Title |
Design of a multi-purpose fragment screening library using molecular complexity and orthogonal diversity metrics
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Published in |
Perspectives in Drug Discovery and Design, May 2011
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DOI | 10.1007/s10822-011-9434-0 |
Pubmed ID | |
Authors |
Wan F. Lau, Jane M. Withka, David Hepworth, Thomas V. Magee, Yuhua J. Du, Gregory A. Bakken, Michael D. Miller, Zachary S. Hendsch, Venkataraman Thanabal, Steve A. Kolodziej, Li Xing, Qiyue Hu, Lakshmi S. Narasimhan, Robert Love, Maura E. Charlton, Samantha Hughes, Willem P. van Hoorn, James E. Mills |
Abstract |
Fragment Based Drug Discovery (FBDD) continues to advance as an efficient and alternative screening paradigm for the identification and optimization of novel chemical matter. To enable FBDD across a wide range of pharmaceutical targets, a fragment screening library is required to be chemically diverse and synthetically expandable to enable critical decision making for chemical follow-up and assessing new target druggability. In this manuscript, the Pfizer fragment library design strategy which utilized multiple and orthogonal metrics to incorporate structure, pharmacophore and pharmacological space diversity is described. Appropriate measures of molecular complexity were also employed to maximize the probability of detection of fragment hits using a variety of biophysical and biochemical screening methods. In addition, structural integrity, purity, solubility, fragment and analog availability as well as cost were important considerations in the selection process. Preliminary analysis of primary screening results for 13 targets using NMR Saturation Transfer Difference (STD) indicates the identification of uM-mM hits and the uniqueness of hits at weak binding affinities for these targets. |
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Geographical breakdown
Country | Count | As % |
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United States | 2 | 2% |
Germany | 1 | <1% |
Portugal | 1 | <1% |
Russia | 1 | <1% |
United Kingdom | 1 | <1% |
Unknown | 105 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 33 | 30% |
Student > Ph. D. Student | 26 | 23% |
Student > Master | 11 | 10% |
Student > Bachelor | 8 | 7% |
Student > Doctoral Student | 5 | 5% |
Other | 15 | 14% |
Unknown | 13 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 47 | 42% |
Agricultural and Biological Sciences | 19 | 17% |
Biochemistry, Genetics and Molecular Biology | 15 | 14% |
Computer Science | 5 | 5% |
Medicine and Dentistry | 5 | 5% |
Other | 4 | 4% |
Unknown | 16 | 14% |