Predicting small molecule fluorescent probe localization in living cells using QSAR modeling. 1. Overview and models for probes of structure, properties and function in single cells

Horobin, RW; Rashid‐Doubell, Fiza; Pediani, John D.; Milligan, Graeme

doi:10.3109/10520295.2013.780634

Cited by 111 publications

(92 citation statements)

References 50 publications

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“…Localises in plasma membrane owing to superlipophilic partitioning, or superamphiphilic insertion, or insertion with headgroup trapping, or protein binding [40,105,107] 0 > log P (cationic species) > À4 and AI < 8 pK a > 10 or permanent cation Z > 0 LCF > 17 and W/L > 0.33 and SB < 100…”

Section: Acknowledgementsmentioning

confidence: 99%

“…Localises in nuclear chromatin owing to dsDNA minor groove binding [40,41,70] log P > 8 A I > 8 or if 5 > AI > 3.5 and HGS > 400 (or HGH < À4) or if CBN > 40 and log P > À10…”

Section: Acknowledgementsmentioning

confidence: 99%

“…For meanings of the structure parameter abbreviations, see Table 3; for a wider range of QSAR models, see [40] If And if And if And if Or if Then the dye For original models, see following references 5 > log P > 0 A I < 3.5 Z = 0 5 > log P > 0 and AI < 3.5, but Z < 0 and pK a << 2 Localises in cytosol [103] 6 > log P > 0 6 > AI > 3.5 Z > 0 Localises in endoplasmic reticulum [104] 8 > log P > 5 8 > AI > 5 Localises in generic biomembranes [40] 8 > log P > 0 8 > AI > 3.5 Z = 0 Localises in Golgi membranes [40,105] log P > 5 A I < 3.5 pK a < 6 (if Z > 0)…”

Section: Acknowledgementsmentioning

confidence: 99%

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Where do dyes go inside living cells? Predicting uptake, intracellular localisation, and accumulation using QSAR models

Horobin

2014

Coloration Technology

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Uptake of dyes into living cells and organisms is of concern to several diverse groups of people. These include those not wishing dyes to enter cells (e.g. manufacturers and users of textile dyes, or laboratory workers using dyes as analytical reagents) and those requiring dye entry (e.g. biologists imaging cell contents, or clinicians using photoactive dyes as antitumour drugs). This diversity results in the need to consider an extremely wide range of dyes -and indeed of cells and organisms. An overview of methods for predicting uptake and intracellular localisation is provided, followed by a more detailed account of the concepts and procedures involved in decision-rule quantitative structure-activity relationship (QSAR) models. Some of these models permit the prediction of which dyes are likely to enter cells, and which dyes will be excluded. Other models predict where internalised dyes will localise within the live cells. Use of QSAR models to understand intracellular accumulation, redistribution, loss from the cell, and metabolic modification of dyes is also considered. In particular, the relationship of such predictions to toxicity is discussed. An extended case example is provided, describing the modelling of dye binding to nucleic acids in single-cell systems. A further case example then illustrates dye localisation in multicellular organisms. Finally, conclusions, critiques, and probable future directions concerning the QSAR modelling approach to dye uptake and localisation are given. A summary of key QSAR decision rules in the form of decision logic tabulations is provided.

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Section: Acknowledgementsmentioning

confidence: 99%

“…Localises in nuclear chromatin owing to dsDNA minor groove binding [40,41,70] log P > 8 A I > 8 or if 5 > AI > 3.5 and HGS > 400 (or HGH < À4) or if CBN > 40 and log P > À10…”

Section: Acknowledgementsmentioning

confidence: 99%

Section: Acknowledgementsmentioning

confidence: 99%

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Where do dyes go inside living cells? Predicting uptake, intracellular localisation, and accumulation using QSAR models

Horobin

2014

Coloration Technology

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“…51 These colloidal particles can be active both in biochemical buffers and in cell culture, 52 affecting the rate and mechanism of penetration of drugs, dyes and reagents into cells. 53 We selected 14 purified TCM molecules for this study on the basis of their structures, availability, and frequency of occurrence in the literature. Most of these compounds formed inhibitory colloidal aggregates, often in a concentration range overlapping that reported for on-target activity.…”

Section: Introductionmentioning

confidence: 99%

Colloidal Aggregation and the in Vitro Activity of Traditional Chinese Medicines

et al. 2015

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Traditional Chinese Medicines (TCMs) have been the sole source of therapeutics in China for two millennia. In recent drug discovery efforts, purified components of TCM formulations have shown activity in many in vitro assays, raising concerns of promiscuity. Here, we investigated 14 bioactive small molecules isolated from TCMs for colloidal aggregation. At concentrations commonly used in cell-based or biochemical assay conditions, eight of these compounds formed particles detectable by dynamic light scattering and showed detergent-reversible inhibition against β-lactamase and malate dehydrogenase, two counter-screening enzymes. When tested against their literature-reported molecular targets, three of these eight compounds showed similar reversal of their inhibitory activity in the presence of detergent. For three of the most potent aggregators, contributions to promiscuity via oxidative cycling were investigated; addition of 1 mM DTT had no effect on their activity, which is inconsistent with an oxidative mechanism. TCMs are often active at micromolar concentrations; this study suggests that care must be taken to control for artifactual activity when seeking their primary targets. Implications for the formulation of these molecules are considered.

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“…More extended discussion of these phenomena is provided elsewhere (Horobin and Rashid-Doubell 2013).…”

Section: Advantages and Limitations Of Qsar Decision Rule Modelsmentioning

confidence: 99%

Uptake and localization mechanisms of fluorescent and colored lipid probes. Part 2. QSAR models that predict localization of fluorescent probes used to identify (“specifically stain”) various biomembranes and membranous organelles

Horobin

Rashid‐Doubell

2015

Biotechnic & Histochemistry

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We discuss a variety of biological targets including generic biomembranes and the membranes of the endoplasmic reticulum, endosomes/lysosomes, Golgi body, mitochondria (outer and inner membranes) and the plasma membrane of usual fluidity. For each target, we discuss the access of probes to the target membrane, probe uptake into the membrane and the mechanism of selectivity of the probe uptake. A statement of the QSAR decision rule that describes the required physicochemical features of probes that enable selective staining also is provided, followed by comments on exceptions and limits. Examples of probes typically used to demonstrate each target structure are noted and decision rule tabulations are provided for probes that localize in particular targets; these tabulations show distribution of probes in the conceptual space defined by the relevant structure parameters ("parameter space"). Some general implications and limitations of the QSAR models for probe targeting are discussed including the roles of certain cell and protocol factors that play significant roles in lipid staining. A case example illustrates the predictive ability of QSAR models. Key limiting values of the head group hydrophilicity parameter associated with membrane-probe interactions are discussed in an appendix.

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Predicting small molecule fluorescent probe localization in living cells using QSAR modeling. 1. Overview and models for probes of structure, properties and function in single cells

Cited by 111 publications

References 50 publications

Where do dyes go inside living cells? Predicting uptake, intracellular localisation, and accumulation using QSAR models

Where do dyes go inside living cells? Predicting uptake, intracellular localisation, and accumulation using QSAR models

Colloidal Aggregation and the in Vitro Activity of Traditional Chinese Medicines

Uptake and localization mechanisms of fluorescent and colored lipid probes. Part 2. QSAR models that predict localization of fluorescent probes used to identify (“specifically stain”) various biomembranes and membranous organelles

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