A systems approach to measuring the binding energy landscapes of transcription factors.
Open accessAbstract
A major goal of systems biology is to predict the function of biological networks. Although network topologies have been successfully determined in many cases, the quantitative parameters governing these networks generally have not. Measuring affinities of molecular interactions in high-throughput format remains problematic, especially for transient and low-affinity interactions. We describe a high-throughput microfluidic platform that measures such properties on the basis of mechanical trapping of molecular interactions. With this platform we characterized DNA binding energy landscapes for four eukaryotic transcription factors; these landscapes were used to test basic assumptions about transcription factor binding and to predict their in vivo function.
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High-throughput methods for measuring biochemical parameters remain limited.
“While high-throughput methods for discovering interactions are well-developed [7], high-throughput methods for measuring biochemical parameters remain limited [8].”
From Universally Sloppy Parameter Sensitivities in Systems Biology Models (2007) · cites this paper as [8]
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“[8] Maerkl SJ, Quake SR (2007) A systems approach to measuring the binding energy landscapes of transcription factors.”
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- Authors
- Maerkl, S. J., & Quake, S. R.
- Affiliations
- California Institute of Technology (US)
- Corresponding author
- Quake, Stephen R.
- Venue
- Science
- Published
- 2007-01-12
- Volume
- 315
- Issue
- 5809
- Pages
- 233-237
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2038282326
- Cited by
- 584
- References
- 1
- Citations by year
- 2026: 11 · 2025: 18 · 2024: 16 · 2023: 24 · 2022: 19 · 2021: 15 · 2020: 31 · 2019: 31 · 2018: 21 · 2017: 36 · 2016: 28 · 2015: 36 · 2014: 44 · 2013: 45 · 2012: 45
- FWCI
- 16.57
- Type
- journal article
- Language
- en
- Open access
- green
- infoscience.epfl.ch
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, cc-by)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced biosensing and bioanalysis techniques
- Keywords
- transcription factors, binding affinity measurement, microfluidic platform, low-affinity interactions, transient interactions
- MeSH terms
- Base Sequence, Computer Simulation, DNA, DNA-Binding Proteins, DNA, Fungal, Humans, Protein Binding, Regulatory Sequences, Nucleic Acid, Repressor Proteins, Saccharomyces cerevisiae, Templates, Genetic, Thermodynamics, Transcription Factors, Gene Expression Regulation, Fungal, Helix-Loop-Helix Motifs, Computational Biology, Protein Isoforms, Oligonucleotide Array Sequence Analysis, E-Box Elements, Saccharomyces cerevisiae Proteins, Microfluidic Analytical Techniques, Systems Biology, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Basic Helix-Loop-Helix Transcription Factors, Basic Helix-Loop-Helix Proteins
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