Theoretical Aspects

Summary

How to use MODULE
 

Required Material

Starting the Program

Input File Format

Initial Display

Displaying the Primary Sequence

Selection of Type of Coupling

Setting Internuclear Distances

Fitting Single Modules

Fitting the Alignment Tensor

Correlation Plots

Comparision of Calculated and Experimental Couplings

Monte Carlo Error Analysis

Test Sample 1

Choice of Modules from Primary Sequence

Fitting the Alignment Tensors

Correlation Plots

Comparision of Calculated and Experimental Couplings

Monte Carlo Error Analysis

Common Alignment Frame

Degenerate Orientations

Automatic Calculation of Molecular Architecture

Covalent Bonds

Test Sample 2

Special Cases

Axially Symmetric Alignment Tensor.

Highly Rhombic Alignment Tensor.

 
Distance Constraints

Creating and Reading Work Folders

Simulating Datasets

Hammerhead Ribozyme - Orientation of Secondary Structural Motifs.

Test Sample 3

Protein-Protein Complexes.

Test Sample 4
 

Two further examples have been chosen to illustrate the use of the Module: these are the examples shown in our recent article describing the program. In both cases we have simulated data from theoretical alignment tensors in systems where orientational information would be particularly valuable.
 
 

The first is the hammerhead ribozyme, whose three-dimensional structure has been determined using X-ray crystallography (Pley et al 1994). This small catalytic RNA comprises three canonical regions of consensus secondary structure in the form of A-type helices, with, in the case of stem II, an additional GAAA tetraloop configuration, folded around the central core of the molecule.

It has recently been demonstrated that residual dipolar couplings can contribute important information to the determination of RNA global fold determination (Mollova et al 2000) precisely because of the complementarity of this long-range structural order, with the local secondary structure which can often be identified from well-established experimental procedures (Saenger 1984).

Similarly, in this example we have simulated dipolar couplings measured in both sugars and bases (assuming a ¹³C labelled sample to be available) from the hammerhead ribozyme, by calculating C-H couplings from the crystallographic structure (pdb code 1mmh) and adding 8% stochastic noise to the simulated values. The alignment tensor was assumed to be

and S assumed to be equal to 1 throughout the molecule. The molecule was then "unwound" using the Discover-derived program SCULPTOR (Hus et al 2000) using a high temperature restrained molecular dynamics calculation, such that the orientation of the helices was no longer native, but the secondary structural regions remained intact.

Comparison of the X-ray crystallographic structure of RNA/DNA ribozyme inhibitor (left pdb code 1mmh) and the structure used as initial model for the simulated experiment using Module (right). The native structure was partially unfolded using high-temperature restrained molecular dynamics as described in the text. The three stem regions are shown in blue (I), orange (II) and red (III), while the core is shown in grey. The heavy atoms from the core region were used for the superposition of the two structures. The rmsd of the heavy atoms between the two models is 10.5Å.
 
 

The different regions of the molecule to be treated as individual domains are selected from the primary sequence. The three stem regions are shown in blue (I), orange (II) and red (III), while the core is shown in yellow.

This non-native structure (heavy atom rmsd of 10.5Å compared to the initial, correct structure) and the simulated couplings were then used to reconstruct a model of the molecule using Module.

The alignment tensors are fitted for the stem regions (I-III); which are then automatically aligned in the reference frame of a common tensor.

In this case the tensors are virtually identical as the data are all calculated assuming the same simulated system.

Comparison of noise — simulated and fitted data from the 3 stem regions of the ribozyme — The blue data correspond to points from stem I, orange from stem II and red from stem III .

It is then possible to organise the three oriented domains relative to the core, either manually or automatically, to find a model in agreement with the orientational data and preserving the known covalence (heavy atom rmsd of 2.5Å compared to the initial, correct structure).
 

I -The alignment tensors of the different modules are determined and their eigenvectors superposed on the structures in their original (unwound) orientation.
 
 

II - The modules are then oriented so that the tensors all have the same alignment in the frame indicated by the tensor directions. The dotted lines indicate the distances between the covalently bound atoms. The substructures can then be manipulated individually on the screen, using only translational degrees of freedom and 180° rotations about A_xx, A_yy and A_zz. to find the most feasible model.
 
 

III - The optimal position of the different modules can also be calculated automatically, as described in the text, and this, or the manually adjusted orientation, can then be fixed and written in standard coordinate format.
 
 

IV - The final structure was calculated automatically using MODULE, by selecting the relative orientation of the different domains which minimises the function

The final model has a backbone rmsd of 2.5 Å compared to the initial crystal structure.

Test Sample 3 - The files used for this example are enclosed with the downloaded package and are called -
 

sample3.pdb

sample3.dat
 

The second example concerns a recently published molecular complex between the minor coat protein from Gene III in phage M13 (G3P) (86 amino acids) and the C-terminal domain of E.Coli protein Tol-A (126 amino acids).

Again this complex has recently been crystallised, and its structure determined using X-ray diffraction (Lubkowski et al. 1999). This structure was used to simulate experimental residual dipolar coupling data from NH sites distributed throughout the two molecules and 5% stochastic noise added to these simulated values. The tensor used in this case has eigenvalues

and S was again assumed to be equal to 1 in all cases.
 
 

The two proteins are treated as individual domains — again selected from the primary sequence (blue — GP3, yellow —Tol-a III).

The alignment tensors of the proteins are determined and their eigenvectors superposed on the structures in their original (pdb) orientation:
 
 

The individual protein structures were then aligned using Align as shown below. In this case the degeneracy of relative orientation plays a  significant role, as there is no covalence between the two partners
 
 

The proteins are rotated so that the tensors all have the same orientation in the alignment tensor frame indicated by the tensor directions. The proteins can be manipulated separately in this frame, using only translational freedom and rotations about A_xx, A_yy and A_zz.

There is no covalent interaction between the proteins, so in order to select between the multiple possible solutions, the user can select points on preferred interaction surfaces of the two molecules to aid the model-building. These may be experimental, such as intermolecular nOe measured between interacting surfaces, or predicted from existing structural information, for example electrostatic or hydrophobic surface calculations. Here we have kept the orientation of the Tol-a constant and show the 4 equivalent orientations of the GP3 protein, due to the inherent degeneracy of p rotations about A_xx, A_yy and A_zz.

Distance Restraints

Alternatively, if chemical shift mapping or inter-protein nOe have been measured distance constraints can be read (using the File menu and the Open Constraints option).

The constraints can be visualised using the constraints button which will appear in the main window when the distances have been successfully read -
 
 

Test Sample 4 - The files used for this example are enclosed with the downloaded package and are called -
 
 

sample4.pdb

sample4.dat
 

This work was supported by the Commisariat à l’Energie Atomique and the Centre National de la Recherche Scientifique.

Hus, J.-C., Marion, D. and Blackledge, M. (2000) J. Mol. Biol. 298, 927-936.

Lubkowski, J., Hennecke, F., Pluckthun, A. and Wlodawer, A. (1999) Structure, 7 711-722.

Mollova, E.T., Hansen, M.R. and Pardi, A. (2000) J. Am. Chem. Soc. 122, 11561-11562.

Pley, H.W., Flaherty, K.M. and McKay, D.B. (1994) Science, 372, 68-74.

Saenger, W. ( 1984) Principles of Nucleic Acid Structure. Springer-Verlag, New York