ribosome builder: a software project to simulate the ribosome

Computational Biology and Chemistry 29 (2005) 163–174

Ribosome Builder: A software project to simulate the ribosome

William Knight, Walter Hill, J. Stephen Lodmell∗

Division of Biological Sciences, The University of Montana, Science Complex Room 202, Missoula, MT 59812, USA

Accepted 28 January 2005

Abstract

The Ribosome Builder is a software project that provides tools and techniques to create dynamic models of macromolecular systems from therapidly growing numbers of atomic structural models. It includes a computer program that allows the user to assemble the multiple molecularcomponents within a 3D space and to define the hypothetical interactions of these components with the initial goal of understanding proteintranslation at an atomic level of detail. The program employs a simplified molecular dynamics forcefield that can simulate the long time-scaleevents, such as docking of translation factors and mRNA translocation. An embedded scripting language and Application ProgrammingInterface (API) enable the creation of Steered Molecular Dynamics (SMD) simulations through the programmable application of externalforces and torques on atoms and bonds. A graphical interface is provided for displaying and interacting with models, recording movies ofm the projecti longationc©

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olecular dynamics movements, and creating annotated 3D simulations of complex macromolecular events. Initial applications ofnclude simulation of tetraloop folding, docking of an mRNA on the 30S subunit and a schematic simulation of the translation eycle. The program is an open source project released under the GNU public license.2005 Elsevier Ltd. All rights reserved.

eywords:Ribosomal translation; RNA; Steered molecular dynamics; Macromolecular simulation; Ribosome modeling

. Introduction

.1. From structure to dynamics

After many decades of research, recent atomic resolutionodels of the ribosome have given us vivid images of the

ranslational machinery (Ban et al., 2000; Schluenzen et al.,000; Wimberly et al., 2000). This wealth of new structuralata has also illuminated our understanding of other RNAolecules. While new static structural models of the ribo-

ome continue to emerge, one challenge that lies ahead is tose these data to develop a comprehensive dynamic modelf the translation process. The successful creation of a dy-amic model of the ribosome would have several importantenefits. The results and the methods used to produce themould be applied to modeling other complex biomolecularystems (Aloy et al., 2004), design of artificial nucleic acidachines (Liao and Seeman, 2004) and evaluation of RNAorld hypotheses (Taylor, 2004).

∗ Corresponding author. Tel.: +1 406 243 6393; fax: +1 406 243 4304.

A primary obstacle to the creation of such dynamic mels is the tremendous difficulty of simulating the molecdynamics of large structures. Ideally, one would like toable to simply submit a structural model of some molecmachine to the computer and obtain an accurate ‘moviits activity. However, the complexity of atomic interactiothe small timescales and the large number of possibleformations of biomolecules currently make this ideal larginfeasible.

Current molecular dynamics programs have madeprogress in accuracy and performance in recent years. Ssizes of 104 to 106 atoms are possible and time intervalsoften in the 10–100 ns range (Hansson et al., 2002; Karpland McCammon, 2002). However, this performance still fashort of what is needed to simulate many important mamolecular processes such as docking, folding and otherconformational changes that can span the millisecondscales.

A number of techniques have been used to enhancability of molecular dynamics to simulate these longer tiscale processes, including Targeted Molecular Dyna(TMD) (Ferrara et al., 2000), Steered Molecular Dynami
E-mail address:[email protected] (J.S. Lodmell).
476-9271/$ – see front matter © 2005 Elsevier Ltd. All rights reserved.oi:10.1016/j.compbiolchem.2005.01.001

164 W. Knight et al. / Computational Biology and Chemistry 29 (2005) 163–174

(SMD) (Izrailev et al., 1998) and Interactive Molecular Dy-namics (IMD) (Grayson et al., 2003). These techniques typ-ically apply constraints, such as external forces to drive thesimulated system in a desired direction.

In simulations of nucleic acid molecules, informationabout secondary structure and tertiary motifs can be used todefine such constraints. External forces derived from base-pairing and base-stacking constraints were used to simulatethe folding of the anticodon stem loop of a tRNA from an A-form conformation to the folded state (Harvey et al., 2003).This long time-scale process was simulated in a relativelyshort amount of real-time computation.

Another example of external constraints is the use of twodifferent structural models of a molecule in different func-tional states. An SMD simulation can be performed in whichexternal forces and torques are used to drive the moleculefrom one conformation to the other. The resulting simulationwill produce a movement that may be a characteristic of theactual activity of the molecule.

