distant sites. Methods/Results: We employ two computationally efficient approaches – graph and elastic

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network modelling to gain insights about the allosteric communication in ribosome. Using graph representation of the structure, we perform k-shortest pathways analysis between peptidyl

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transferase center-ribosomal tunnel, decoding center-peptidyl transferase center - previously

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reported functional sites having allosteric communication. Detailed analysis on intact structures points to common and alternative shortest pathways preferred by different states of translation. All shortest pathways capture drug target sites and allosterically important regions. Elastic

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network model further reveals that residues along all pathways have the ability of quickly establishing pair-wise communication and to help the propagation of a perturbation in long-

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ranges during functional motions of the complex.

Conclusions: Contact topology and inherent dynamics of ribosome configure potential

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communication pathways between functional sites in different translation states. Inter-subunit

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bridges B2a, B3 and P-tRNA come forward for their high potential in assisting allostery during translation. Especially B3 emerges as a potential druggable site. General Significance: This study indicates that the ribosome topology forms a basis for

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allosteric communication, which can be disrupted by novel drugs to kill drug-resistant bacteria. Our computationally efficient approach not only overlaps with experimental evidence on

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allosteric regulation in ribosome but also proposes new druggable sites.

Keywords: allosteric regulation; bacterial ribosome; coarse-graining; k-shortest pathways; anisotropic network model Abbreviations: DC Decoding Center; PTC Peptidyl Transferase Center; EF Elongation Factor; tRNA transfer RNA; mRNA messenger RNA; rRNA ribosomal RNA; A Aminoacyl; P Peptidyl; E Exit; RF Release Factor.

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1. Introduction The supramolecule ribosome translates the genetic code to a functional protein in all living cells. Accumulated evidence points to an allosteric communication network between its many functional yet distant sites for the regulation of this vital process. The communication is likely to be retained by means of conformational changes involving tertiary interactions, while

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binding of an inhibitor or mutations may inhibit fluctuations of critical residues at functional

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regions [1-4]. Exploring the allosteric paths is a key to reveal the underlying mechanisms of translation, as well as to design new antibiotics targeting non-orthosteric sites for drug-

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resistant bacteria [5].

The genetic code is translated in the decoding center (DC) formed by conserved and flexible

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nucleotides G530, A1492 and A1493 (Thermus thermophilus numbering scheme is used here and throughout the manuscript unless stated otherwise. The corresponding Escherichia coli

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numbering is given in parentheses if different) constantly monitoring the cognate transfer

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RNA (tRNA) [6-8] (Fig. 1). Although DC occupies a small area compared to the supramolecule ribosome, the effects of its functional motions are revealed at distant sites of

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the complex. Mutational studies on yeast ribosome, revealed an allosteric link between DC on small subunit and peptidyl transferase center (PTC), which is the catalytic cavity for peptide

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bond synthesis on the large subunit, extending through nucleotides C2452 and U2554 on 23S ribosomal RNA (rRNA) [9]. Similarly, extensive studies on yeast ribosome detected sophisticated signaling pathways between DC and PTC, crossing the B1b/c inter-subunit bridge at the interface of ribosomal proteins S18 and L11 [10]. Additionally, Sergiev et al. proposed that the inter-subunit bridge B1a, a conserved A-site finger near B1b/c, is a part of an allosteric system linking DC with functional regions on the bacterial large subunit [11]. Unique position of 5S rRNA at the central protuberance, close to inter-subunit bridges B1a and B1b/c, was suggested to be involved in allosteric communication of distant functional

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sites on the ribosome complex [12]. On the other hand for Thermus thermophilus, Laurberg et al. reported that conformational changes of nucleotides A1493 of 16S rRNA, A1913 of 23S rRNA and switch loop of release factor (RF) 1 maintain coordination between DC and PTC to prevent a premature termination in translation [13]. A structural study on elongation factor (EF)-Tu bound bacterial ribosome revealed a communication pathway between the catalytic

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site of EF-Tu assisting acetylated-tRNA and DC located 80 Å away [14]. Consequently, this

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functional region appears as one of the hubs of the allosteric communication network

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extending throughout the ribosome complex.

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Fig. 1. Architecture of the Thermus thermophilus ribosome complex. On the bacterial ribosome complex (PDB ID: 2wdk-2wdl [15]), small subunit 30S (rRNA in blue, ribosomal

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proteins in light blue), large subunit 50S (rRNAs in gray, ribosomal proteins in light gray), AtRNA (in orange), ribosomal proteins L4 (in green), L22 (in purple) and other critical sites are

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indicated.

PTC is another hub region constantly communicating with various parts of the complex, besides DC. Mutational studies on Haloarcula marismortui 50S ribosomal subunit suggested

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a transmission of information between the GTPase center of EFs, the sarcin-ricin loop and

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PTC [2]. A communication pathway between aminoacyl (A), peptidyl (P) and exit (E) sites of PTC on the large subunit and EF binding site in yeast was revealed by a chemical protection analysis [9]. Additional to this study, genetic, biochemical and structure probing analyses pointed to the role of the ribosomal protein L3 to coordinate an allosteric signaling pathway between PTC and EF binding site [16, 17]. An apparent communication pathway of residues was proposed for the narrow gate of the Escherichia coli ribosomal tunnel (Fig. 1) between the flexible nucleotide A2062 and the A-site crevice of PTC, which can modulate the stalling of the ribosome complex during the synthesis of specific polypeptides [18]. This finding was

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supported by other experimental and computational studies [4, 19, 20]. Similarly, several groups investigated allostery at the entrance of the ribosomal tunnel [3, 21, 22] and provided valuable hints on communication mechanisms between the tunnel and PTC.

