Introduction

Introduction/Overview

Program Goals

RDPharm3D is a computational tool that allows scientists who are not computational experts to quickly and easily ask -- and answer -- "what if?" type questions using pharmacophore models. The models themselves are developed by computational chemists and deployed to the end-user scientists. End users query the pharmacophore models by simply drawing probe molecules in ChemDraw and then pulling them into RDPharm3D with a button click.


Using RDPharm3D

You do not need to be an expert computational chemist to use RDPharm3D to search molecules for pharmacophores.

This section introduces you to using the software to search molecules for a pharmacophore and covers the advanced topic of refining a search by adding points to an existing pharmacophore.


Getting Started

Once you have launched RDPharm3D, you need to load a P3D file containing a pharmacophore definition and other parameters. This is done by selecting the File->Open menu option and browsing to the file.

Your computer may also be configured so that double clicking P3D files will automatically launch RDPharm3D; consult your IT staff for information about this option.


Adding Molecules

You can add additional molecules to be searched at any time by clicking the Grab Molecule(s) from ChemDraw button at the bottom of the Search Results page.

Clicking this button will add the molecule in the active document in ChemDraw, and add it to the Search Results page. If there are multiple molecules in the active ChemDraw document, they will each be added individually to the Search Results page.

Molecules brought in from ChemDraw are automatically assigned a name based on their position in the list. These names can be changed via a slow double click on the molecule name (like renaming files in Windows Explorer).

To check whether or not a molecule is able to match the pharmacophore, click the + sign next to its name. This will expand the molecule and show you a list of possible mappings, if any, of the pharmacophore onto the molecule's atoms. See the next section for information about working with these mappings.


Exploring Hits

When you first expand a mapping, RDPharm3D will attempt to generate a number of three-dimensional conformations (embeddings in the language of distance geometry) that satisfy the pharmacophore. Depending upon the complexity of the molecule, this may take several seconds. Each of the mapping's embeddings are scored in three different ways:
  1. Energy: this is an estimate of the energy of the embedding relative to the energy of the unconstrained molecule. Because this energy is only an estimate, it is possible to see negative energy values; these should not be considered as physically meaningful (i.e. the pharmacophore does not somehow stabilize the molecule).
  2. Shape Score: this is a measure of the degree of shape overlap between the embedding and the reference molecule. Higher shape scores indicate better shape matches.
  3. Alignment RMS: this is the root-mean-squared distance between the pharmacophore points in the embedding and those in the reference molecule. Lower RMS values indicated better matches.
Further details about the scoring functions can be found in the Scoring Alignments section of the Methodology chapter.

You can change the the sort order of each mapping's embeddings by left clicking the column headings in the results tree.

Left clicking an individual alignment will cause that alignment to be displayed in PyMol. The details of what is displayed are controlled by the view options.

If you would like to see more possible structures for a mapping, right click on the mapping entry in the results tree and select More Alignments from the context menu.

Each alignment entry has a checkbox that can be used to flag the alignment for export to an SD file.

Note: In some cases, RDPharm3D may identify mappings that either cannot be realized by the molecule or that generate structures that are too strained to be chemically reasonable. Expanding these mappings will generate an error message.


Editing Molecules

In addition to adding new molecules from ChemDraw, it is also possible to edit the molecules that are already in the results tree. To do so, right click on a molecule item and select Edit Molecule from the context menu. The molecule will be displayed in ChemDraw, where you can make the desired changes. Once you are done editing, click Ok in the dialog box and your changes will be brought into the results tree. To abort the editing, click Cancel in the dialog and the molecule will not be modified.

If you would like to edit a copy of the molecule (leaving the original molecule unaltered in the results tree), right click on the molecule item and select Duplicate Molecule from the context menu. The copied molecule will be added at the top of the results tree; the copy can be edited as described above.


Changing the View

RDPharm3D provides a number of options that control the display of embeddings in PyMol. These are accessible via checkboxes at the top of the results tree:
  1. Show Protein?: if this is checked, the protein structure will be displayed along with each embedding and the reference molecule.
  2. Show Neighborhood?: when checked, this causes the surface of the protein around the reference molecule to be displayed. This option is disabled unless Show Protein? is checked.
  3. Show H Bonds: when checked, this causes likely hydrogen bonds between the aligned embedding and the protein to be drawn. This option is disabled unless Show Protein? is checked.


