Courses

Course 1. QSAR analysis - principles, methods and applications

Description and objectives

The correlation of biological activities with molecular descriptors leads to QSAR models which provide insights into the mechanism of drug action and enable predictions of novel compounds with desired properties. The course imparts basic knowledge on QSAR methods and their application, deals with LFER-based descriptors of hydrophobic, electronic and steric effects and covers some problems of model validation. Classical approaches like Hansch and Free-Wilson analysis will be presented with examples. 3D-QSAR methods (CoMFA, CoMSIA) based on the correlation of biological data with molecular fields (hydrophobic, electronic and steric field variables) of aligned structures will be explained, followed by the demonstration of a typical CoMFA approach (software Sybyl, Tripos L.P.).

Lecturer: Stefan Dove, University of Regensburg, Germany

Stefan Dove works as senior scientist and associate professor at the University of Regensburg, department of Pharmaceutical/Medicinal Chemistry. He deals with computer-assisted drug research with some thirty years of experience in QSAR analysis. Current projects aim at the investigation of protein-ligand interactions by molecular modeling and 3D-QSAR methods, considering different drug targets like G-protein coupled receptors, tyrosine kinases, adenylyl cyclases and hyaluronidases. Stefan Dove obtained his Dr. rer. nat. degree 1979 and his habilitation 1990 at the Institute of Drug Research of the Academy of Sciences of the GDR, Berlin, where he worked until 1991, mainly in the group of Rainer Franke, on the development and application of multivariate QSAR methods. 1991 he moved to his present position at the University of Regensburg. He is author and coauthor of over 90 publications in the field of medicinal chemistry and chemical biology and was member of the Editorial Board of QSAR & Combinatorial Science for many years. For master students in medicinal chemistry and science informatics, he holds lectures and courses on computer-assisted drug research (molecular modeling and QSAR).

 

 

 

 
 

Course 3. ABC of Modelling Transporter Data - Principles and Practical Know How

Description and objectives

The session involves both lecture and hands-on elements. It will give a step-by-step guide to modelling in vitro transporter data which could enable participants in better understanding of the common terms in this area. Transporter related experiments will be revisited and some pitfalls will be highlighted with the aim of assisting the researchers in finding their way through the complex datasets obtained from various in vitro techniques. Participants should bring their own computer and will work in small groups (2-3 people). We will only need Microsoft Excel, where the ‘Data Analysis Toolpack’ and the ‘Solver’ options within Add-ins are enabled.

Lecturer: Sibylle Neuhoff, Simcyp Ltd, UK

Sibylle is a principal scientist in Translational Science (DMPK) at Simcyp Limited (Sheffield, UK). She is working in the field of PBPK/PD modelling, oral drug absorption, metabolism and toxicity. Her areas of expertise are active drug transport and non-CYP metabolising enzymes (UGTs). She received a Bachelor of Sciences (Vordiplom) in Food Chemistry and a Master of Science (Diplom) in Chemistry from the Johan Wolfgang Goethe-University in Frankfurt am Main, Germany in 1992 and 1996, respectively. Her master thesis (1996) focused on the diuretic effect of ethacrynic acid and it’s phase-II-metabolite, the cystein-conjugate, in vivo in the rat and was carried out at the Department of Pharmacology (Frankfurt/M., Germany) with Prof. Ernst Mutschler. Her dissertation work entitled ‘Refined in vitro models for prediction of intestinal drug transport’ was carried out at the Department of Pharmacy at the Uppsala University (Uppsala, Sweden) with Professor Per Artursson and at AstraZeneca R&D (Mölndal, Sweden) with Associate Professor Anna-Lena Ungell (2002-2005). Current research interests include pharmacogenomics of drug-metabolizing enzymes and transporters related to drug disposition and pharmacodynamics, legend interactions with human phase II enzymes and transporters, and novel approaches to simulate and/or predict metabolic clearance, metabolic drug-drug interactions and transporter-related interactions in liver, intestine, brain and kidney.

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