Two classical models on allostery, Monod-Wyman-Changeux [23] and Koshland-Nemethy-

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Filmer [24], consider that perturbation of an effector at one site induces a conformational transition between two distinct states of the protein (relaxed and tense) for biological function.

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While these two distinct conformations coexist at equilibrium, the binding of the effector

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alters the active site conformation using a single and well-defined signal propagation pathway. Recent understanding on allostery assumes native states as ensembles of pre-existing

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populations, which may experience an equilibrium shift due to an effector [25], but not

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necessarily undergoing a significant conformational change [26]. This recent view also implies multiple communication pathways, major and minor, between the allosteric site and

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the functional site. A mutation resulting in a significant effect, such as a decrease in activity or

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lethality, may point to a major pathway or a minor effect suggests a minor pathway [27]. Existence of major and minor pathways in a protein structure was supported by experimental

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data such as for PDZ domain family [28, 29], and CREB binding protein CBP [30, 31].

Using experimental approaches to reveal allosteric communication pathways on protein

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structures are very time and resource consuming, especially for very large complexes like the ribosome. At this point, computational models studying allostery based on protein structures provide useful testable insights [32, 33]. Various computational approaches have been developed to reveal signaling pathways of residues in allosteric proteins [34-43]. Additionally, there exist web-based servers, applications and databases to predict signal propagation pathways in proteins and their complexes [44-48].

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In this study, we aim to understand the role of the contact topology of bacterial ribosome together with its functional dynamics on the formation of allosteric pathways by taking experimental evidence as reference. The structure of this 2.5 MDa supramolecule is composed of proteins and rRNA. Therefore, it necessitates advanced computational resources and a reliable molecular force field for a full-atom technique, or large memory requirements for the

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available applications to reveal allosteric networks. Here, we took a computationally efficient

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and a force-field independent approach by employing two different methods: k-shortest

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pathways calculation on a graph model and elastic network modeling. We calculated kshortest pathways of residues between allosterically linked sites of the ribosome, namely DC,

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PTC and discriminating gate of the ribosomal tunnel to explore potential major and minor shortest pathways formed by the ribosome topology. Network approaches are simple yet

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powerful in identifying potential short cuts between distant sites of a protein, by extracting the important topological features of its complicated structure [33, 34] . Motivated by the success

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of structure-based models to reveal signaling pathways in proteins [33-36, 42, 49, 50], we

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modeled the ribosome structure as a weighted graph based on approximated inter-residue interactions. Then, we employed Yen’s algorithm [51] to obtain k-shortest pathways between

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predefined nodes. Here, we aim to reveal how much of known allosteric residues can be captured along the shortest pathways defined by the ribosome topology, rather than taking a

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sequence-based approach [52]. Various studies underline the role of contact topology of the protein in long-range transmission of allosteric signals by coupled interactions and conformational changes of residues [41, 42, 49, 50, 53-55]. In this line, we employed elastic network model using normal mode analysis [56] to examine fluctuations of the shortest pathways residues in functional motions of the ribosome. Functional global dynamics include energetically favorable motions and involve high collectivity of residues, which can describe the long-range character of

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allosteric communication. These motions can be obtained from low-frequency spectrum of vibrational modes of the native structure. Previously for the bacterial ribosome and its components, ratchet-rotation of subunits, head rotation of the small subunit, anti-correlated motions of large L1 and L7/L12 stalks, translocation of tRNAs were successfully produced by the elastic network modeling [57-59]. For all calculated pathways, we investigated cross-

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correlations of residues in low-frequency motions, where high cross-correlation contributes to

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allosteric communication in proteins. We further investigated the mean-squared fluctuations

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of distances of consecutive residues forming the shortest paths. Small distance fluctuations between residues imply short commute times between these, which consequently have high

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potential to transmit a signal [60].

This combined approach of graph and elastic network models can aid us to get insights about

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the effect of translational states on the formation of shortest pathways, critical residues and

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potential druggable sites.

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regions for the shortest pathways, residue-pairs with high ability of communication and

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2.1. Dataset

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2. Materials and Methods

Crystal structures of ribosome complex of Thermus thermophilus representing different states of the translation process are investigated (Table 1). Three structures outline the elongation phase of the protein synthesis and one structure belongs to the termination phase.