The Ribosome Builder software program makes exten-sive use of steered molecular dynamics methods to simu-late movements of RNA and protein components. The pro-gram includes a powerful scripting language and associatedlibrary of functions that are used to define external forcesand torques. These external constraints are applied to modelsin a simplified forcefield. The forcefield has been designedp clu-s nfor-m con-j ients calea

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ap-p r isp s ofa reseno user.T er ofd ad-i on ofd ove-m tiona vieso

imu-l wo-d d in

a journal article) and a complete three-dimensional molec-ular dynamics simulation of the entire process. There areseveral advantages to this approach. First, the descriptionof macromolecular structures and processes in conventionalprint media is inherently awkward and incomplete. A statictwo-dimensional image can only show a single view of athree-dimensional structure. Very often, it is not possible toadequately observe and identify the partially occluded ele-ments, especially in representations of large complex struc-tures. In addition, dynamic movements can not be explicitlyrepresented. Therefore, one purpose of a schematic simu-lation is to act as a scientific description similar to a con-ventional journal article, but using the medium of animatedthree-dimensional graphics.

A second purpose of the schematic simulation is to act as astarting point for the development of a fully complete modelof some process. It is typical for a scientific model to evolveover time from an uncertain and incomplete state to a moredetailed and well-supported one. To model a complex activ-ity such as protein translation, a schematic simulation mayemploy low-resolution atomic models with uncertain posi-tions, higher resolution atomic models with unresolved parts,a heterogeneous mix of molecules from different species anda simplified set of movements that symbolize the actual pro-gression of atoms through time and space.

An important consequence of creating schematic simula-t defi-n o-n sultsi , thisf rvest . Ana e de-v jectb en bei ens,p pleteo ctuali st befi

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rimarily to maintain bond lengths, bond angles, steric exion and hydrogen bonding. Precise calculation of the coational energy is not made. These simplifications, in

unction with the external driving forces, enable the efficimulation of large molecular models and long time-sctivity.

.2. Schematic simulations

As detailed models of macromolecular systems areeloped, the models will typically include multiple compents that undergo sequential interactions and conformahanges. A new challenge emerges in how to effectivelyesent, investigate, describe and communicate the conthese complex models.

Annotated 3D schematic simulations represent oneroach to this challenge for which the Ribosome Buildearticularly well suited. A schematic simulation consistscripted sequence of events that are intended to rep

ne or more complex macromolecular processes to thehe content of such a simulation draws upon a numbifferent capabilities from the main program, including lo

ng and display of static and dynamic models, presentatiescriptive text and graphical annotations, coordinated ment of the three-dimensional viewpoint, scripted transland rotation of objects, and playback of pre-recorded mof molecular dynamic simulations.

The term ‘schematic’ is used because this type of sation is intended to fill a gap between a conventional timensional description of events (as typically presente

t

ions of macromolecular systems is that it motivates theition of preliminary models for most of the principal compents and interactions at an atomic level in detail. This re

n an explicit, observable and detailed hypothesis. In turnacilitates critical evaluation of the hypothesis, which seo identify missing, or incorrect components and statesnalogy can be made to a situation that occurs in softwarelopment. Often, the design of a complex software proegins as a set of general specifications, which must th

mplemented explicitly in source code. When this happarts of the general specifications that are vague, incomr ambiguous will be glaringly revealed because the a

mplementation requires that such unspecified parts mulled in before the work can proceed (Spolsky, 2004).

Finally, the components and the interaction sequencere created for a schematic simulation can often becomeusable resources for the creation of alternative hypotnd simulations. Over time, a powerful toolbox of predefiomponents can grow. Collections of such componentsypically be encapsulated into larger modules and resuew building blocks that can be used to model the procet higher levels of abstraction.

. Program capabilities

.1. System overview

An overview of the input, tools and output of the progrs shown inFig. 1. The program can be used in conjunct

W. Knight et al. / Computational Biology and Chemistry 29 (2005) 163–174 165

Fig. 1. Block diagram of the Ribosome Builder system.

with a web browser, as discussed in more detail below. Theprimary input data consist of atomic structural models in theform of PDB files from the Protein Data Bank (Berman etal., 2000). A number of ribosome-related PDB files are dis-tributed with the program. The third input component consistsof user-defined script files, which are used to automate andcustomize the behavior of the program.

The 3D graphical user interface and simplified forcefieldare the built-in components of the main program. The resultsof working with the program include new static structuralmodels that have been produced from the changes in the inputmodels. Molecular dynamics trajectories can also be outputas movie files, for subsequent playback. Both static modelsand movies are then typically incorporated as components,along with scripting code, to produce a schematic simulationwhich can be viewed in the 3D graphics window.

2.2. Graphical user interface

The central activity of the Ribosome Builder program isto load and arrange multiple molecular structural models in3D space and to construct and run SMD simulations. Thegraphical interface provides a diversity of input controls andvisual feedback to support this modeling activity.Fig. 2 is ascreenshot of the main window that shows some of the prin-c ow,P

tiona view-p oarda ualp ectsi , andt the

object hierarchy (and at the atom level for dynamic models).The current selection is also reflected in the PDB hierarchywindow.

The graphical representations of models include displayof spacefilling atoms, covalent bonds, chain backbones andsurface meshes in CPK or user-defined colors. Varying levelsof transparency are possible for the surface representations.After the positions and appearances of models have beendefined by the user, that configuration can be saved to a fileand restored at a later time, which is useful when workingwith multiple models and configurations.