Adding Points to the Pharmacophore

RDPharm3D allows you to explore the effects of adding features to the pharmacophore in your P3D file in a straightforward manner.

Selecting Atoms

The first step in adding features to the pharmacophore is to select atoms in PyMol that define the feature(s). For single-atom features, such as hydrogen-bond donors, you should select that atom; for multi-atom features, such as aromatic groups, you should select one of the aromatic atoms.

After selecting the atoms, click the Grab Atoms From PyMol button at the top of the Define Pharmacophore page. The new atoms are added at the end of the list of atoms already in the pharmacophore:

By clicking the Highlight button next to the feature assignment box for each feature, you can highlight the corresponding atom in the molecular sketch (this is the gray circle in the figure above).

Assigning Feature Types

To assign a feature type, click the feature assignment box for each new feature and select the appropriate type. RDPharm3D will only show you feature types that match the atom you selected:

For example, in the illustration above, atom 3 is involved in three different feature types, you must select one for the pharmacophore.

Defining Distances

After assigning types to the points you added, the last step in updating the pharmacophore is to set the distances between the new feature(s) and the others in the pharmacophore. This is done by clicking the Grab Distances button.

When Grab Distances is pressed, RDPharm3D examines reference molecule, calculates the distances between the new features and those already present in the pharmacophore, and adds the new distances to the list of distances at the bottom of the window:

The distance ranges are automatically calculated based on a tolerance value.

Note that the sketch of the pharmacophore on the molecule has also been updated to highlight the atoms in the new feature (drawn with red circles in the sketch).

Exploring Changes

Once the new pharmacophore has been defined, you can switch back to the Search Results tab in order to explore how your current set of molecules can align.

Note: Defining a new pharmacophore will destroy any alignments that you may have found to the current pharmacophore. If you would like to save these, you should Save your work before clicking Grab Distances.


Saving Your Work

You have a number of options available for saving your work in RDPharm3D. These are detailed in the following sections.

Saving Everything

The most comprehensive approach for saving your work is available by selecting the File->Save or File->Save As menu options. These will save a P3D file with full details about the reference molecule, pharmacophore (including your changes, if any), and the contents of your Search Results page.

Exporting All Molecules

This command, accessible via the File->Export->All Hits menu option, allows you to save an SD file containing all of the molecules currently on the Search Results page.

The molecules will be saved without information about 3D structure or any mappings to the pharmacophore. A single copy of each molecule will be saved, even if each has multiple mappings.

Exporting Alignments

This command, accessible via the File->Export->Checked Alignments menu option, allows you to save an SD file containing the aligned 3D structures that are checked on the Search Results page.

If multiple alignments are selected for an individual molecule, they will all be exported by this command.


Method Overview

Methodology

Introduction

RDPharm3D uses distance geometry [Blaney1994,Crippen1981] to do pharmacophore searches and to generate a set of molecular conformations that match a pharmacophore. The matching conformations are "cleaned up" using a molecular force field [Rappe1992, Casewit1992] and aligned to the reference pharmacophore.

The general algorithm for finding matching conformations for a probe molecule is:
  1. Build the distance bounds matrix for the probe
  2. Find all mappings of the pharmacophore's feature types onto the probe
  3. Find all compatible mappings by searching through the mappings to find those where the probe's bounds matrix is compatible with the pharmacophore's distance requirements
  4. Generate molecular conformations for each compatible mapping, "clean up" the resulting conformations using a force field, then align those conformations to the reference pharmacophore.
  5. Score the generated alignments using several metrics.


Building the Bounds Matrix

The distance bounds matrix for each molecule contains lower bounds for each atom--atom distance in the lower triangle and the upper bounds for each distance in the upper triangle. These bounds are assigned using a rules-based approach [Blaney1994] where 1--2, 1--3, and some 1--4 distances are set using the force field's bond length, bond angle, and torsion parameters respectively. Bounds for some higher order distances (typically associated with rings) are also set. Any remaining distance bounds are set to conservative defaults: with a minimum above the sum of van der Waals radii and a large maximum.

