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Min KA, Zhang X, Yu JY, Rosania GR. Computational approaches to analyse and predict small molecule transport and distribution at cellular and subcellular levels. Biopharm Drug Dispos 2013; 35:15-32. [PMID: 24218242 DOI: 10.1002/bdd.1879] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2013] [Revised: 10/15/2013] [Accepted: 11/01/2013] [Indexed: 12/31/2022]
Abstract
Quantitative structure-activity relationship (QSAR) studies and mechanistic mathematical modeling approaches have been independently employed for analysing and predicting the transport and distribution of small molecule chemical agents in living organisms. Both of these computational approaches have been useful for interpreting experiments measuring the transport properties of small molecule chemical agents, in vitro and in vivo. Nevertheless, mechanistic cell-based pharmacokinetic models have been especially useful to guide the design of experiments probing the molecular pathways underlying small molecule transport phenomena. Unlike QSAR models, mechanistic models can be integrated from microscopic to macroscopic levels, to analyse the spatiotemporal dynamics of small molecule chemical agents from intracellular organelles to whole organs, well beyond the experiments and training data sets upon which the models are based. Based on differential equations, mechanistic models can also be integrated with other differential equations-based systems biology models of biochemical networks or signaling pathways. Although the origin and evolution of mathematical modeling approaches aimed at predicting drug transport and distribution has occurred independently from systems biology, we propose that the incorporation of mechanistic cell-based computational models of drug transport and distribution into a systems biology modeling framework is a logical next step for the advancement of systems pharmacology research.
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Affiliation(s)
- Kyoung Ah Min
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, Ann Arbor, MI, 48109, USA
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2
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Rosania GR, Shedden K, Zheng N, Zhang X. Visualizing chemical structure-subcellular localization relationships using fluorescent small molecules as probes of cellular transport. J Cheminform 2013; 5:44. [PMID: 24093553 PMCID: PMC3852740 DOI: 10.1186/1758-2946-5-44] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2013] [Accepted: 10/01/2013] [Indexed: 12/12/2022] Open
Abstract
Background To study the chemical determinants of small molecule transport inside cells, it is crucial to visualize relationships between the chemical structure of small molecules and their associated subcellular distribution patterns. For this purpose, we experimented with cells incubated with a synthetic combinatorial library of fluorescent, membrane-permeant small molecule chemical agents. With an automated high content screening instrument, the intracellular distribution patterns of these chemical agents were microscopically captured in image data sets, and analyzed off-line with machine vision and cheminformatics algorithms. Nevertheless, it remained challenging to interpret correlations linking the structure and properties of chemical agents to their subcellular localization patterns in large numbers of cells, captured across large number of images. Results To address this challenge, we constructed a Multidimensional Online Virtual Image Display (MOVID) visualization platform using off-the-shelf hardware and software components. For analysis, the image data set acquired from cells incubated with a combinatorial library of fluorescent molecular probes was sorted based on quantitative relationships between the chemical structures, physicochemical properties or predicted subcellular distribution patterns. MOVID enabled visual inspection of the sorted, multidimensional image arrays: Using a multipanel desktop liquid crystal display (LCD) and an avatar as a graphical user interface, the resolution of the images was automatically adjusted to the avatar’s distance, allowing the viewer to rapidly navigate through high resolution image arrays, zooming in and out of the images to inspect and annotate individual cells exhibiting interesting staining patterns. In this manner, MOVID facilitated visualization and interpretation of quantitative structure-localization relationship studies. MOVID also facilitated direct, intuitive exploration of the relationship between the chemical structures of the probes and their microscopic, subcellular staining patterns. Conclusion MOVID can provide a practical, graphical user interface and computer-assisted image data visualization platform to facilitate bioimage data mining and cheminformatics analysis of high content, phenotypic screening experiments.
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Affiliation(s)
- Gus R Rosania
- Department of Pharmaceutical Sciences, University of Michigan College of Pharmacy, 428 Church Street, Ann Arbor, MI 48109, USA.