2.3. HTML browser integration

The program is designed to work in conjunction with anHTML browser such as Mozilla Firefox. As a standaloneapplication, the Ribosome Builder program can support 3Dgraphical operations more easily and flexibly than a third-party HTML browser. However, the browser offers a powerfulsupplement to the 3D graphical environment.

Modern browsers are highly optimized to displaymultiple-tabbed 2D windows of hyperlinked text, tabular dataand graphics in a universal open standard. Furthermore, thebasics of HTML are simple enough so that many users cancreate small, organizational HTML documents. These doc-u 3Dg tinga eada

nalH n ah fromt ulars iated

ipal UI components: menus, toolbars, 3D graphics windDB hierarchy window and status window.In the graphics window, the mouse and keyboard func

s navigation controls to rotate and translate the user’soint to any location in the 3D space. The same keybnd mouse controls function in a similar way for the manositioning of PDB models in the simulation space. Obj

n the graphics widow can be selected by mouse clickshe selection can occur at PDB, chain or residue level in

ments, in conjunction with a suitable interface to theraphical application, can be a powerful way of navigand working with molecular modeling data that is sprcross many different directories and file types.

The browser is typically loaded with an organizatioTML document that contains a set of hyperlinks. Wheyperlink is clicked, it causes a command to be sent

he browser to the Ribosome Builder to execute a particcript. In this way, a set of defined hyperlinks and assoc


Fig. 2. Screenshot of main window.

scripts can allow the user to load models, adjust the graphicalrepresentation and initiate a suite of molecular dynamics set-up operations with just a few clicks on a particular HTMLpage. The user can then navigate to another HTML page ina different directory, which may define an entirely differentmodeling project and initiate another set of operations in thesame way. This control strategy combines the benefits of thefamiliar browser interface, as exemplified in Protein Explorerand Chime (Martz, 2002), with the power and flexibility ofa scripting language embedded in a standalone open sourceapplication such as PyMOL (DeLano, 2002).

2.4. Scripting

The program contains an interpreter that can executeuser-defined scripts written in the Lua scripting language(Ierusalimschy et al., 1996). Lua is a small, robust, highlyefficient and extensible cross-platform open source languagewith powerful data definition and object-orientation capabili-ties. In addition, its syntax is simple and elegant and intendedto appeal to the non-professional programmer.

The Ribosome Builder project includes a comprehensiveand annotated scripting application programming interface(API), which is a set of functions written in Lua that provideaccess to the operations and data in the main program. Thefunctions are organized by category and are documented inHTML pages. The categories fall into three general areas.The first area deals with visual representation of models andincludes functions for controlling the view, setting graphicalstate and creating annotations. The second area covers thechemical representation of models with functions for control-ling the forcefield, accessing the data in static and dynamicmodels and recording movies. A third area contains functionsto support scripting, file, string, geometry, mathematical andother types of general utility operations.

2.5. Forcefield

2.5.1. Types of interactionsThe forcefield functions and parameters in the Ribosome

Builder were developed from scratch, without reference toexisting forcefields such as AMBER (Cornell et al., 1995)


or CHARMM (MacKerell et al., 2000). This was an inten-tional design decision, in accord with the goal of modelingextremely large structures such as the ribosome. The initialemphasis has been on computational efficiency, as opposedto more accurate, but time-consuming, simulations with es-tablished forcefields.

The molecular dynamics forcefield calculates the inter-actions between atoms and updates their positions at eachtimestep. The forces and movements are not calibrated to aphysical timescale but they do maintain bond lengths, bondangles and steric exclusions. Additional force functions areapplied to reproduce electrostatic, hydrogen bond and base-stacking interactions.

The movement of each atom in the forcefield is calcu-lated from explicit accumulations of forces and torques on theatom. This is in contrast to conventional forcefields, wherethe forces are calculated from a potential energy representa-tion. Because an atom has an explicit orientation and valencestructure, the interacting forces are used to compute torquesthat rotate the orientation, in addition to translating the atomcenter-of-mass.

The total force and torque on an atom at each timestepare the sum of forces and torques from all atom pair interac-tions involving that atom, as given in Eqs.(1) and(2). Theforce equation contains terms for steric (s), covalent (c), elec-trostatic (e), hydrogen bond (h) and aromatic base-stackingf lent(

F

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j reaction torque, shown in Eq.(5).

Fc = Fis − Fjs (4)

Tc = Tis − Tjs (5)

The force between an atom and its shadow point is given bythe spring force function in Eq.(6). The torque produced isthe cross product of the moment arm and the applied force.For the direct torque,Tis, the moment arm is zero, becausethe point of application of the force and the center-of-mass ofthe atom coincide. However, the reaction torqueTjs will benon-zero for the reaction forces applied at the shadow pointof atomj, as shown in Eq.(7). The pointsPi andPj refer tothe current locations of atomi and atomj. The pointsQi andQj are the shadow points for atomsi andj, and are calculatedby multiplying the original location vector of the atom by thetransform matrix of the other atom.

