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| About John W Liebeschuetz (CCDC) |
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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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Selectivity, Diversity and Pose Quality in Virtual Screening: The case for Post-docking Analysis
John W. Liebeschuetz, Cambridge Crystallographic Data Centre
Most structure based virtual screens currently carried out will utilise a highly pre-filtered list of ligands; these ligands will then be docked against one protein using one scoring function to rank the poses and make a percentage cut in which enrichment is found. This approach is time-efficient but may lead to an over reliance on a single scoring function, it may lead to lack of diversity in the hit list and it does not fully employ chemist/modeller expert knowledge.
An alternative approach is to generate more data and then use post-docking processing to filter down the results.
Advantages include being able to optimally use more than one scoring function, (the consensus approach) and being able to apply a number of different analyses to one set of docking poses. Several distinctive lists of privileged structures may thus be identified, broadening the chance of finding something novel. An additional advantage is that post-processing can easily be extended to results obtained from two or more proteins. This may be useful for instance to address ligand selectivity between different related target proteins.
Although it is easy these days to generate many hundreds of thousands of docking poses, specialist tools for data mining large numbers of docking poses are not widely available. We believe there is a need for such tools and they need to be designed with both the chemist and modeller in mind.
This talk will evaluate the rationale for post-docking analysis and illustrate some success stories. Some of the analyses that can be performed will be exemplified with reference to the CCDC’s recently released analysis program GoldMine.
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