Once the bounds matrix is constructed, it is refined using a triangle bounds smoothing algorithm that iteratively shrinks the individual bounds until they are as tight as possible.[Crippen1981]


Finding Pharmacophore Mappings

Finding Mappings

Potential mappings of the pharmacophore onto the molecule are found as follows:
  1. Lists of all matches the molecule has for each of the pharmacophore's features are created
  2. All possible combinations of these matches are generated
At this stage in the search process, the pharmacophore distances are not used. The only constraint on the mappings is that a single atom may not be involved in more than one feature in the mapping. This improves efficiency by removing degenerate pharmacophores from consideration.


Matching Pharmacophores

For maximum efficiency, a mapping is checked for whether it can match a pharmacophore in a series of steps ordered by increasing computational complexity:
  1. The 2D limits are checked: this test ensures that the topological distances between the features (or between the atoms in the features) do not exceed the pharmacophores threshold values.
  2. The 3D limits are checked: in this test the molecular distance bounds matrix is compared to the pharmacophore's distance requirements. If the molecular bounds matrix is compatible for this mapping, the matrix is updated.
  3. Triangle bounds smoothing is attempted to ensure that the updated bounds matrix still satisfies the triangle inequality.
Any mapping which passes all three tests is considered to be a likely candidate for matching the pharmacophore and is reported as a "hit".

Note: Bounds matrices that pass triangle bounds smoothing are not absolutely guaranteed to be physically embeddable (i.e. they will not produce valid 3D geometries). This means that some small number of hits from the pharmacophore matching process will be false positives. This will become apparent when the user actually attempts to generate structures for these hits.


Generating Structures

Three-dimensional structures are generated for a mapping by:
  1. Creating an initial set of coordinates by embedding the updated bounds matrix for each mapping [Crippen1981]
  2. Cleaning up the embedded structures using the Universal Force Field (UFF).[Rappe1992, Casewit1992] The optimization is done with constraints to ensure that the final structure still satisfies the pharmacophore.
    3. Aligning the cleaned conformation to the reference pharmacophore.[Heisterberg1990]
Whenever possible, multiple aligned conformations are generated for each mapping. This provides the user with an overview of the ways in which the probe molecule can satisfy the pharmacophore.<>


Scoring Alignments

Several different metrics are computed to score each alignment:
  1. Alignment RMS: This is the root mean squared distance (in Angstroms) between features in the aligned conformation and those in the reference pharmacophore. Lower RMS values correspond to better alignments.
  2. Conformation energy: This is the difference (in kcal/mol) between the computed UFF energies of the aligned conformation and a baseline conformation of the probe molecule. The baseline energy is calculated by generating a number of 3D structures of the free probe molecule (not subject to pharmacophore constraints) and taking the lowest energy. Lower conformation energies correspond to more stable alignments. Negative conformation energies do not indicate special stabilization by the pharmacophore, they just indicate a less-than-perfect value for the baseline energy. :-)
  3. Shape score: this is the Tanimoto similarity between the shape of the aligned conformation and that of the reference molecule. The shapes are generated on a Cartesian grid using the van der Waals radii of the atoms. Higher shape scores indicate better shape matches.


References

  1. Blaney, J. M.; Dixon, J. S. "Distance Geometry in Molecular Modeling". Reviews in Computation Chemistry; VCH: New York, 1994.
  2. Crippen, G. M. Distance Geometry and Conformational Calculations; Wiley: New York, 1981.
  3. Rappé, A. K.; Casewit, C. J.; Colwell, K. S.; Goddard III, W. A.; Skiff, W. M. "UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations". J Am Chem Soc 1992, 114, 10024-10035.
  4. Casewit, C. J.; Colwell, K. S.; Rappé, A. K. "Application of a universal force field to organic molecules". J Am Chem Soc 1992, 114, 10035-10046.
  5. Heisterberg, D. J. "QTRFIT: a routine for quaternion alignment of molecules"; 1990, Ohio Supercomputer Center: http://www.ccl.net/cca/software/SOURCES/C/quaternion-mol-fit/index.shtml.