Fis = −kdisvPiQi (6)

Tjs = (Qj − Pi) ⊗ Fjs (7)

The torsion torque,Tt, is the torque produced on an atominvolved in a torsion bond, consisting of four atoms A–D.The torque is derived from the steric force between atoms Aand D, as shown in Eq.(8). The axial component of this forceis shown in Eq.(9).

F

F

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T

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ith an ctioni

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orces (r). The torque equation contains terms for covac), torsion bond (t) and hydrogen bond (h) torques.

= Fs + Fc + Fe + Fh + Fr (1)

= Tc + Tt + Th (2)

he atom pair interaction for each term depends uponype of atoms and the threshold distances. For examplteric interaction term is skipped for 1–2, 1–3 and 1–4 botoms, and all steric interactions are skipped betweenairs more distant than 25A.

The steric interaction term is a Lennard–Jones funcs shown in Eq.(3). k is a scaling factor, calculated from tum of the van der Waals radii of the two atoms whichroduce a force of zero at the equilibrium distance:vij is thenit vector between atomsi andj.

s =(

1

(k · d)n− 1

(k · d)m

)· vij (3)

he covalent interaction is calculated from the shadow pethod, described in more detail below. Briefly, the me

elies upon a set of covalently-bonded atoms with an ineometry. As the atoms change position over time, a shoint is the original location of one atom relative to the tra

ormed frame of a second atom. The force on an atomi ishe sum of its shadow point force and the reaction forche shadow point of atomj, as shown in Eq.(4). The correponding torque is the sum of the atomi torque and the ato

AD = 1

(kdAD)n− 1

(kdAD)m(8)

r = (FAD � vBC)vBC (9)

t = FAD − Fr (10)

B = (PA − PB) ⊗ Ft (11)

C = −TB (12)

he tangential component of the force,Ft, is then used troduce the torques on atoms B and C, as shown in Eq(11)nd Eq.(12).

An electrostatic force is calculated between atoms won-zero charge, as given by the standard coulomb fun

n Eq.(13).

e =(

−k · qi · qj

(dij)2

)vij (13)

he hydrogen-bond function is a more complex functhich uses two equilibrium distances. The first distancetween the hydrogen bond donor and acceptor atoms aecond equilibrium distance is between the hydrogennd the non-bonded electron pair of the acceptor atom, w

s projected out from the center of the atom along a valond vector.

The function is piecewise continuous and consists of tegions: a lower distance region that is electrostatic, giveq.(14); a middle region that is harmonic, given by Eq.(15);nd an upper distance region that is electrostatic, give


Fig. 3. Use of shadow points in covalent bonding. Coordinate frames are shown asx, y andzaxes colored in red, green and blue, and located at the center ofeach atom. The shadow points represent the location of the bonded atoms when their coordinate frames are coincident. The divergence of the atoms from theirshadow points has been exaggerated for illustration.

Eq. (16). The force is then multiplied by a directional factorthat reflects the orientation of the hydrogen bond.

Fhl = −ke

[dij − (deq − kwa)]2(14)

Fhm = ks · (dij − deq) (15)

Fhu = ke

[dij − (deq + kwa)]2(16)

The aromatic base-stacking force is only applied for nucleicacid residues. It is currently implemented as a simple elec-trostatic force, calculated between centrally-located atoms inthe aromatic ring, as shown in Eq.(17).

Fr =(

−kr

(dij)2

)vij (17)

2.5.2. Shadow point method for covalent bondingIn order to permit the use of strong driving forces and

longer timesteps without excessive distortion of bond angles,a new method involving ‘shadow points’ was developed forthe Ribosome Builder forcefield. This method differs fromconventional molecular dynamics approaches where bondangles are typically maintained by applying spring forcesbetween 1 and 3 atoms.

t co-o f thei ova-l pairo ng isc ectedt ginalb e oft ove-

ment of the coordinate frames of the two atoms to a rotationabout their mutual bond vector.

The shadow point constraints of multiply bonded atomswill then combine to maintain the constant bond angles be-tween the atoms. This effect becomes evident by consider-ing a single bond angle defined by three atoms, with atom 1bonded to atom 2, which in turn is bonded to atom 3. As thecoordinate frame of atom 2 rotates about its bond with atom1, the shadow point connection of atom 2 to atom 3 will alsorotate about this same bond vector. This constrains atom 3 torotate about the vector, maintaining the bond angle.

This approach results in a rigidly bonded structure that isrobust in response to strong external forces. The representa-tion of the geometrical orientations of the electronic structureof atoms is also used in defining hydrogen bond interactions.