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Table 1. Translation states of the bacterial ribosome complex investigated in this study. PDB ID: 2j00 - 2j01 [61] 4juw - 4jux [62]

Resolution (Å) 2.8

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2wdk - 2wdl [15]

Translation state Ribosome complex at pre-translocational state including mRNA, P- and E-tRNAs Ribosome complex at intermediate state of translocation including mRNA, P/E-tRNA and EFG.GTP complex Ribosome complex at pre-peptidyl transfer state including mRNA, A-, P- and E-tRNAs Ribosome complex at translation termination state including mRNA, P-, E-tRNAs and RF2

3.5 3.0

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3f1e - 3f1f [63]

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2.2. k-shortest pathways

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A protein structure can be described as a three-dimensional weighted graph formed of nodes

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that are linked by edges. In this representation, nodes are placed at C (amino acids) and P (nucleotides) atoms, and neighboring nodes are connected by edges with predictable lengths.

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Length of an edge can be estimated using the local interaction strength between two residues

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(nodes), assuming that probability of communication between two residues is a function of their interaction strength. In this reasoning, strongly interacting residues are close to each other and can transmit an information using a conformational change [60]. Similar to previous

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studies on representing proteins as small world networks to investigate their structural features

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[64, 65], revealing shortest pathways between distant residues [60, 66] or adjusting forces between interacting residues [56], the local interaction strength or the affinity aij between a coarse-grained node pair (i,j) is set as,

a ij 

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(1)

N i .N j

Nij for a node pair (i,j) is the total number of heavy atom-atom neighboring of the corresponding residues within a cutoff distance of 4.5 Å. Here, a perturbation from one site is expected to propagate through non-bonded interactions of residues such as hydrogen bonding

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and van der Waals, occurring below 5 Å [65]. Nij is then weighted by Ni and Nj, which are the number of heavy atoms of residues i and j, in order to avoid any bias due to size of residues. Accordingly, nodes having higher interaction strength can be assumed closer in the graph. However, bonded nodes have higher local interaction strength values as compared to close non-bonded neighbors. Here, the inverse of the affinity of nodes, aij-1, provides a relative

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measure for the length of their edges linking them, while eliminating the extreme bias towards

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bonded interactions in the shortest pathways calculations, in which long-range interactions are

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also considered.

Such a coarse-grained description of the bacterial ribosome structure enables the calculation

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of alternative shortest pathways between two sites of the protein complex, using the k-shortest pathway algorithm introduced by Yen [51], executing O(N) times Dijkstra’s algorithm [67],

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where N is the number of nodes. Dijkstra’s algorithm is an efficient tool to calculate the shortest pathway problem by spanning all vertices reachable from a single node in the graph.

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Yen’s algorithm ranks the k-shortest pathways between two nodes without repeated nodes. In

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this study, the in-house code delivers different k-shortest pathways that may use same nodes resulting into similar pathways. Information gained from all calculations is used to identify

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which residues are frequently visited in all calculated pathways, as well as to explore diverse pathways between two functional sites. The length of each path is obtained by consecutively

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summing pairwise distances aij-1 between ith and jth residues following along the pathway.

An optimum number of k=20 shortest pathways is employed between distant ribosomal sites, namely ribosomal tunnel, and DC and PTC, three functional sites critical for the translation process (see Supplementary Information, Figs. S1-S3). Twenty shortest pathways are consistently calculated for each destination in each ribosome structure given in Table 1.

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2.3. Elastic network model Collective functional motions of the ribosome complex realizing in low-frequencies, such as the ratchet-like rotation of two subunits, can be obtained by the elastic network model using normal mode analysis [56, 57, 59]. Native structure of the complex containing N residues is described as an elastic network of N nodes linked by springs. Here, nodes can be placed at the

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center of mass of residues. Magnitude of the spring constants between (i,j) node-pairs γij can

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be adjusted based on their total atom-atom neighboring within a cutoff distance Rcut of 10 Å

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[56]. In order to obtain the coupled motions of the nodes in three-dimension, anisotropic network model [68] is employed where the total potential energy V of the elastic network is

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i, j

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V 

( Rij  Rij0 ) 2

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Rcut

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defined as a summation of harmonic interactions of all (i,j) pairs by,

(2)

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Here, Rij and Rij0 are the instantaneous and equilibrium distances between ith and jth nodes (1≤

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i, j ≤ N). The diagonilization of the Hessian matrix, with elements being the second derivative of the total potential energy with respect to mass-weighted coordinates of ith and jth nodes,

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leads to the calculation of 3N normal modes of the protein complex. 3N-6 vibrational modes provide the magnitude and direction of harmonic fluctuations of residues. Six normal modes

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with zero eigenvalues correspond to rotational and translational motions of the structure in three-dimension. When the protein complex in its functional oligomeric state is investigated with normal mode analysis, low-frequency modes with high residue collectivity provide functionally relevant motions of the structure [69]. Calculation of the vibrational modes for the intact bacterial ribosome requires the diagonalization of the Hessian, which is a computationally daunting task for this supramolecule composed of more than 104 residues. Here, the computationally efficient BLZPACK software [70] using the block Lanczos

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algorithm [71] enables to diagonalize the Hessian matrix and to calculate vibrational modes of the ribosome complex in various translation states. First ten low-frequency modes of the ribosomal structures are calculated, which is conventional for the normal mode analysis of this complex [57-59]. These collective motions correspond to the ratchet-like rotation of small and large subunits, head rotation of the small subunit, anti-correlated motions of L1 and

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L7/L12 stalks, translational motion of tRNAs and mRNA. These modes have the highest

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contribution to residue fluctuations in ribosome structure.