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Natesan S, Wang T, Lukacova V, Bartus V, Khandelwal A, Subramaniam R, Balaz S. Cellular quantitative structure-activity relationship (Cell-QSAR): conceptual dissection of receptor binding and intracellular disposition in antifilarial activities of Selwood antimycins. J Med Chem 2012; 55:3699-712. [PMID: 22468611 PMCID: PMC3338160 DOI: 10.1021/jm201371y] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
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We present the cellular quantitative structure–activity
relationship (cell-QSAR) concept that adapts ligand-based and receptor-based
3D-QSAR methods for use with cell-level activities. The unknown intracellular
drug disposition is accounted for by the disposition function (DF),
a model-based, nonlinear function of a drug’s lipophilicity,
acidity, and other properties. We conceptually combined the DF with
our multispecies, multimode version of the frequently used ligand-based
comparative molecular field analysis (CoMFA) method, forming a single
correlation function for fitting the cell-level activities. The resulting
cell-QSAR model was applied to the Selwood data on filaricidal activities
of antimycin analogues. Their molecules are flexible, ionize under
physiologic conditions, form different intramolecular H-bonds for
neutral and ionized species, and cross several membranes to reach
unknown receptors. The calibrated cell-QSAR model is significantly
more predictive than other models lacking the disposition part and
provides valuable structure optimization clues by factorizing the
cell-level activity of each compound into the contributions of the
receptor binding and disposition.
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Affiliation(s)
- Senthil Natesan
- Albany College of Pharmacy and Health Sciences, Vermont Campus, Colchester, Vermont 05446, USA
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4
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Pacini S, Morucci G, Ruggiero M, Gulisano M, Punzi T. Tensegrity and plasma for skin regeneration. Skin Res Technol 2011; 18:356-63. [DOI: 10.1111/j.1600-0846.2011.00576.x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/06/2010] [Indexed: 01/16/2023]
Affiliation(s)
- Stefania Pacini
- Department of Anatomy, Histology and Forensic Medicine; University of Firenze; Italy
| | - Gabriele Morucci
- Department of Anatomy, Histology and Forensic Medicine; University of Firenze; Italy
| | - Marco Ruggiero
- Department of Experimental Pathology and Oncology; University of Firenze; Italy
| | - Massimo Gulisano
- Department of Anatomy, Histology and Forensic Medicine; University of Firenze; Italy
| | - Tiziana Punzi
- Department of Anatomy, Histology and Forensic Medicine; University of Firenze; Italy
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Zheng N, Tsai HN, Zhang X, Rosania GR. The subcellular distribution of small molecules: from pharmacokinetics to synthetic biology. Mol Pharm 2011; 8:1619-28. [PMID: 21805990 DOI: 10.1021/mp200092v] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The systemic pharmacokinetics and pharmacodynamics of small molecules are determined by subcellular transport phenomena. Although approaches used to study the subcellular distribution of small molecules have gradually evolved over the past several decades, experimental analysis and prediction of cellular pharmacokinetics remains a challenge. In this review, we survey the progress of subcellular distribution research since the 1960s, with a focus on the advantages, disadvantages and limitations of the various experimental techniques. Critical review of the existing body of knowledge points to many opportunities to advance the rational design of organelle-targeted chemical agents. These opportunities include (1) development of quantitative, non-fluorescence-based, whole cell methods and techniques to measure the subcellular distribution of chemical agents in multiple compartments; (2) exploratory experimentation with nonspecific transport probes that have not been enriched with putative, organelle-targeting features; (3) elaboration of hypothesis-driven, mechanistic and modeling-based approaches to guide experiments aimed at elucidating subcellular distribution and transport; and (4) introduction of revolutionary conceptual approaches borrowed from the field of synthetic biology combined with cutting edge experimental strategies. In our laboratory, state-of-the-art subcellular transport studies are now being aimed at understanding the formation of new intracellular membrane structures in response to drug therapy, exploring the function of drug-membrane complexes as intracellular drug depots, and synthesizing new organelles with extraordinary physical and chemical properties.
