ChemBioet: Chemical Biology supported by etworks of Chemists and Biologists Affinity Proteomics Meeting Alpbach Michael Lisurek 15.3.2007
- Introduction - Equipment Screening Unit - Screening Compound Collection - Screening Project
Status of Usage of HTS Pharmaceutical Companies: - Standard Tool for Drug Development since Decades! Academic Institutions: - Lack of Available Compound Libraries - Lack of Automation and Know-How - Lack of Supporting Chemical Synthesis Resources - Lack of Support by Computational Drug Design
Medicinal Chemistry/ Molecular Modeling Automated Screening Unique Technology nline Database Screening Unit Compound Library Mobility Shift on Chips HT Cellular Imaging
ChemBioet: Academic Screening etwork Chemistry Compounds meets Biology Assays & Targets Bioprofiles Screening Units Compound Libraries & Technological Know-How for HTS Molecular Probes Combined Database in silico Methods
Equipment Screening Unit Supporting Academic Projects
Liquid Handling Robot for Library Transfer 384 Well Dispenser 384 Well Washer MTP Speed-Vac
Automated Mobility Shift Screening (LabChip-250) Caliper Life Sciences Leibniz-Institut für Molekulare Pharmakologie Boston - Berlin
Automated Mobility Shift Screening (LabChip-250) Caliper Life Sciences, Screening Technology
Reader-Equipment Safire 2 Genios Pro - Absorption Scans (Continuous Wavelength Range) - Fluorescence Intensity - Luminescence - Fluorescence Polarization - Luminescence and Chemiluminescence - Luciferase Assays - Realtime Kinetics
Automated Microscope : Automated Cell Culture and Sample Preparation Automated Image Analysis Software: - Drugs affecting Proliferation of Tumor Cells (Microtubuli) - euroregeneration (Differentiation of euronal Cells) - Translocations (Inflammation, Leukemia)
Automated Image Recognition: Inflammation Inactive Leibniz-Institut für Molekulare Pharmakologie Active Picture- Documents Multiparameter- Spreadsheets Cell nucleus: 20.63 524.09 Cytoplasm: 141.46 45.95
Screening Compound Collection Strategy for the Assembly of a Screening Compound Collection
Assembly of a Screening Compound Collection Enriched with Bioactive Scaffolds > 2.000.000 Lowest Estimate of Stable Drug Candidates: 10 13 1 Million Tests / Day 27 300 Years ~ 17.000 (< 1 %) Rational Pre-selection of Bioactive & Chemically Diverse Compounds for ChemBioet
Assembly of a Screening Compound Collection Enriched with Bioactive Scaffolds > 2.000.000 Lowest Estimate of Stable Drug Candidates: 10 13 1 Million Tests / Day 27 300 Years ~ 17.000 (< 1 %) Rational Pre-selection of Bioactive & Chemically Diverse Compounds for ChemBioet
Strategy for the Assembly of a Screening Compound Collection 1 st Step: Removing reactive, unstable and irrelevant Compounds S Hal 2 nd Step: Search for Compounds containing bioactive Substructures, derived from the WDI Hal S S Hal H C C 3 rd Step: Selection of a calculated Diverse Subset C CH 2 I Se 4 th Step: Lipinskis Rule of 5 Self-made Filter / Sybyl (Tripos)
1 st Step: Removing reactive, unstable and irrelevant Compounds S 2 nd Step: Search for Compounds containing bioactive Substructures, derived from the WDI S 3 rd Step: Selection of a calculated Diverse Subset 4 th Step: Lipinskis Rule of 5 Self-made Filter / Sybyl (Tripos)
1 st Step: Removing reactive, unstable and irrelevant Compounds Br Br Br 2 nd Step: Search for Compounds containing bioactive Substructures, derived from the WDI S H F Br S H 3 rd Step: Selection of a calculated Diverse Subset H H H 4 th Step: Lipinskis Rule of 5
1 st Step: Removing reactive, unstable and irrelevant Compounds Br Br Br 2 nd Step: Search for Compounds containing bioactive Substructures, derived from the WDI S H F Br S H 3 rd Step: Selection of a calculated Diverse Subset H H H 4 th Step: Lipinskis Rule of 5
1 st Step: Removing reactive, unstable and irrelevant Compounds Br Br Br 2 nd Step: Search for Compounds containing bioactive Substructures, derived from the WDI S H F Br S H 3 rd Step: Selection of a calculated Diverse Subset H H H 4 th Step: Lipinskis Rule of 5 Diverse Subset Tool / ME (CCG) MW, H ACC, H D,,, RT, Substructures, logp, logs, logd
1 st Step: Removing reactive, unstable and irrelevant Compounds 2 nd Step: Search for Compounds containing bioactive Substructures, derived from the WDI 3 rd Step: Selection of a calculated Diverse Subset 4 th Step: Lipinskis Rule of 5 C. Lipinski et al. (1997) Adv. Drug Del. Rev. 23, 3-25 H-Bond Donors < 5 H-Bond Acceptors <10 LogP < 5 MW < 500 (< 800) Compute Descriptors / ME (CCG)
Where are the Bioactive Substructures derived from? World Drug Index (WDI): Database of 35 000 Biologically Active Small Molecules Search for Maximum Common Substructures: ClassPharmer (BioReason)
Where are the Bioactive Substructures derived from? World Drug Index (WDI): Database of 35 000 Biologically Active Small Molecules Search for Maximum Common Substructures: ClassPharmer (BioReason) CH CH 2 S CH
Where are the Bioactive Substructures derived from? World Drug Index (WDI): Database of 35 000 Biologically Active Small Molecules Search for Maximum Common Substructures: ClassPharmer (BioReason) CH CH 2 S CH 573 Maximum Common Substructures
Screening Projects Recent Successful Example
M. tuberculosis Myo-Inositol-Phosphatase Antagonists Primary Screen: 100 µm Compound Substrate: Sorbitol-6-Phosphate Detection: P i -Malachitegreen-Mo Complex o Inhibition Blank ovel Antagonists with K i < 1 µm Phosphate Reference 500 µm 400 µm 300 µm 200 µm 100 µm 50 µm 0 µm
ovel Small Molecule Antagonist of M. tuberculosis Growth Inhibition in Medium A C* 200 100 50 10 200 100 50 10 µm B Medium only Tb only Growth Inhibition in Macrophages CFU/ml 1.0 10 07 -C 8.0 10 06 6.0 10 06 4.0 10 06 2.0 10 06 1 2 3 4 5 + C Day
FMP: - Med. Chem.: J. Rademann R. Raz M. Schmidt S. Al-Gharabli - Drug Design: R. Kühne - MR: H. schkinat S. Hübel - Screening Unit: J.P. von Kries C. Erdmann S. Behnken V. Pütter M. Schade MDC: K. Hellmuth W. Birchmeier. Rötzschke K. Falk C. Scheidereit E. Wanker M. Lipp MPI, Dortmund: H. Prinz, A. ören H. Waldmann (*HWA) www.chembionet.de Structural Genomics Consortium EMBL-Hamburg: M. Wilmanns M. Weiss P. Tucker MPG-Hamburg: H. Bartunik MPI-IB, Berlin S. Kaufmann SGC M. Sundström S. Knapp University of xford