Cancer Research - Europa

CancerGrid
Grid-aided computer system for
rapid anti-cancer drug design
Summary
In the three years of this multidisciplinary research project,
the 10-member Consortium plans to develop and refi ne
methods for the enrichment of molecular libraries to facilitate
discovery of potential anti-cancer agents. Using
grid-aided computer technology, the likelihood of fi nding
anti-cancer novel leads will substantially increase the translation
of basic knowledge to application stage.
In particular, through the interaction with novel technologies
and biology, the R&D consortium aims at:
• developing focused libraries with a high content of anticancer
leads;
• building models for prediction of disease-related cytotoxicity
and of kinase/HDAC/MMP and other enzyme
(i.e. HSP90) inhibition or receptor antagonism using
HTS results;
• developing a computer system based on grid technology,
which helps to accelerate and automate the in silico
design of libraries for drug discovery processes, and
which is also suitable for future design of libraries for
drug discovery processes that have diff erent biological
targets (the result is a new marketable technology).
Problem
Keywords | Bioinformatics | pharmacology | grid technology | library design | in-silico prediction of drug-like properties |
prediction of ADME parameters | predictive toxicology | creation of virtual libraries |
After the completion of the sequencing stage of the human
genome project, the major focus of discovery eff orts turned
to the identifi cation of the druggable portion of the genome
that is linked to pathological states and is able to interact with
the drug-like chemical space, restoring normal functions.
Apparently, the druggable genome is a subset of the 30 000
genes in the human genome that express proteins and represent,
in many ways, an unprecedented gift and exceptional
opportunity for drug discovery scientists and for patients
who are hoping for therapies of diseases currently uncured.
That subset (estimated as ca. 3 000 proteins) is able to bind
drug-like molecules as characterised by the Lipinski’s ruleof-5
criteria.
In order to fi nd more rapidly small molecule modulators to
the newly emerging validated targets, the high-throughput
screening provides a reasonable solution to screen large
compound libraries. However, it seems most of the targets
can be classifi ed into large target families such as kinases
and GPCRs: thus, development of target focused libraries
could dramatically increase the hit rate as well as open the
way to identifying selective inhibitors/antagonists within the
target families.
The idea of ‘focused libraries’ or ‘targeted libraries’ of molecules
emerged in recent years as a ‘compromise’, or as an
attempt to bridge between two seemingly confl icting
approaches to drug discovery:
• high Throughput Screening (HTS), by which hundreds of
thousands of compounds, mainly in big pharma, were
tested against a (hopefully validated) biological target
such as a protein or a cellular system. The basic assumption
of HTS is that large numbers and diversity should
cover chemical space well enough to fi nd, at least, ‘hits’
(that are active in micromolar concentrations) which
may subsequently be transformed to ‘leads’ (with affi nities
in the nanomolar range and with reasonable drug-like
properties) and fi nally to drug candidates. Combinatorial
chemistry has also been on the side of HTS, presenting
the ability to synthesise huge amounts of derivatives
based on specifi c ‘scaff olds’;
• rational drug design approaches such as structure-based
design and ligand-based design. The fi rst takes into consideration
the detailed atomic structure of the target and
the possibilities for forming physical interactions (i.e.,
hydrogen bonds, Van der Waals interactions, electrostatic
complementarity, hydrophobicity, etc.) between small
molecules and specifi c sites on the targets, while the second
depends more on properties of known active
molecules and uses similarity ideas (including ‘pharmacophore’
searches) to discover new active molecules. The
substantial reduction in discovering new chemical entities
by big pharma in recent years has been in part attributed
to the failures due to very low hit rate in both the HTS and
Combichem, on the one hand, and on the inability to
properly taking into account the pharmacokinetic (ADME/
Tox) eff ects as well as entropy, solvation and target fl exibility
in structure- and ligand-based designs.
A landmark in introducing pharmacokinetic considerations
to drug design and development has been the ‘Rule of 5’ of
Lipinski. This idea, which is now less than a decade old, also
provided an immediate tool to reduce the size of combinatorial
libraries and of HTS candidates by ‘fi ltering’, i.e., requiring
that all molecules must pass the Lipinski rule (three out of
four conditions for the limiting of molecular weight, calculated
lipophilicity, and the numbers of H-bond donors and
acceptors) in order to be in the proper bioavailability range.
The molecules that passed the Lipinski fi lter were thus targeted
on oral bioavailability, and their numbers were much
smaller than those for the initially planned experiments. The
idea of ‘fi lters’ thus gained momentum, and additional fi lters
such as those of Veber (limiting the number of rotatable
bonds and the size of polar surface area), also for bioavilability,
were suggested. Both Lipinski and Veber rules did not
consider directly any conformational aspects (3-dimensional
172 CANCER RESEARCH PROJECTS FUNDED UNDER THE SIXTH FRAMEWORK PROGRAMME