3. Applications

To illustrate some of the capabilities of the RibosomeBuilder, three applications of the program will be described.They range in size from the folding of a short RNA oligomerinto a tetraloop, to the wrapping of a longer mRNA arounda path in the 30S subunit to a schematic simulation of theelongation cycle of the ribosome.

3

anS r ofR m-l ings tat helix

The shadow point scheme, as shown inFig. 3relies uponhe definition of a coordinate frame for each atom. Thisrdinate frame represents the geometrical orientation o

nternal electronic structure of an atom. To define a cent bond, two spring forces are applied between eachf covalently bonded atoms. One endpoint of each sprionnected to an atom and the other endpoint is conno a shadow point. The shadow point represents the orionded location of the first atom in the coordinate fram

he second atom. These springs constrain the relative m

.1. Folding a tetraloop

An example of applying higher-order information toMD simulation is shown in the folding of a short oligomeNA from the A-form helix conformation to a folded ste

oop structure with a GNRA tetraloop motif. The starttructure was generated by Nucleic Acid Builder (Macke el., 2004) and is shown on the left in tan color inFig. 4A. The

arget structure was obtained from the 12 residues of


Fig. 4. Tetraloop folding. (A) Unfolded oligomer in tan on left, target structure in dark green. (B) Directions of applied torque and reaction torque at torsionangleα between residues G5 and C6 of unfolded structure. (C) Alignment of folded structure and target structure.

41 of the 30S subunit in the crystal structure of PDB model1J5E (Wimberly et al., 2000) and is shown on the right indark green inFig. 4A.

Before the creation of an SMD script, an analysis of thetorsion angles of the folded tetraloop structure was done us-ing the dihedral functions in the scripting API of the pro-gram. Classification of the backbone torsion angles into ro-tamers, according to the table of suite conformers (Murrayet al., 2003) confirmed that all of the residues in both theunfolded and the folded structures were in the A-form con-former except for the single suite of the first two residuesof the tetraloop (G1266–C1267). In this suite, only a singletorsion angle undergoes a significant change. Theα torsion

angle of C1267 changes from−62.1◦ in the A-form helix to152.2◦ in the folded tetraloop.

This motivated the creation of a script to apply the angularsprings around the bonds in the backbone atoms of the oligoto drive a conformational change to the folded state. An an-gular spring, also called a ‘torsion spring’, applies a torqueon an atom and an oppositely-directed reaction torque on itsbonded partner atom with a magnitude proportional to theangle difference between the current torsion angle and thetarget torsion angle for that torsion bond. A total of 68 tor-sion springs were created. The applied torques were clampedto a maximum value to prevent excessive distortion of themodel.


The primary motion of the oligo is a twisting of the twohalves on either side of the C1267α torsion angle describedabove. The direction of the applied torque for that partic-ular torsion angle had to be defined a little differently. In-stead of being applied in the direction that would minimizethe difference to the target angle, the torque was applied inthe counter-clockwise direction so that the two halves weretwisted in the opposite direction. This is because a torqueapplied in the clockwise direction would cause a clash be-tween adjacent bases. Presumably this directionality reflectsthe way the oligo might fold in reality, although it is possibleto envision a more complicated set of coordinated rotationsof adjacent residues that would enable a clockwise folding ofthe two ends.

Once the two halves of the oligo had rotated to the tar-get conformation, the hydrogen bond forces produced base-pairing in the stem as intended, although there was a certaindegree of variability in the pairing depending upon the val-ues of the forcefield hydrogen bonding parameters. This isbecause the formation of strong and stable hydrogen bondsbetween non-canonical acceptors and donors tended to trapthe structure in non-target conformations. External thermalinput and longer simulation times were employed to try topush the structure out of these local minima and toward thetarget conformation, but better results were obtained by re-ducing the stability of the hydrogen bonds.

enta on-f tra-j n be-t orea pre-f butt ionsa

e rac-t g anR ionst ringc

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tioni thew delo uced( rkg e1 micd posi-t

ro-g merg leic

Acid Builder (tan structure inFig. 5 A), and then drive themodel to the target conformation of the docked mRNA in thecrystal structure.

To produce this final docked conformation, a script wascreated that applied external forces on the backbone atomsof the oligomer. The forces were produced with a harmonicspring function with clamping applied as needed to limit themagnitude of forces to a maximum value. The forces were ap-plied in a sequential manner by starting with the first residueand then proceeding to the next residue only after the pre-vious one was aligned to its target location within a certainthreshold distance (Fig. 5B).

In addition to the external forces, the interactions betweenthe residues were simulated by the forcefield in order to main-tain the proper steric and covalent bond distances and anglesduring the alignment. About 2 h of real-time computation on atypical desktop machine were required to produce a success-ful alignment of the backbone atoms to the target locations,resulting in an all-atom model of an mRNA in the dockedlocation (Fig. 5C). A movie of the simulation was recordedand is included in the distribution.