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Affiliation(s)
- Nan Zheng
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, Ann Arbor, Michigan 48109, United States
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Abstract
Chemical address tags can be defined as specific structural features shared by a set of bioimaging probes having a predictable influence on cell-associated visual signals obtained from these probes. Here, using a large image dataset acquired with a high content screening instrument, machine vision and cheminformatics analysis have been applied to reveal chemical address tags. With a combinatorial library of fluorescent molecules, fluorescence signal intensity, spectral, and spatial features characterizing each one of the probes' visual signals were extracted from images acquired with the three different excitation and emission channels of the imaging instrument. With multivariate regression, the additive contribution from each one of the different building blocks of the bioimaging probes toward each measured, cell-associated image-based feature was calculated. In this manner, variations in the chemical features of the molecules were associated with the resulting staining patterns, facilitating quantitative, objective analysis of chemical address tags. Hierarchical clustering and paired image-cheminformatics analysis revealed key structure-property relationships amongst many building blocks of the fluorescent molecules. The results point to different chemical modifications of the bioimaging probes that can exert similar (or different) effects on the probes' visual signals. Inspection of the clustered structures suggests intramolecular charge migration or partial charge distribution as potential mechanistic determinants of chemical address tag behavior.
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Affiliation(s)
- Kerby Shedden
- Department of Statistics, University of Michigan, Ann Arbor, Michigan 48109, USA
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Kim YK, Ha HH, Lee JS, Bi X, Ahn YH, Hajar S, Lee JJ, Chang YT. Control of Muscle Differentiation by a Mitochondria-Targeted Fluorophore. J Am Chem Soc 2009; 132:576-9. [DOI: 10.1021/ja906862g] [Citation(s) in RCA: 56] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Yun Kyung Kim
- Department of Chemistry, New York University, New York, New York 10003, Department of Chemistry, MedChem Program of Life Sciences Institute, National University of Singapore, Singapore 117543, Laboratory of Bioimaging Probe Development, Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Biopolis, Singapore 138667
| | - Hyung-Ho Ha
- Department of Chemistry, New York University, New York, New York 10003, Department of Chemistry, MedChem Program of Life Sciences Institute, National University of Singapore, Singapore 117543, Laboratory of Bioimaging Probe Development, Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Biopolis, Singapore 138667
| | - Jun-Seok Lee
- Department of Chemistry, New York University, New York, New York 10003, Department of Chemistry, MedChem Program of Life Sciences Institute, National University of Singapore, Singapore 117543, Laboratory of Bioimaging Probe Development, Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Biopolis, Singapore 138667
| | - Xuezhi Bi
- Department of Chemistry, New York University, New York, New York 10003, Department of Chemistry, MedChem Program of Life Sciences Institute, National University of Singapore, Singapore 117543, Laboratory of Bioimaging Probe Development, Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Biopolis, Singapore 138667
| | - Young-Hoon Ahn
- Department of Chemistry, New York University, New York, New York 10003, Department of Chemistry, MedChem Program of Life Sciences Institute, National University of Singapore, Singapore 117543, Laboratory of Bioimaging Probe Development, Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Biopolis, Singapore 138667
| | - Siti Hajar
- Department of Chemistry, New York University, New York, New York 10003, Department of Chemistry, MedChem Program of Life Sciences Institute, National University of Singapore, Singapore 117543, Laboratory of Bioimaging Probe Development, Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Biopolis, Singapore 138667
| | - Jae-Jung Lee
- Department of Chemistry, New York University, New York, New York 10003, Department of Chemistry, MedChem Program of Life Sciences Institute, National University of Singapore, Singapore 117543, Laboratory of Bioimaging Probe Development, Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Biopolis, Singapore 138667
| | - Young-Tae Chang
- Department of Chemistry, New York University, New York, New York 10003, Department of Chemistry, MedChem Program of Life Sciences Institute, National University of Singapore, Singapore 117543, Laboratory of Bioimaging Probe Development, Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A*STAR), Biopolis, Singapore 138667
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Shedden K, Li Q, Liu F, Chang YT, Rosania GR. Machine vision-assisted analysis of structure-localization relationships in a combinatorial library of prospective bioimaging probes. Cytometry A 2009; 75:482-93. [PMID: 19243023 DOI: 10.1002/cyto.a.20713] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
With a combinatorial library of bioimaging probes, it is now possible to use machine vision to analyze the contribution of different building blocks of the molecules to their cell-associated visual signals. For this purpose, cell-permeant, fluorescent styryl molecules were synthesized by condensation of 168 aldehyde with 8 pyridinium/quinolinium building blocks. Images of cells incubated with fluorescent molecules were acquired with a high content screening instrument. Chemical and image feature analysis revealed how variation in one or the other building block of the styryl molecules led to variations in the molecules' visual signals. Across each pair of probes in the library, chemical similarity was significantly associated with spectral and total signal intensity similarity. However, chemical similarity was much less associated with similarity in subcellular probe fluorescence patterns. Quantitative analysis and visual inspection of pairs of images acquired from pairs of styryl isomers confirm that many closely-related probes exhibit different subcellular localization patterns. Therefore, idiosyncratic interactions between styryl molecules and specific cellular components greatly contribute to the subcellular distribution of the styryl probes' fluorescence signal. These results demonstrate how machine vision and cheminformatics can be combined to analyze the targeting properties of bioimaging probes, using large image data sets acquired with automated screening systems.