Residue cross-correlations averaged over l lowest-frequency modes, especially for the shortest

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 R i (l )  R j (l ) 1  1   1   k  (l )  k R i (l ) R j (l )  (l ) 

(3)

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Cij 

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path residues, are calculated by,

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Here, ΔR(l) is the displacement vector of residues i and j at lth normal mode with a corresponding eigenvalue λ(l). Cross-correlations are normalized with the norms of

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displacement vectors in order to obtain values between -1 and 1, which respectively points to

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anti-correlated and fully-correlated motions of residue pairs.

Deformation analysis is a measure of determining the intrinsic flexibility of a protein, which can be composed of rigid domains connected by flexible domains [72]. Here, deformation energy is calculated to assess the dynamic nature of the residues forming the calculated shortest pathways. Mapping calculated shortest pathways among dynamic domains can help interpreting how each residue or structural component can contribute to the signal

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transmission between two sites. Deformation energy on each residue in a low-frequency mode l is calculated as [57, 72] ,

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Di (l )   i, j

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R 2

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 R j (l )  Ri (l )  Rij0



2

1 N (l )

(4)

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where, ΔRi and ΔRj are the fluctuations of residues i and j in mode l. Rigid domains can be

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recognized with small local deformations of residues with respect to their neighbors in lowfrequency modes, therefore small values of Di(l). A highly flexible region may be identified

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with its high deformation values. The overall deformation energy of residue i, 𝐷𝑖 , induced by

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first l modes of motion is calculated by summing Di(l) values. Then, the cooperativity of consecutive shortest path residues to transmit a signal between functional sites over the first

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ten slowest modes is analyzed.

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Mean-squared distance fluctuation <ΔRij2> between residue pair (i,j) calculated as,

(5)

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R ij2  R i2  R 2j  2 R i .R j

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and averaged over the first ten normal modes, is used as a measure to reveal residues with high potential of communication during the functional dynamics of the ribosome complex. Accordingly, a low value of <ΔRij2> points to a residue pair with a low ‘commute time’ and a good ability to transmit/receive a signal to/from each other, as was elegantly formulated for discrete-time, discrete-state Markov process of information transfer in protein structures [60].

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3. Results and Discussion 3.1. Potential pathways between the ribosomal tunnel and peptidyl transferase center The narrowest part of the ribosomal tunnel guarded by the highly conserved β-hairpin of ribosomal protein L22 and L4 (Fig. 1), discriminates specific nascent chains and stalls

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elongation process by signaling in the direction of PTC [73]. An allosteric link was proposed between the peptide sensor A2062 and nucleotides A2451 and C2452 at the A-site crevice of

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PTC to stall the protein synthesis. Here, nucleotides A2503, G2061, U2504 help the

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communication of these two distant sites [19].

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In order to determine if this apparent sequence of interacting residues is defined by the contact topology of this region, we calculated twenty shortest pathways between the ribosomal tunnel

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(A2062 on 23S rRNA) and PTC A-site crevice (A2451) on each crystal structure in the dataset. The combined analysis of residue frequency distribution on eighty shortest pathways

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(i.e. four crystal structures with twenty pathways), between A2062 and A2451 are shown by

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color-coding the residues from high to low frequency in Fig. 2 (and given separately for each crystal structure in Fig. S4). Major pathways, here defined as the sequence of high frequency

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residues, can be easily recognized within the other shortest pathways. Accordingly, a major pathway sourcing from the highly flexible A2062 on the tunnel follows residues G2061,

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C2063, C2064, C2501 and A2450 on 23S to finally reach the A-site of PTC. Majority of these residues also forms the shortest pathways in different translation states, as shown in Table S1. Length of the pathways, which are the summation of distances between consecutive residues, are indicated in Table S1. Close values of the lengths for different translation states imply no significant conformational changes between the ribosomal crystal structures. Indeed, backbone root mean-square deviation (RMSD) of this relatively small area on the complex is calculated as ~0.3 Å when considering four ribosome structures. RMSD value increases to 0.7

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Å for all heavy atoms, where the major source of deviation is the side chain motions of the flexibile nucleotide A2062.

Fig. 2. Residues of eighty shortest pathways from A2062 to A2451. Residues are colored according to their relative frequencies from red (high frequency) to blue (low frequency), by

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excluding A2062 and A2451 appearing in all paths. High and low frequency residues form the major and minor pathways, respectively. The location of pathways is indicated on the 50S

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subunit shown in the bottom.

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Most importantly, our calculations agree with the previously proposed allosteric pathway [18, 19]. Here, the nucleotide G2061 bears a major role in allosteric communication, while

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residues A2503 and U2504 provide an alternative short pathway between the tunnel and PTC (Figs. 2, S4). It is not surprising to observe the shortest pathway as A2062 → C2063 →

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C2064 → A2450 → A2451 for all investigated structures since the universally conserved

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non-Watson-Crick base-pair at A2450-C2063 exists in this particular area [74]. An extensive mutational and MD simulation study focusing on the A2450-C2063 wobble base-pair showed

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its impact on the flexibility of A2062 [75]. Our results propose that the local density of the residues in the tunnel area lays a basis for an effective communication. Dynamics of these

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residues during functional motions support this idea, as will be discussed in Section 3.3. Motivated by the success of this graph model, we decided to employ this approach for investigating potential shortest routes between highly distant functional sites of the ribosome to get insights into their communication means during the translation process.