In this first simulation, interaction with the surroundingRNA and proteins of the 30S subunit was not done, butthe success of the approach opens the way to the simu-lations of more realistic trajectories of mRNA docking. Anumber of steps in the translational process, including theS uires ex-t

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om-p is fo-c tweens nt initi-a thee re area andh nsfera of as at ana

con-s ntlyc rtainf ts, aso largen cess,t e thev rdert Thes d thel -Tua and

Although this simulation was done with rather stringrtificial constraints to produce a fold to a known target c

ormation, it was able to produce a chemically plausibleectory in which bond lengths, angles and steric exclusioween atoms were maintained throughout the folding. Mccurate MD simulations of tetraloop dynamics would be

erred for determining the actual stability of a target fold,hey are generally confined to simulating smaller fluctuatround a particular conformation (Sorin et al., 2002).

If the rotameric definition of RNA conformation (Murrayt al., 2003) can be extended by the identification of cha

eristic coordinated transitions of adjacent rotamers alonNA backbone, the application of a set of external tors

o produce such transitions might prove useful for exploonformational change in RNA structures.

.2. Producing large conformational changes in mRNA

A prerequisite for an adequate simulation of translas a model of an mRNA of sufficient length that it spansidth of the ribosomal subunits. A crystal structure mof an mRNA docked to the 30S subunit has been prodYusupova et al., 2001) and is 27 nucleotides in length (dareen structure inFig. 5A). However, the model (PDB codJGO) only shows the six center nucleotides in full atoetail. The remaining residues are represented by the

ions of backbone phosphorus atoms.One application of SMD by the Ribosome Builder p

ram was to use an all-atom model of a 27 nt RNA oligoenerated in standard A-form helix conformation by Nuc

hine–Dalgarno interaction and translocation, will reqimilar simulations of large conformational change ofended mRNA molecules.

.3. A schematic simulation of translation elongation

In contrast to the view of static stereochemistry of conents at fixed sites, a dynamic concept of translationused on the changes that occur and the transitions betates (Woese, 2001). Translation of mRNA into protein ohe ribosome can be divided into three distinct phases:tion, elongation and termination. A complete model oflongation phase remains to be developed, but now thesufficient number of structural models of componentsypothetical mechanisms for the decoding, peptide-trand translocation substeps to permit the constructionchematic model of the entire elongation sequencetomic level of detail.

A schematic simulation of this process has beentructed with the Ribosome Builder. The simulation curreonsists of approximately 60 distinct steps, although a ceraction of these are concerned with presentational evenpposed to actual model events. Because there are aumber of intricate components and events in the pro

he script makes extensive use of operations that changiewpoint and graphical representation of molecules in oo optimally present particular details to the observer.tructural content includes atomic models of the small anarge subunits, tRNAs, mRNA, and translation factors EFnd EF-G. All the models are loaded into the program


Fig. 5. Wrapping an mRNA around a target path. (A) Unfolded mRNA in A-form helix colored in tan, target structure in dark green. (B) Partially wrappedmRNA, with blue line showing external force acting on currently aligning residue. (C) Final conformation of mRNA wrapped around target structure.

aligned to a common geometrical reference frame. A screenshot of the simulation displaying a subset of the models isshown inFig. 6.

The structural models are taken from snapshots of the ri-bosome in various functional states. Some of the movementsin the simulation, such as docking of translation factors, arerepresented by simple geometrical interpolation of the staticstructures from one position and orientation to another. Otherevents, such as codon–anticodon recognition, peptide bondformation and translocation, are represented by playback of

molecular dynamics movies that were produced from SMDsimulations.

The complete simulation can be downloaded from theproject web site and played back in the main program on auser’s local machine. An associated HTML document canbe loaded into a web browser, which will then provide acollection of runtime controls that allow the user to single-step through the simulation or jump directly to any particularevent. The simulation is not a pre-recorded animation. Atany point, the user may stop the playback and use the 3D


Fig. 6. Screenshot from the schematic simulation of the elongation cycle of the ribosome.

interface controls to change the viewpoint and inspect thestructural models. At some point in the future, the simulationmay be ported to other formats such as VRML or MPEG. Ifrecorded as a video in MPEG format, the simulation wouldlose the interactive capability, but it would allow for view-ing of the content without having to download and install theRibosome Builder program.

This schematic model of elongation is only intended toserve as a foundation for the development of additional, moreelaborate models of translation and other activities of RNA.As Woese (2001)suggests, a deeper understanding of theribosome may require more than an accurate model of allthe detailed interactions of the present mechanism. The hy-pothetical construction of smaller and simpler systems oftRNA-like entities and peptides may generate a missing evo-lutionary perspective into the complexities and elaborationsof the modern ribosome (Woese, 2001).

