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Review
. 2009 Dec;13(5-6):539-48.
doi: 10.1016/j.cbpa.2009.09.018. Epub 2009 Oct 12.

Connecting synthetic chemistry decisions to cell and genome biology using small-molecule phenotypic profiling

Bridget K Wagner  1 , Paul A Clemons
Affiliations
Review

Connecting synthetic chemistry decisions to cell and genome biology using small-molecule phenotypic profiling

Bridget K Wagner et al. Curr Opin Chem Biol. 2009 Dec.

Abstract

Discovering small-molecule modulators for thousands of gene products requires multiple stages of biological testing, specificity evaluation, and chemical optimization. Many cellular profiling methods, including cellular sensitivity, gene expression, and cellular imaging, have emerged as methods to assess the functional consequences of biological perturbations. Cellular profiling methods applied to small-molecule science provide opportunities to use complex phenotypic information to prioritize and optimize small-molecule structures simultaneously against multiple biological endpoints. As throughput increases and cost decreases for such technologies, we see an emerging paradigm of using more information earlier in probe-discovery and drug-discovery efforts. Moreover, increasing access to public datasets makes possible the construction of 'virtual' profiles of small-molecule performance, even when multiplexed measurements were not performed or when multidimensional profiling was not the original intent. We review some key conceptual advances in small-molecule phenotypic profiling, emphasizing connections to other information, such as protein-binding measurements, genetic perturbations, and cell states. We argue that to maximally leverage these measurements in probe-discovery and drug-discovery requires a fundamental connection to synthetic chemistry, allowing the consequences of synthetic decisions to be described in terms of changes in small-molecule profiles. Mining such data in the context of chemical structure and synthesis strategies can inform decisions about chemistry procurement and library development, leading to optimal small-molecule screening collections.

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Figures

Figure 1
Figure 1. General conceptual framework for phenotypic profiling of small molecules
Measurement data are integrated (details depending on the measurement types) to afford computational vector representations of each compound in the measurement “space”, after which similarities between profiles can be computed for each pair of compounds. Most profiling studies rely on “landmark” compounds to connect new compounds to compounds with known mechanisms of action. Some chemistry-centric studies, highlighted in this review, attempt to uncover relationships between profile similarities and decisions made during small-molecule library synthesis.
Figure 2
Figure 2. Connectivity of small molecules with molecular targets using the NCI-60 cell lines [11]
Matrix algebra was adapted to produce clustered correlations between 3,989 small molecules and 76 molecular targets (represented by 113 cellular “features”) using the “common language” of 60 cancer cell lines in which both small-molecule sensitivity and protein expression (or function) levels were measured.
Figure 3
Figure 3. Conceptual framework for connecting protein-binding measurements with cell-based assay measurements using small molecules as the connecting dimension
Compounds might be used to directly connect protein-binding assays to cell-based assay measurements when each has been exposed to a common compound collection. A simple implementation would entail comparing the number of shared “hits” to random expectation.
Figure 4
Figure 4. Example of applying phenotypic profiling to understanding consequences of synthetic chemistry decisions [62]
Forty cell-based assay measurements were made on each member of a library of compounds with specific variation in skeletal and stereochemical elements, revealing that patterns of performance correspond to decisions in library synthesis (see text). Images were reproduced in modified form with permission from the J. Am. Chem. Soc.
Figure 5
Figure 5. Example of applying phenotypic profile similarity to select subsets of stereochemical features correlated with patterns of biological performance [13]
Ten cell-based assay measurements were made at eight concentrations on each member of a library of compounds with specific variations in stereochemical elements. Whereas stereochemical similarity defined by all possible stereocenters showed little relationship to profile similarity, selecting a subset of descriptors identified those stereocenters correlated with particular patterns of biological performance (see text). Images were reproduced in modified form with permission from the J. Am. Chem. Soc.
Figure 6
Figure 6. Conceptual framework for connecting small-molecule substructure features with cell-based assay measurements using small-molecules as the connecting dimension
As suggested by Weinstein [11], compounds might be used to directly connect small-molecule substructures to assay outcomes. Such methods might benefit from first restricting the chemical structure representation (see text).
See this image and copyright information in PMC

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