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3.2. Potential pathways between decoding center and peptidyl transferase center Although DC and PTC are physically distant in the ribosomal complex, they are highly coordinated for careful translation of the genetic code [9, 10, 13, 76]. Therefore, exploring the shortest pathways between these two active centers can shed light into the translation mechanism. After the recruitment of the cognate tRNA to the complex, peptide bond

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synthesis between amino acids located at the CCA ends of A- and P-tRNAs is catalyzed by

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PTC. The cavity of PTC mediates only rRNA residues, which are highly conserved and have

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critical functional activities. Two of these are A2451 and G2251, which respectively interact with A-tRNA and P-tRNA [77, 78]. A2451 located at the A-loop, is very close to the amino

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group of A-tRNA, and 2’-OH of A2451 is required for peptide bond formation [78, 79] as well as it stabilizes P-tRNA conformation for an efficient peptidyl transferase activity [61].

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Consequently, A2451 in PTC A-site is selected as the sink node in our shortest pathways calculations.

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Twenty shortest pathways sourcing from nucleotide A1492 (DC) and progressing down to A2451 are calculated for the dataset and summarized in Fig. 3 (for details, refer to Table S1,

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Fig. S1, Fig. S2 and Fig. S5). In following sections, we will discuss the main observations.

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Fig. 3. Shortest pathways between DC and PTC at different translation states. (A) Shortest pathways from A1492 (DC) to A2451 (PTC A-site) span common/different structural elements in different translation states. (B) In the box, structural elements forming all calculated pathways displayed in (A) are shown together. In the lower panel, residues are colored based on their relative frequencies in a total of eighty shortest pathways, where red to blue points to decreasing frequency.

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3.2.1. Common and alternative shortest pathways at different translation states

For a transmission of information from DC to PTC A-site crevice, we determined shortest pathways with similar lengths but traveling rather different routes and crossing different intersubunit bridges for different translation states studied. When considering all rRNA residues

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forming these paths, RMSD between crystal structures with PDB IDs 2wdk-2wdl, 2j00-2j01, 3f1e-3f1f and 4juw-4jux, is in the range of 0.7-1.8 Å based on all atoms, and 0.5-1.7 Å based

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on backbone phosphorus atoms. Structural deviations mostly originate from flexible residues

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A1492, A1493 on 16S rRNA, A2602, U2506 and H69 region on 23S rRNA. All tRNAs and

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RF2 are excluded from RMSD calculations since they lack in several crystal structures.

We discuss our results according to the general sequence in the translation process: pre-

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translocation, translocation and pre-peptidyl transfer states forming the outline of the

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elongation phase, and finally the termination state.

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At the pre-translocation state (PDB ID: 2j00-2j01), we calculated two alternative potential pathways between the DC and A-site of the PTC (Fig. 3A). In Fig. S5A, frequency distributions of residues over twenty shortest paths are displayed. The lengths of the pathways

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are very close for this structure as well as for the other structures (Fig. S2). This finding points

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that the contact topology of the ribosome can set multiple routes between two regions, tracing residues with similar local densities. Interestingly, the shortest pathway follows a small patch of mRNA and then the anti-codon stem loop, elbow and CCA end of P-tRNA to reach A2451 on PTC (Table S1). This path exists in ~40% of twenty shortest paths (Fig. S5A), which indicates a possible role of P-tRNA for communication of DC and PTC. This finding will be further discussed in the light of functional dynamics of the ribosome in Section 3.3. An alternative short pathway continues over the stable inter-subunit bridge B3, an RNA-RNA interface between 30S and 50S. This pathway is observed in ~60% of twenty paths. The inter-

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subunit bridge B3 at the center of the complex is highly conserved in three domains of life [80] and indispensable for subunit association stability [81]. This bridge was suggested to be the pivot point for ratchet-like rotation of subunits since it is highly stable during this motion [82, 83], and its intactness on h44 has impact on fidelity of initial codon selection [84]. Another significant finding is the highly conserved and flexible U2506 that is frequently

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appearing in the short pathways. U2506 is critical in peptide bond synthesis [85] and is a drug

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binding nucleotide [86].

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In the presence of EF-G and tRNA in its hybrid state P/E (PDB ID: 4juw-4jux), twenty shortest pathways cluster on one major path passing from the large interface of the inter-

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subunit bridge B3 (Fig. 3A), quitting the route over tRNA that is now in its hybrid state. In

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this translocation structure, U2506 is still visited in all twenty shortest paths (Fig. S5B). Then, at the pre-peptidyl transfer state with A-, P- and E-tRNAs (PDB ID: 2wdk-2wdl), this

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pathway is still frequently visited, with other structural components coming into the picture,

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such as CCA ends of A- and P-tRNAs, and A2602 being an important residue at the PTC (Fig. S5C). Flexible A2602 is a drug binding site [87] and it is known to have a role in nascent polypeptide release during termination of translation with its direct effect on

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hydrolysis [88, 89].

