HOME- Bryn Mawr Conference
- Workshops & Training
- 2010 Oxford (Discovery)
- 2010 Oxford (ADMET)
- 2009 Oxford (Discovery)
- Blanchard, H
- Bryant, S
- Coveney, P
- Hardy, B
- Hawkins, P
- Klamt, A
- Knapp, S
- Kranz, M
- Liebeshuetz, J
- Oledzki, P
- Pirok, G
- Wolber, G
- Zamora, I
- Bursary Award
- 2009 Oxford (ADMET)
- 2008 Oxford
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John Liebeschuetz graduated with a degree in natural science from Cambridge University in 1981. This was followed by a studentship at Southampton University researching stereo-electronic effects in organic reactions. The combination of theoretical and experimental work that this entailed was his first exposure to multi-disciplinary working, a style of operation which has stood him in good stead ever since.From 1985 John worked as a synthetic chemist in the crop protection research arm of Dow Chemicals, more latterly for DowElanco, at the Dow research site near Oxford, England. He became interested in applying molecular modelling techniques for the discovery of new crop protection agents and used both rational design and QSAR methodology successfully in a number of projects. In 1994, after a “reorganisation” he joined Biotech with a move to Proteus in Macclesfield, UK. There John abandoned synthetic chemistry for the less messy, but occasionally less aesthetically satisfying world of molecular modelling. There followed an exciting 10 years employing the new techniques of docking and virtual screening to real problems in drug design. During this time John lead a team who invented the first truly de novo designed series of factor Xa inhibitors, from which an orally available antithrombotic clinical candidate was uncovered. This is currently in Phase II trials.Further “reorganisations” followed and after working for four different organisations (Proteus, Protherics, Tularik and Amgen), but having ever had only one desk, he left in 2005 to join the Cambridge Crystallographic Data Centre as Applications and Marketing Manager. His current research interests relate to the validation and improvement of structure based design tools with particular emphasis on using knowledge based methodology. A particular interest is to find ways of bridging the communication gap between chemist and modeller.
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Structure-Based Design Planning
John Liebeshuetz (CCDC)
“I have a therapeutic target of interest and I have a 3D model of the protein I wish to design ligands for. What should I do now ??”
This workshop is designed for anyone who finds themselves in this position. The key considerations to keep in mind when starting a design project are laid out and explored. We will first look at choice of suitable structural protein models. In this section we will examine how to validate a model and find and correct errors in the protein or ligand. We will investigate protein mobility and take account of this in model selection. We will look at protonation, and investigate how we might validate protonation states in cases of doubt.
The second part of the workshop will teach how to find other proteins that may need to be considered due to the similarity of their binding sites to the target. Such targets may be responsible for undesirable side effects of your candidate drug. We will see how to identify proteins that have little homology with the target, but which have similarities in respect to their binding site shape and binding characteristics.
The major program we will use in this workshop is Relibase+, a tool for probing the structure of ligand-protein complexes in the PDB and in-house databases. The group will:
* Find and superimpose a set of homologous candidate protein structures and identify out of these a good protein/ligand structure to work with
* Investigate whether there are errors in the structure e.g. misassigned waters, incorrect histidine, asparagine or glutamine rotamers in the active site, or geometry errors in the ligand
* Investigate whether we can assign protonation states in cases where it is not obvious
* Look for other proteins which may not have high homology or familial similarity with the target protein, but which share functional and shape similarities in the active site region.
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