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Affiliation(s)
- Kerby Shedden
- Department of Statistics, University of Michigan, Ann Arbor, Michigan 48109, USA
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Affiliation(s)
- Stefan Balaz
- Department of Pharmaceutical Sciences, College of Pharmacy, North Dakota State University, Fargo, North Dakota 58105, USA.
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Simulation-based cheminformatic analysis of organelle-targeted molecules: lysosomotropic monobasic amines. J Comput Aided Mol Des 2008; 22:629-45. [PMID: 18338229 PMCID: PMC2516532 DOI: 10.1007/s10822-008-9194-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2007] [Accepted: 02/05/2008] [Indexed: 11/18/2022]
Abstract
Cell-based molecular transport simulations are being developed to facilitate exploratory cheminformatic analysis of virtual libraries of small drug-like molecules. For this purpose, mathematical models of single cells are built from equations capturing the transport of small molecules across membranes. In turn, physicochemical properties of small molecules can be used as input to simulate intracellular drug distribution, through time. Here, with mathematical equations and biological parameters adjusted so as to mimic a leukocyte in the blood, simulations were performed to analyze steady state, relative accumulation of small molecules in lysosomes, mitochondria, and cytosol of this target cell, in the presence of a homogenous extracellular drug concentration. Similarly, with equations and parameters set to mimic an intestinal epithelial cell, simulations were also performed to analyze steady state, relative distribution and transcellular permeability in this non-target cell, in the presence of an apical-to-basolateral concentration gradient. With a test set of ninety-nine monobasic amines gathered from the scientific literature, simulation results helped analyze relationships between the chemical diversity of these molecules and their intracellular distributions.
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Zhang X, Shedden K, Rosania GR. A cell-based molecular transport simulator for pharmacokinetic prediction and cheminformatic exploration. Mol Pharm 2007; 3:704-16. [PMID: 17140258 PMCID: PMC2710883 DOI: 10.1021/mp060046k] [Citation(s) in RCA: 33] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
In the body, cell monolayers serve as permeability barriers, determining transport of molecules from one organ or tissue compartment to another. After oral drug administration, for example, transport across the epithelial cell monolayer lining the lumen of the intestine determines the fraction of drug in the gut that is absorbed by the body. By modeling passive transcellular transport properties in the presence of an apical to basolateral concentration gradient, we demonstrate how a computational, cell-based molecular transport simulator can be used to define a physicochemical property space occupied by molecules with desirable permeability and intracellular retention characteristics. Considering extracellular domains of cell surface receptors located on the opposite side of a cell monolayer as a drug's desired site of action, simulation of transcellular transport can be used to define the physicochemical properties of molecules with maximal transcellular permeability but minimal intracellular retention. Arguably, these molecules would possess very desirable features: least likely to exhibit nonspecific toxicity, metabolism, and side effects associated with high (undesirable) intracellular accumulation; and most likely to exhibit favorable bioavailability and efficacy associated with maximal rates of transport across cells and minimal intracellular retention, resulting in (desirable) accumulation at the extracellular site of action. Simulated permeability values showed good correlations with PAMPA, Caco-2, and intestinal permeability measurements, without "training" the model and without resorting to statistical regression techniques to "fit" the data. Therefore, cell-based molecular transport simulators could be useful in silico screening tools for chemical genomics and drug discovery.
