ArticleProceedings of the National Academy of Sciences of the United States of America2011
Direct inference of protein-DNA interactions using compressed sensing methods.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 26 citations in OpenAlex.
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- Biophysical prediction of protein-peptide interactions and signaling networks using machine learning.Nature methods · 2020Article
- An affinity-structure database of helix-turn-helix: DNA complexes with a universal coordinate system.BMC bioinformatics · 2015Article
- A multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks.Nature genetics · 2014Article
- Article
- Computational methodology for ChIP-seq analysis.Quantitative biology (Beijing, China) · 2013Article
- Computational prediction of broadly neutralizing HIV-1 antibody epitopes from neutralization activity data.PloS one · 2013Article
- Improved predictions of transcription factor binding sites using physicochemical features of DNA.Nucleic acids research · 2012Article
- Application of compressed sensing to the simulation of atomic systems.Proceedings of the National Academy of Sciences of the United States of America · 2012Article
- Atomistic modeling of protein-DNA interaction specificity: progress and applications.Current opinion in structural biology · 2012Review
- 3DTF: a web server for predicting transcription factor PWMs using 3D structure-based energy calculations.Nucleic acids research · 2012Article
- (Compressed) sensing and sensibility.Proceedings of the National Academy of Sciences of the United States of America · 2011Article
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2 authors at 1 institution in 1 country.
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Abstract
Compressed sensing has revolutionized signal acquisition, by enabling complex signals to be measured with remarkable fidelity using a small number of so-called incoherent sensors. We show that molecular interactions, e.g., protein-DNA interactions, can be analyzed in a directly analogous manner and with similarly remarkable results. Specifically, mesoscopic molecular interactions act as incoherent sensors that measure the energies of microscopic interactions between atoms. We combine concepts from compressed sensing and statistical mechanics to determine the interatomic interaction energies of a molecular system exclusively from experimental measurements, resulting in a "de novo" energy potential. In contrast, conventional methods for estimating energy potentials are based on theoretical models premised on a priori assumptions and extensive domain knowledge. We determine the de novo energy potential for pairwise interactions between protein and DNA atoms from (i) experimental measurements of the binding affinity of protein-DNA complexes and (ii) crystal structures of the complexes. We show that the de novo energy potential can be used to predict the binding specificity of proteins to DNA with approximately 90% accuracy, compared to approximately 60% for the best performing alternative computational methods applied to this fundamental problem. This de novo potential method is directly extendable to other biomolecule interaction domains (enzymes and signaling molecule interactions) and to other classes of molecular interactions.
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