Topics and Goals:
The genomes of many organisms have been solved and structural genomics
initiatives are producing more and more structural data. It is only a question of time until we will have reached
the point where structures for every gene family (and fold) will be available, thus providing sufficient templates
for more reliable homology modelling of any putative target protein for drug discovery. What can we learn
already now by comparing structures in terms of gene families? How can we best characterize and address this
biological space? Combinatorial chemistry provides efficient access to vast areas of chemical space and the
criteria to define the subsets of this space relevant to drug molecules are increasingly better understood.
Nevertheless, both spaces are still handled and searched rather independently. On the long run, properties and
information of both spaces must be intimately cross-linked and merged to efficiently explore these spaces. What
are reasonable approaches to achieve this goal? What are the most useful descriptors to capture the
complementarity between chemical and biological space? Recent attempts have tried to extract information from
protein families to define guidelines for the design of small-molecule ligands, and, conversely, ligand data have
been merged into a consensus picture to define pharmacophores that can be mapped into and onto proteins. What
are the perspectives of these techniques and what are possible alternatives? - The workshop is intended to
address these and similar questions by expert presentations and by fostering discussions among the attendees.
The workshop is organized by:
|