4. Software implementation

The core application is written in C++. Low-level func-tions are organized in libraries for modularity and reuse. Thegraphical interface is implemented with OpenGL and the Qtapplication framework (Trolltech, 2005). Higher-level andapplication-specific operations are defined with Lua scripts.S e Perla ina

The documentation includes a user manual and com-mented code in Doxygen format. The command-line inter-face and the scripting API are fully documented in HTML.Development of tutorials and example applications is ongo-ing.

4.1. Availability

At the present time the program is only available for Win-dows 95/98/ME/NT/XP platforms. However, the softwareconsists of cross-platform open source code, and the pro-gram is in the process of being ported to GNU/Linux plat-forms. The program is distributed under the GNU GeneralPublic License.

A complete distribution of the program, including sourcecode and demonstrations, is available at therbuilder projecton SourceForge (http://rbuilder.sourceforge.net). For addi-tional questions on availability and use, contact WilliamKnight via email [email protected].

4.2. Future work

Near-term goals include the development of more efficientintegrators for timestep movement, migration of the commonSMD routines from scripting code to more efficient C++ code,better support for proteins (because the initial emphasis hasb tion,p ou-t port

ome scripts that generate HTML reports and graphs usnd gnuplot, which are also distributed with the programstripped-down form.

een on nucleic acids), a better ring-stacking force funclug-ins for other forcefields and energy minimization r

ines, and the creation of better graphical tools to sup

http://rbuilder.sourceforge.net/

mailto:[email protected]


interactive modeling, forcefield configuration and construc-tion of schematic simulations.

5. Conclusion

The Ribosome Builder is a software program for model-ing the translational process of the ribosome in atomic detailthrough steered molecular dynamics simulations. The pro-gram provides a rich graphical interface and scripting API tosupport the SMD modeling. Preliminary applications includethe simulation of tetraloop folding, docking of mRNA to atarget path on the 30S subunit and a schematic simulation oftranslation elongation.

The set-up, monitoring and analysis of steered moleculardynamics simulations present a steep learning curve for thegeneral researcher in molecular biology, whose time is of-ten divided among many competing tasks. Freely availableopen source programs such as VMD (Humphrey et al., 1996)go a long way toward lowering the barriers to SMD inves-tigations by presenting a graphical interface, custom menusand scripting support. In addition, open source libraries suchas the Molecular Modeling Toolkit (MMTK) (Hinsen, 2000)enable the rapid prototyping of modeling applications in ahigh-level scripting language. The Ribosome Builder projectaims to take the process one step further by demonstratingt thed omalt

atingm no-t heses andp rtantm othertp 3Dm easief theiri

litieso rallyu t arec ouldi mpsa

olst ro-m rtoireo use.S hem d int ell-b thea astl

Acknowledgements

We gratefully acknowledge Dr. John Gerdes for criticalreading of the manuscript and Scott Hennelly for helpful dis-cussions regarding use of the Ribosome Builder software.This work was supported in part by the National Institutes ofHealth grant GM35717 to WEH.

References

Aloy, P., Bottcher, B., Ceulemans, H., Leutwein, C., Mellwig, C., Fischer,S., Gavin, A.C., Bork, P., Superti-Furga, G., Serrano, L., Russell, R.B.,2004. Structure-based assembly of protein complexes in yeast. Science303, 2026–2029.

Ban, N., Nissen, P., Hansen, J., Moore, P.B., Steitz, T.A., 2000. Thecomplete atomic structure of the large ribosomal subunit at 2.4Aresolution. Science 289, 905–920.

Berman, H.M., Bhat, T.N., Bourne, P.E., Feng, Z., Gilliland, G., Weissig,H., Westbrook, J., 2000. The Protein Data Bank and the challenge ofstructural genomics. Nat. Struct. Biol. 7 (Suppl.), 957–959.

Cornell, W., Cieplak, P., Bayly, C., Gould, I., Merz, K., Ferguson, D.,Spellmeyer, D., Fox, T., Caldwell, J., Kollman, P., 1995. A secondgeneration force field for the simulation of proteins, nucleic acids,and organic molecules. J. Am. Chem. Soc. 117, 5179–5197.

DeLano, W., 2002. The PyMOL Molecular Graphics Systemhttp://pymol.sourceforge.net/.

Ferrara, P., Apostolakis, J., Caflisch, A., 2000. Computer simulations ofprotein folding by targeted molecular dynamics. Proteins 39, 252–260.

G elec-ular

H r dy-

H nu-base

H h to

H lar

I sible

I lnar,ics,

s, 4.

K ions

L mer

M nual

M andly-

M cular

M pen

M J.S.,100,

S anell,, A.,

he customization of the tools, the scripting libraries andata around a particular problem domain such as ribos

ranslation.The program also proposes a scheme for acceler

odel building by introducing the tools to create anated simulations of molecular models and processes. Tchematic simulations can facilitate rapid prototypingromote feedback from larger groups of users; two impoechanisms that have accelerated the development of

echnologies such as computer software (Moody, 2001). Byroviding an explicit graphical representation of complexolecular structures and events, the scheme makes it

or researchers to work on problem domains outside ofmmediate experience.