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Affiliation(s)
- Xinyuan Zhang
- Department of Pharmaceutical Science, University of Michigan College of Pharmacy, Ann Arbor, MI 48109
| | - Kerby Shedden
- Department of Statistics, University of Michigan, Ann Arbor, MI 48109
| | - Gus R. Rosania
- Department of Pharmaceutical Science, University of Michigan College of Pharmacy, Ann Arbor, MI 48109
- CORRESPONDING AUTHOR: Gus R. Rosania, Ph.D., Department of Pharmaceutical Sciences, University of Michigan College of Pharmacy, 428 Church Street, Ann Arbor, MI 48109. . Phone: 734-763-1032. Fax: 734-615-6162
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12
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Rosania GR, Crippen G, Woolf P, States D, Shedden K. A Cheminformatic Toolkit for Mining Biomedical Knowledge. Pharm Res 2007; 24:1791-802. [PMID: 17385012 DOI: 10.1007/s11095-007-9285-5] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2007] [Accepted: 02/27/2007] [Indexed: 01/31/2023]
Abstract
PURPOSE Cheminformatics can be broadly defined to encompass any activity related to the application of information technology to the study of properties, effects and uses of chemical agents. One of the most important current challenges in cheminformatics is to allow researchers to search databases of biomedical knowledge, using chemical structures as input. MATERIALS AND METHODS An important step towards this goal was the establishment of PubChem, an open, centralized database of small molecules accessible through the World Wide Web. While PubChem is primarily intended to serve as a repository for high throughput screening data from federally-funded screening centers and academic research laboratories, the major impact of PubChem could also reside in its ability to serve as a chemical gateway to biomedical databases such as PubMed. CONCLUSION This article will review cheminformatic tools that can be applied to facilitate annotation of PubChem through links to the scientific literature; to integrate PubChem with transcriptomic, proteomic, and metabolomic datasets; to incorporate results of numerical simulations of physiological systems into PubChem annotation; and ultimately, to translate data of chemical genomics screening efforts into information that will benefit biomedical researchers and physician scientists across all therapeutic areas.
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Affiliation(s)
- Gus R Rosania
- Department of Pharmaceutical Sciences, University of Michigan College of Pharmacy, 428 Church Street, Ann Arbor, MI 48109, USA.
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Shedden K, Posada MM, Chang YT, Li Q, Rosania G. Prospecting for Live Cell BioImaging Probes With Cheminformatic Assisted Image Arrays (CAIA). PROCEEDINGS. IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING 2007:1108-1111. [PMID: 23482717 DOI: 10.1109/isbi.2007.357050] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
High-throughput microscopic screening instruments can generate huge collections of images of live cells incubated with combinatorial libraries of fluorescent molecules. Organizing and visualizing these images to discern biologically important patterns that link back to chemical structure is a challenge. We present an analysis and visualization methodology - Cheminformatic Assisted Image Array (CAIA) - that greatly facilitates data mining efforts. For illustration, we considered a collection of microscopic images acquired from cells incubated with each member of a combinatorial library of styryl molecules being screened for candidate bioimaging probes. By sorting CAIAs based on quantitative image features, the relative contribution of each combinatorial building block on probe intracellular distribution could be visually discerned. The results revealed trends hidden in the dataset: most interestingly, the building blocks of the styryl molecules appeared to behave as chemical address tags, additively and independently encoding spatial patterns of intracellular fluorescence. Translated into practice, CAIA facilitated discovery of several outstanding styryl molecules for live cell nuclear imaging applications.
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Affiliation(s)
- Kerby Shedden
- Department of Statistics, University of Michigan, Ann Arbor, MI 48109
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Abstract
Much of the attention devoted to the elucidation of multidrug-resistance mechanisms in tumor cells has focused on transmembrane drug transporters and their ability to pump drug molecules from the cytosol to the extracellular medium. However, intracellular drug concentrations often remain high in drug-resistant cells and therefore do not explain how drug pumping at the plasma membrane confers multidrug resistance. Recent work indicates how drug sequestration in cytoplasmic organelles can account for these paradoxical results and how cellular pharmacokinetics may be exploited to target the activity of small molecules to specific cell types.
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Affiliation(s)
- Vivien Y Chen
- Department of Pharmaceutical Sciences, University of Michigan College of Pharmacy, 428 Church Street, Ann Arbor, Michigan 48109, USA
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