Institute for Organic Chemistry and Chemical Biology -
Prof. Dr. Gisbert Schneider

>

Research fields

• Chemoinformatics and Bioinformatics
  
• Development and application of virtual screening approaches for the identification of novel lead structures
  
• Application of machine learning approaches for the derivation of structure-activity-relationships
  
• Molecular design with evolutionary algorithms and artificial neural networks
  
• Analysis of protein-targeting-signals
  
  

>

Resources and Abilities

• Multiprocessor Linux cluster
  
• Application of commercial software and software developed in our group for drug design and molecular modeling
  
  

>

Staff

• Dipl.-Bioinf. Swetlana Derksen (allosteric modulation of GPCRs)
  
• Dipl.-Bioinf. Yusuf Tanrikulu (pharmakophor modelling)
  
• Dipl.-Bioinf. Martin Löwer (in silico search for protease-genes in the genome of H. pylori)
  
• Dipl.-Bioinf. Eugen Proschak (de novo drug design using shape descriptors)
  
  

>

Publications

• Rupp M, Proschak E, Schneider G: Kernel Approach to Molecular Similarity Based on Iterative Graph Similarity. J Chem Inf Model 2007; 47:2280-2286.
  
• Schmuker M, Schneider G: Processing and classification of chemical data inspired by insect olfaction. Proc Natl Acad Sci USA 2007; 104:20285-20289.
  
• Glen R, Schneider G: (Eds). "*Challenges in Virtual Screening ", Special Issue, *QSAR & Combinatorial Science 2006; 25(12), Wiley-VCH, Weinheim, New York.
  
• Noeske T, Sasse BC, Stark H, Parsons CG, Weil T, Schneider G: Predicting compound selectivity by self-organizing maps: Cross-activities of metabotropic glutamate receptor antagonists. ChemMedChem 2006; 1:1066-1068.
  
• Schüller A, Fechner U, Renner S, Franke L, Weber L, Schneider G: A pseudo-ligand approach to virtual screening. Comb Chem High-Throughput Screen 2006; 9:359-364.
  
• Meissner M, Schmuker M, Schneider G: Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training. BMC Bioinformatics 2006; 7:125-136.
  
• Fechner U, Schneider G: Flux (1): A virtual synthesis scheme for fragment-based de novo design. J Chem Inf Model 2006; 46:699-707.
  
• Byvatov E, Sasse BC, Stark H, Schneider G: From virtual to real screening for novel D3 dopamine receptor ligands. ChemBioChem 2005; 6:997-999.
  
• Renner S, Ludwig V, Boden O, Scheffer U, Göbel M, Schneider G: New inhibitors of the Tat-TAR RNA interaction found with a "fuzzy" pharmacophore model. ChemBioChem 2005; 6:1119-1125.
  
• Schneider G, Fechner U: Computer-based de novo design of druglike molecules. Nature Re. Drug Discov 2005; 4:649-663.
  
• Franke L, Byvatov E, Werz O, Steinhilber D, Schneider P, Schneider G: Extraction and visualization of potential pharmacophore points using Support Vector Machines: Application to ligand-based virtual screening for COX-2 inhibitors. J Med Chem 2005; 48:6997-7004.
  
• Schneider G, Fechner U: Advances in the prediction of protein targeting signals. Proteomics 2004; 4:1571-1580.
  
• Renner S, Schneider G: Fuzzy pharmacophore models from molecular alignments for correlation-vector based virtual screening. J Med Chem 2004; 47:4653-4664.
  
• Downs G, Schneider G (Eds): "*Machine Learning Methods in QSAR Modelling", Special Issue, *QSAR & Combinatorial Science 2003; 22(5), Wiley-VCH, Weinheim, New York.
  
• Böhm HJ, Schneider G (Eds): Protein-Ligand Interaction: From Molecular Recognition to Drug Design. Wiley-VCH 2003;, Weinheim, New York.
  
• Schneider G, So SS: Adaptive Systems in Drug Design. Landes Bioscience 2001;, Georgetown.
  
• Böhm HJ, Schneider G (Eds): Virtual Screening for Bioactive Molecules. Wiley-VCH 2000;, Weinheim, New York.
  
• Wrede P, Schneider G (Eds): Concepts in Protein Engineering and Design. Walter-de-Gruyter 1994;, Berlin, New York.