Summary
Phenotypic chemogenomics studies require screening strategies that account for the complex nature of the experimental system. Unknown mechanism of action and high frequency of false positives and false negatives necessitate iterative experiments based on hypotheses formed on the basis of results from the previous step. Process-driven High Throughput Screening (HTS), aiming to “industrialize” lead finding and developed to maximize throughput, is rarely affording sufficient flexibility to design hypothesis-based experiments.
In this contribution, we describe a High Throughput Cherry Picking (HTCP) system based on acoustic dispensing technology that was developed to support a new screening paradigm. We demonstrate the power of hypothesis-based screening in three chemogenomics studies that were recently conducted.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Booth, B. and Zemmel, R. (2004) Prospects for productivity. Nat. Rev. Drug Discov. 3, 451–456.
Mitchison, T. J. (1994) Towards a pharmacological genetics. Chem. Biol. 1, 3–6.
Schreiber, S. L. (1998) Chemical genetics resulting from a passion for synthetic organic chemistry. Bioorg. Med. Chem. 6, 1127–1152.
Chiang, S. L. (2006) Chemical genetics: use of high-throughput screening to identify small-molecule modulators of proteins involved in cellular pathways with the aim of uncovering protein function. In: J. Hüser (ed.) High Throughput-Screening in Drug Discovery. Wiley-VCH, Weinheim, pp. 1–13.
Hertzberg, R. P. and Pope, A. J. (2000) High-throughput screening: new technologies for the 21st century. Curr. Opin. Chem. Biol. 4, 445–451.
Macarron, R. (2006) Critical review of the role of HTS in drug discovery. Drug Discov. Today 11, 277–279.
Lipinski, C. A., Lombardo, F., Dominy, B. W., and Feeney, P. J. (2001) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 46, 3–26.
Zhang, J. H., Chung, T. D. Y., and Oldenburg, K. R. (2000) Confirmation of primary active substances from high throughput screening of chemical and biological populations: a statistical approach and practical considerations. J. Comb. Chem. 2, 258–265.
Malo, N., Hanley, J. A., Cerquozzi, S., Pelletier, J., and Nadon, R. (2006) Statistical practice in high-throughput screening data analysis. Nat. Biotechnol. 24, 167–175.
Padmanabha, R., Cook, L., and Gill, J. (2005) HTS quality control and data analysis: a process to maximize information from a high-throughput screen. Comb. Chem. High Throughput Screen. 8, 512–527.
Alanine, A., Nettekoven, M., Roberts, E., and Thomas, A. W. (2003) Lead generation – enhancing the success of drug discovery by investing in the hit to lead process. Comb. Chem. High Throughput Screen. 6, 51–66.
Schopfer, U., Engeloch, C., Stanek, J., Girod, M., Schuffenhauer, A., Jacoby, E., and Acklin, P. (2005) The Novartis compound archive - from concept to reality. Comb. Chem. High Throughput Screen. 8, 513–519.
Scheel, G., Pfeiffer, M. J. (2009) Long-Term Storage of Compound Solutions for High Throughput Screening by Using a Novel 1536-Well Microplate. J. Biomol. Screen. 14, 492–498.
Engeloch, C., Schopfer, U., Muckenschnabel, I., Le Goff, F., Mees, H., Boesch, K., Hueber, M., and Popov, M. (2008) Stability of screening compounds in wet DMSO. J. Biomol. Screen. 13, 999–1006.
Slee, A. M., Wuonola, M. A., McRipley, R. J., Zajac, I., Zawada, M. J., Bartholomew, P. T., Gregory, W. A., and Forbes, M. (1987) Oxazolidinones, a new class of synthetic antibacterial agents: invitro and invivo activities of DuP 105 and DuP 721. Antimicrob. Agents Chemother. 31, 1791–1797.
Projan, S. J. and Bradford, P. A. (2007) Late stage antibacterial drugs in the clinical pipeline. Curr. Opin. Microbiol. 10, 441–446.
Payne, D. J., Gwynn, M. N., Holmes, D. J., and Pompliano, D. L. (2007) Drugs for bad bugs: confronting the challenges of antibacterial discovery. Nat. Rev. Drug Discov. 6, 29–40.
O’Brien, J., Wilson, I., Orton, T., and Pognan, F. (2000) Investigation of the Alamar Blue (resazurin) fluorescent dye for the assessment of mammalian cell cytotoxicity. Eur. J. Biochem. 267, 5421–5426.
Lipinski, C. A., Lombardo, F., Dominy, B. W., and Feeney, P. J. (1997) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 23, 3–25.
Egan, W. J., Merz, K. M. Jr., and Baldwin, J. J. (2000) Prediction of drug absorption using multivariate statistics. J. Med. Chem. 43, 3867–3877.
National Committee for Clinical Laboratory Standards (2003) Methods for Dilution Antimicrobial Susceptibility Test for Bacteria That Grow Aerobically; Approved Standard – Sixth Edition. NCCLS document M7-A6. NCCLS, Wayne, PA.
Acknowledgments
Drs E. Jacoby and P. Fürst (both NIBR associates) are acknowledged for support and discussions.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Humana Press, a part of Springer Science+Business Media, LLC
About this protocol
Cite this protocol
Schopfer, U. et al. (2009). Hypothesis-Driven Screening. In: Jacoby, E. (eds) Chemogenomics. Methods in Molecular Biology, vol 575. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60761-274-2_13
Download citation
DOI: https://doi.org/10.1007/978-1-60761-274-2_13
Published:
Publisher Name: Humana Press, Totowa, NJ
Print ISBN: 978-1-60761-273-5
Online ISBN: 978-1-60761-274-2
eBook Packages: Springer Protocols