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For the elongation phase structures, shortest pathways highlight the inter-subunit bridge B3 as an important location that merits further examination for the ribosome allostery. Another critical region, namely U2552-U2554 located on the A-loop of PTC, is consistently noticed, where highly conserved nucleotide G2553 makes Watson-Crick base-pair with the CCA end of A-tRNA [90]. Depicting these flexible residues i.e. U2506, A2602 and G2553, along the shortest pathways especially for the elongation phase structures is very intriguing; these are critical in either peptide bond synthesis or nascent peptide release. Inherent conformations of

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the ribosome structure during protein synthesis modulate the contact topology such that it offers shortest routes between distant active sites especially passing from residues critical in the related translation state.

This latter observation is also valid for the translation termination state accommodating

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release factor RF2, mRNA, P- and E-tRNAs (PDB ID: 3f1e-3f1f). Major signaling pathway traces over the bridge B2a, a central inter-subunit bridge important for ribosome stability like

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B3 [81], then over Helix 69 (H69) and P-tRNA to finally reach the nucleotide A2451 (Fig.

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3A, Fig. S5D). This path is visited in 90% of twenty shortest pathways. The inter-subunit bridge B2a, involving a RNA-RNA interface like B3, is next to the functional site DC of the

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ribosome complex. This bridge is quite stable during the translocation process in contrast to

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protein-RNA bridges at the periphery undergoing large conformational changes, as cryoelectron studies indicate [91]. Neighboring position of B2a to the A-tRNA led to the

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suggestion that H69 of the large subunit is involved in transmitting the signal of correct

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codon-anticodon pairing to the large subunit [92, 93]. Another frequently visited residue is A1913 of B2a on 23S. Mutation studies showed the critical role of A1913 in tRNA selection process [76], and MD simulations indicated that nucleotides A1912 and A1919, next to the

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calculated signaling paths, are important for a hydrogen-bonding network that brings h44 and

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H69 together [94]. Another role of H69 emerged during translation termination assisted by RFs [63], while its deletion with A1913 resulted in defective polypeptide release by RF1 [95]. Inter-subunit bridge B2a, H69 and A1913 are clearly indispensable for the translation, and the contact topology interestingly points in their direction for their role in allosteric communication to terminate the translation. On the other hand, for the termination state, a less frequently visited alternative short path from DC is composed of the bridge B3, 23S rRNA, RF2, and CCA end of P-tRNA (Figs. 3A, S5D). Length of this alternative route is found close to that of the major path, indicating its

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plausibility besides the shortest pathway (Fig. S1, Fig. S2). RF2 is a critical protein for the hydrolysis of the peptidyl-tRNA ester bond for polypeptide release when the stop codon reaches the A-site on 30S. The mechanism of coupling between stop codon recognition and peptidyl-tRNA hydrolysis has been debated [63]. According to the biochemical and genetic studies on crystal structure ribosome-bound RF2 complexes, RF2 includes distinct domains

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interacting with both DC and PTC [96-98]. Especially domain 3 with the conserved GGQ

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motif (Gly251–Gln253 in Thermus thermophilus, Gly250–Gln252 in Escherichia coli),

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penetrated into the PTC plays an important role in hydrolysis by contacting 23S rRNA and PtRNA [63, 98]. Accordingly, our calculations show that domain 3 residues next to the GGQ

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motif, namely Thr274-Arg279 (Gln273-Arg278 in Escherichia coli), Asn284 (Asn283 in Escherichia coli) linking the inter-subunit bridge B3 and A-site of PTC, provide an alternative

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shortest path sourcing from DC and reaching PTC. This observation agrees with previously suggested role of the RF2 on the mechanism for coordination of stop codon recognition and

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peptidyl-tRNA hydrolysis [63].

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Conservation analysis of the bacterial rRNA [99] indicates that 94% of rRNA residues along shortest pathways from DC to A-site of PTC are highly conserved (i.e. > 90% conservation)

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(Fig. S5). From RF2 residues appearing along the paths, Asn284 (Asn283 in Escherichia coli)

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is fully conserved and Arg279 (Arg278 in Escherichia coli) is strongly conserved, based on a conservation analysis of RF2 structure over 13 different types of bacteria using ClustalW Omega at EMBL-EBI (names of species given in Table S2) [100, 101]. At this point, it is worth mentioning that various experimental and computational studies such as [31, 35, 46, 52] recognize the importance of conserved residues to transmit an allosteric information from one functional site to another.

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Fig. 3B summarizes all our results for the shortest pathways between DC and PTC. Four distinct shortest pathways between DC and PTC A-site with similar path lengths are observed for different translational states. For the elongation phase, pathways comprise (1) B3, U2552U2554, U2506, A2602 or (2) P-tRNA; for the termination phase, pathways continue through (3) B2a, H69 of 23S rRNA and P-tRNA or (4) B3 and RF2. Our calculations consistently

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show that different conformations of the ribosomal complex adopted at distinct translation

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states switch between pre-existing shortest pathways formed of regions specifically important

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for the related state.