The customization and schematic simulation capabif the Ribosome Builder software should prove geneseful for modeling other macromolecular systems thaomposed of multiple moving components. Examples cnclude the polymerase machinery, motor proteins, pund signaling pathways.

There is still much work to be done in building better too view, modify and distribute dynamic models of macolecular systems. As these tools improve, a wide repef dynamic models should become available for publicuch models will fill in the low-level atomic details of tultitude of building blocks that are currently being use

he construction of genome-wide interaction maps. A wuilt hierarchy of information and software tools fromtomic to the multicellular-level will help us to scale the v

andscapes of systems biology.

r

rayson, P., Tajkhorshid, E., Schulten, K., 2003. Mechanisms of stivity in channels and enzymes studied with interactive molecdynamics. Biophys. J. 85, 36–48.

ansson, T., Oostenbrink, C., van Gunsteren, W., 2002. Moleculanamics simulations. Curr. Opin. Struct. Biol. 12, 190–196.

arvey, S.C., Wang, C., Teletchea, S., Lavery, R., 2003. Motifs incleic acids: molecular mechanics restraints for base pairing andstacking. J. Comput. Chem. 24, 1–9.

insen, K., 2000. The molecular modeling toolkit: a new approacmolecular simulations. J. Comput. Chem. 21, 79–85.

umphrey, W., Dalke, A., Schulten, K., 1996. VMD: visual molecudynamics. J. Mol. Graph. 14 (33–38), 27–28.

erusalimschy, R., de Figueiredo, L., Celes, W., 1996. Lua—an extenextension language. Software: pract. experience 26, 635–652.

zrailev, S., Stepaniants, S., Isralewitz, B., Kosztin, D., Lu, H., MoF., Wriggers, W., Schulten, K., 1998. Steered Molecular DynamComputational Molecular Dynamics: Challenges, Methods, IdeaSpringer-Verlag, Berlin, pp. 39–65.

arplus, M., McCammon, J.A., 2002. Molecular dynamics simulatof biomolecules. Nat. Struct. Biol. 9, 646–652.

iao, S., Seeman, N.C., 2004. Translation of DNA signals into polyassembly instructions. Science 306, 2072–2074.

acke, T., Svrcek-Seiler, W. and Case, D., 2004. NAB Users’ Mahttp://www.scripps.edu/mb/case/casegrsh-3.2.html.

acKerell Jr., A.D., Banavali, N., Foloppe, N., 2000. Developmentcurrent status of the CHARMM force field for nucleic acids. Biopomers 56, 257–265.

artz, E., 2002. Protein Explorer: easy yet powerful macromolevisualization. Trends Biochem. Sci. 27, 107–109.

oody, G., 2001. Rebel Code. The inside story of Linux and the OSource Revolution. Perseus Publishing, p. 60.

urray, L.J., Arendall, W.B., Richardson 3rd, D.C., Richardson,2003. RNA backbone is rotameric. Proc. Natl. Acad. Sci. U.S.A.13904–13909.

chluenzen, F., Tocilj, A., Zarivach, R., Harms, J., Gluehmann, M., JD., Bashan, A., Bartels, H., Agmon, I., Franceschi, F., Yonath

http://pymol.sourceforge.net/

http://www.scripps.edu/mb/case/casegrsh-3.2.html


2000. Structure of functionally activated small ribosomal subunit at3.3 angstroms resolution. Cell 102, 615–623.

Sorin, E.J., Engelhardt, M.A., Herschlag, D., Pande, V.S., 2002. RNAsimulations: probing hairpin unfolding and the dynamics of a GNRAtetraloop. J. Mol. Biol. 317, 493–506.

Spolsky, J., 2004. The Schlemiel way of software.http://www.salon.com/tech/feature/2004/12/09/spolsky/.

Taylor, W.R., 2004. A molecular model for transcription in the RNAworld based on the ribosome large subunit. Comput. Biol. Chem. 28,313–319.

Trolltech, 2005. Whitepaper. http://www.trolltech.com/products/whitepapers.html.

Wimberly, B.T., Brodersen, D.E., Clemons Jr., W.M., Morgan-Warren,R.J., Carter, A.P., Vonrhein, C., Hartsch, T., Ramakrishnan, V.,2000. Structure of the 30S ribosomal subunit. Nature 407, 327–339.

Woese, C.R., 2001. Translation: in retrospect and prospect. RNA 7,1055–1067.

Yusupova, G.Z., Yusupov, M.M., Cate, J.H., Noller, H.F., 2001. The pathof messenger RNA through the ribosome. Cell 106, 233–241.

http://www.salon.com/tech/feature/2004/12/09/spolsky/

http://www.salon.com/tech/feature/2004/12/09/spolsky/

http://www.trolltech.com/products/whitepapers.html

http://www.trolltech.com/products/whitepapers.html

ribosome builder: a software project to simulate the ribosome

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