Integrating computational methods:Layout 1 14/1/10 20:00 Page 63
Molecular Modelling
The biologically relevant conformational and ly highly-dimensional. A high-fidelity descrip-
electronic-structure properties of a molecule tion of molecular reality is necessary to move
usually require three (and often more) dimen- from metaphor to pharmacophore, and from
sions for accurate representation and compari- simile to simulation.
son. Once a high-fidelity pharmacophore has
been established, it must be used to screen the Key applications of toxicity screening
novel compound against compounds known to in discovery and development
be toxic. Databases of these compounds, such It is an oft-quoted statistic that more than 90% of
as the FDA’s DSSTox, represent the knowledge compounds in development will not become suc-
collected from thousands of man-hours spent cessful drugs. While ballpark figures of this sort
characterising toxicity. Matching this existing may be a direct and unavoidable consequence of
body of work to the questions posed by newly the size of chemical space, this single figure encap-
discovered compounds is the key to realising sulates many variables that can be improved. The
significant time and cost savings in discovery earlier toxic candidates are dropped from the
and development. development process, the greater the amount of
This approach has the advantage of directly time and money saved.
analysing the existing data with a rational phar-
macophore based on realistic molecular geome- Virtual library design, pre-screening,
try and electronic structure. This replaces inter- and cross-screening
mediary rules of thumb, such as Lipinski’s rule- A high quality pharmacophore can improve key
of-five and other criteria of ‘drug-likeness’. Such stages of discovery and development. When
criteria have proved modestly successful at applied to the very beginning of the ligand-based
selecting leads for development, but fail to pre- discovery process, it can be the basis of a rational-
dict the efficacy of biological signalling mole- ly designed virtual library. This can better orient
cules such as peptides (which do not fit the rules an initial HTS/HCS search of chemical space. One
of drug-likeness), as well as toxicity. Indeed, the of the characteristic limitations of HTS is the
brevity of such rules is itself an example of an library it is based on. These libraries tend to be
attempt at reducing the dimensionality of the variations on a scaffold. While there may be a
underlying system. However, this approach great number of unique compounds in such an
causes a critical loss of information when under- HTS ‘deck’, their derivation from a small set of
standing molecular systems, which are inherent- scaffolds means they are all rather closely related.
Figures A2 (left) and A3 (right): 3D biologically relevant conformer pharmacophore representations. Note the large deviation from planarity in
imipramine's central ring, as well as the conformational difference of the tertiary amine chain. Pharmacophore legend – orange arrows: aromatic centres; orange
ellipses: hydrophobic centre; blue sphere: polar centre (omitted in A2 and B2 for clarity); purple sphere: H-bond donor/acceptor site; red arrow: H-bond donor/acceptor vector
Drug Discovery World Winter 2009/10 63
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