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3.2.2. Major pathways between decoding center and peptidyl transferase center We evaluated all calculated shortest paths between DC and PTC (eighty in total) to reveal

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more frequently visited residues that would form major pathways on the contact topology of the bacterial ribosome. Over eighty different pathways, relative frequencies of all residues are

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color-coded in the lower panel of Fig. 3B. Major pathway crosses critical helix 44, the inter-

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subunit bridge B3 and residues on the A-loop of PTC, namely U2552-U2554. Then, it continues on PTC residues U2506, C2507, C2452 and finally reaches A2451. The inter-

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termination state.

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subunit bridge B2a and RF2 have lower frequencies as they specifically appear in translation

On the other hand, our calculations are highly similar for shortest pathways between DC and P-site of PTC, namely for residue G2251 interacting with P-tRNA, showing that a signal sourcing from DC may reach both A- and P-crevice of PTC through the same paths (results not shown).

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3.3. Implications of functional motions in allosteric signal transmission Shortest pathways drawn by the contact topology of the bacterial ribosome clearly capture many critical residues and regions for the translation process. For a better assessment of the plausibility of the proposed shortest pathways for the communication of tunnel and PTC, and DC and PTC, we analyzed ribosome dynamics at the low-frequency spectrum.

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As mentioned earlier, a perturbation on an allosteric site, for example due to a binding event

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of a ligand, may be transmitted to a distant site via correlated fluctuations of residues using

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bonded and non-bonded interactions. In this line, we obtained normal mode deformations of the intact ribosomal structures at low-frequencies, involving intrinsic functional motions of

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the complex. For ten slowest modes obtained with ANM calculations, we first calculated orientational cross-correlations for each consecutive residue-pair along a shortest pathway.

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Then, we averaged cross-correlations over ten slowest modes using Eq. 3. Limits of normalized cross-correlations are -1 and 1, indicating fully anti-correlated and correlated

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fluctuations of residue-pairs, respectively. For the shortest pathways between DC-PTC and

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tunnel-PTC, cross-correlations between neighboring residues are in the range of 0.80-0.99, considering all investigated structures. Correlated motions of pathway residues during global

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motions can support a signal transmission between distant functional sites of ribosome.

Then, we calculated deformation energies of residues averaged over first ten normal modes using Eq. 4. In Fig. 4A, deformation energy values of residues are color-coded on the pretranslocation state structure to distinguish between rigid domains (blueish) separated by flexible domains (reddish). Deformation energy distributions for the other structures are given in Supplementary Figs. S6-S8. Rigid domains indicate group of residues moving in the same direction during the collective motions, which are coordinated by flexible domains. In a rigid domain motion, deformation energies of residues are low whereas they are high in flexible

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regions. Low frequency motions of the ribosome complex, e.g. the ratchet-like rotation of the two subunits, small subunit head rotation, high amplitude motions of stalks [57, 59] determine the dynamic domains on the ribosome structure. Accordingly, 30S and 50S become two basic dynamic domains, which accommodate other dynamic sub-domains, such as the head of the small subunit and L1 stalk of large subunit. The interface between small and large subunits,

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including the tRNAs, forms the flexible domain. Another flexible domain is linking L1 stalk

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to the large subunit.

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Fig. 4. Dynamic behaviors of residues on calculated shortest pathways. (A) Deformation energy distribution on small (30S) and large (50S) subunits of the structure with PDB ID: 2j00-2j01. Red to blue indicates a decrease in deformation energy of residues. Residues forming the twenty shortest pathways between (B) DC (A1492) and PTC (A2451), (C) tunnel (A2062) and PTC (A2451) are colored as in (A). mRNA (green), P-tRNA (orange), 16S (blue), 23S (grey) are explicitly indicated. <ΔRij2> values for all residues in twenty shortest paths between (D) DC and PTC, (E) tunnel and PTC are displayed on a heat map. Dark blue (dark red) represents lowest (highest) <ΔRij2> values. Black (yellow) squares indicate residuepairs on the shortest (alternative shortest) pathway. Black stars point to inter-subunit bridge B3 residues.

In Fig. 4B, we further focus on deformation energies of residues on the shortest and

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alternative shortest pathways between DC and PTC. Path residues are color-coded from high (red) to low (blue) deformation energy taking the intact structure as basis, shown in Fig. 4A.

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The remaining parts of the structure are hidden for clarity. Interestingly at the pretranslocation state, P-tRNA forms the shortest pathway between DC and PTC, and has a high deformation energy especially concentrated on its elbow region due to its inter-structural movements. The alternative pathway accommodating the B3 inter-subunit bridge has lower deformation energy values as compared with the shortest route. While the dynamic nature of the residues on these pathways are different, i.e. flexible or rigid, both pathways seem plausible for allosteric propagation of a perturbation in DC to the distant PTC. P-tRNA

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positioned as a flexible linker between two major dynamic domains, 30S and 50S, can transmit a force generated at DC to PTC through its inherent conformational changes during the translocation, as was previously proposed for allosteric multi-domain proteins [102]. On the other hand, the inter-subunit bridge B3 path, which is consistently observed in other structures at different translation states, is located both on flexible and rigid domains of the

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complex (Supplementary Figs. S6-S8). Conformational flexibility of DC and neighboring

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regions in 16S is apparent in low-frequency motions of the complex. Effects of

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conformational rearrangements in the small subunit can propagate through the bridge B3 and can be transmitted through the correlated motions of residues of 50S to reach the PTC region.

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The contact topology of the termination state suggests a major path crossing over B2a and PtRNA and an alternative path crossing over the B3 bridge, RF2 and P-tRNA. Both pathways

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accommodate residues with low deformation energies, making these pathways convenient for allosteric communication. In summary, even though functional sites DC and PTC are

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significantly distant from each other, inherent flexibility of the complex and correlated low-

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frequency motions can facilitate their long-range communication.

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Mean-squared fluctuations of distances between residue-pairs in the functional motions of the ribosome can provide an important measure to reveal residues with high potential of

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communication. In Fig. 4D, <ΔRij2> values, rescaled between 0 and 1, are plotted for all residues in twenty shortest paths between DC and PTC for the structure with PDB ID: 2j002j01. Here, values are colored from blue to red, representing an increasing trend in values. Black (yellow) squares indicate values for consecutive residues on the shortest (alternative shortest) pathway. During the functional motions of the ribosome complex, residues both on shortest and alternative pathways remain close to each other (i.e. small <ΔRij2> values), pointing to their short commute times, i.e. their ability to quickly establish communication to

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transmit an information. These calculations are repeated for the other structures at different translation states leading to similar results (see Figs. S6-S8). Finally, we analyzed the low-frequency motions in the narrow gate of the ribosomal tunnel. Entrance of the tunnel from the PTC site is embedded in the large subunit, therefore residues exhibit low deformation energy values in the low-frequency motions in all investigated

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translation states (Fig. 4C and Supplementary Figs. S6C, S7C, S8C). Mean-squared

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fluctuations of distances between consecutive residues of the shortest pathways are very low

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as well (Fig. 4E and Supplementary Figs. S6E, S7E, S8E). These results suggest that a perturbation at the flexible A2062 occurring at any translational state, can be transmitted to

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PTC 10 Å away via few neighboring residues with low commute times.

4. Conclusions

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We employed two complementary structure-based methods, graph and elastic network

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models, to reveal the role of the bacterial ribosome contact topology in allosteric communication of active sites during protein synthesis, for the first time to our knowledge.

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Indeed, contact topology of different translation states lead to potential short pathways mapping residues and regions, specifically critical in allosteric regulation for the related

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translation state. Moreover, residues forming the shortest pathways are highly correlated to transmit a perturbation in long-ranges and have the ability to quickly communicate with their neighbors.

Our results also indicate that at different translational states where the contact topology changes, alternative shortest pathways may emerge to transmit an information between functional regions. Nonetheless, there exist frequently visited critical residues or regions

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shared by all major and minor pathways. For example, acceptor arm P-tRNA and the intersubunit bridge B3 (Fig. 3) stand out at the intersection of shortest pathways sourcing from the DC down to the PTC. For the ribosomal tunnel entrance, one major pathway seem to dominate and this region is a well-known antibiotic target [5].

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Highly conserved rRNA and ribosomal protein residues constitute ~90% of shortest pathways

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residues. An important portion of these residues is known antibiotic targets, clustered around

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DC, PTC and the ribosomal tunnel entrance. Enormous size of the ribosomal complex assumes a large number of potential drug binding sites for stopping protein synthesis in

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bacteria. An extensive effort has been devoted for predicting new drug binding sites, such as by hierarchical screening strategies, constructing rRNA mutation libraries, mapping

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deleterious mutations and searching for drug binding motifs in the ribosomal structure [103107]. Potential pathways drawn by our topology-based approach (Figs. 2, 3), pin known

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antibiotic binding sites and point to potential druggable sites. For example, central inter-

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subunit bridges B2a and B3 seem to bear a critical role in allosteric signaling, and these are clearly attractive sites for antibiotics to block distant communication, therefore to stop protein

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synthesis. Indeed, several antibiotics targets the intersubunit bridge B2a and its neighboring regions [108-110]. Considering the role of B3 in ratchet-like motion [82, 83] and observing

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this bridge consistently in different shortest pathways from DC to other functional sites, the entire interface of the intersubunit bridge B3 presents an attractive target site for designing new antibiotics.

Although we selected few number of destination residues for the shortest pathways, this experiment can be easily extended to different functional residues of critical regions for translation. Nonetheless, our force field free and computationally efficient approach

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successfully maps a significant amount of allosteric residues as discussed throughout this study, and provides interesting and testable observations to elucidate the role of structural elements of the nano-machine in order to control its sophisticated allosteric mechanisms.

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Acknowledgements

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The in-house code used to calculate k-shortest pathways in this study was developed by Serhat

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Sarikavak in Istanbul Technical University, Department of Chemical Engineering. OK thanks Zeynep Kurkcuoglu for her useful comments on this work. This work was supported by

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Istanbul Technical University, Scientific Research Projects Foundation [Project No: 36110].

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Highlights

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Distant functional sites of bacterial ribosome use allostery to communicate. Potential pathways between three sites are calculated based on the contact topology. Calculated shortest pathways captures known allosteric residues. Alternative short pathways are detected for different translation states. Intersubunit bridges B3 & B2a distinguish as potential allosteric druggable sites.

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