Predicting Target DNA Sequences of DNA-Binding Proteins Based on Unbound Structures

Chen, Chien‐Yu; Chien, Ting-Ying; Lin, Cheng-Kai; Lin, Chih‐Wei; Weng, Yi-Zhong; Chang, Darby Tien-Hao

doi:10.1371/journal.pone.0030446

Cited by 23 publications

(30 citation statements)

References 31 publications

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“…However, methods utilizing 3D structures of TFs do not have these limitations. With an increasing number of solved structures of protein/DNA complexes in Protein Data Bank (PDB) [9], it is becoming more common to identify TFBSs using structural information of solved protein/DNA complexes [10]–[29].…”

Section: Introductionmentioning

confidence: 99%

A Structural-Based Strategy for Recognition of Transcription Factor Binding Sites

Schones

Wang

et al. 2013

PLoS ONE

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Scanning through genomes for potential transcription factor binding sites (TFBSs) is becoming increasingly important in this post-genomic era. The position weight matrix (PWM) is the standard representation of TFBSs utilized when scanning through sequences for potential binding sites. However, many transcription factor (TF) motifs are short and highly degenerate, and methods utilizing PWMs to scan for sites are plagued by false positives. Furthermore, many important TFs do not have well-characterized PWMs, making identification of potential binding sites even more difficult. One approach to the identification of sites for these TFs has been to use the 3D structure of the TF to predict the DNA structure around the TF and then to generate a PWM from the predicted 3D complex structure. However, this approach is dependent on the similarity of the predicted structure to the native structure. We introduce here a novel approach to identify TFBSs utilizing structure information that can be applied to TFs without characterized PWMs, as long as a 3D complex structure (TF/DNA) exists. This approach utilizes an energy function that is uniquely trained on each structure. Our approach leads to increased prediction accuracy and robustness compared with those using a more general energy function. The software is freely available upon request.

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Section: Introductionmentioning

confidence: 99%

A Structural-Based Strategy for Recognition of Transcription Factor Binding Sites

Schones

Wang

et al. 2013

PLoS ONE

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“…40–42 Recent advances in array and sequencing technologies allow genome-wide studies of chromatin modifications. In particular, histones and their post translational modifications serve as key epigenetic marks that are extensively mapped on genomic scale due to their role in gene expression and in chromatin packaging.…”

Section: Epigenomic Bulk Studiesmentioning

confidence: 99%

Toward Single-Molecule Optical Mapping of the Epigenome

et al. 2013

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The last decade has seen an explosive growth in the utilization of single-molecule techniques for the study of complex systems. The ability to resolve phenomena otherwise masked by ensemble averaging has made these approaches especially attractive for the study of biological systems, where stochastic events lead to inherent inhomogeneity on the population level. The complex composition of the genome has made it an ideal system to study on the single-molecule level and methods aimed at resolving genetic information from long, individual, genomic DNA molecules have been in use for the last 30 years. These methods, and particularly optical based mapping of DNA, have been instrumental in highlighting genomic variation and contributed significantly to the assembly of many genomes including the human genome. Nanotechnology and nanoscopy have been a strong driving force for advancing genomic mapping approaches, allowing both better manipulation of DNA on the nano-scale and enhanced optical resolving power for analysis of genomic information. In the very last years, these developments have been adopted also for epigenetic studies. The common principle for these studies is the use of advanced optical microscopy for the detection of fluorescently labeled epigenetic marks on long, extended DNA molecules. Here we will discuss recent single-molecule studies for the mapping of chromatin composition and epigenetic DNA modifications, such as DNA methylation.

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“…However, (16) also showed that performance may degrade in unbound queries if conformational changes occur upon DNA binding. Therefore, users are encouraged to compare predictions using different templates for figuring out the positions in the predicted PWMs with high confidence.…”

Section: Evaluation and Case Studiesmentioning

confidence: 99%

“…This query protein was selected from the seven testing proteins used in (16) by the following procedures. We queried the seven protein names in the AH-DB (26), a database of protein structure pairs before and after binding, and the query structure (1G6N) turned out to be the unbound structure with the largest root-mean-square deviation (RMSD) of 4.54 to the bound structure upon DNA binding.…”

Section: Evaluation and Case Studiesmentioning

confidence: 99%

DBD2BS: connecting a DNA-binding protein with its binding sites

Chien

Lin

et al. 2012

Nucleic Acids Research

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By binding to short and highly conserved DNA sequences in genomes, DNA-binding proteins initiate, enhance or repress biological processes. Accurately identifying such binding sites, often represented by position weight matrices (PWMs), is an important step in understanding the control mechanisms of cells. When given coordinates of a DNA-binding domain (DBD) bound with DNA, a potential function can be used to estimate the change of binding affinity after base substitutions, where the changes can be summarized as a PWM. This technique provides an effective alternative when the chromatin immunoprecipitation data are unavailable for PWM inference. To facilitate the procedure of predicting PWMs based on protein–DNA complexes or even structures of the unbound state, the web server, DBD2BS, is presented in this study. The DBD2BS uses an atom-level knowledge-based potential function to predict PWMs characterizing the sequences to which the query DBD structure can bind. For unbound queries, a list of 1066 DBD–DNA complexes (including 1813 protein chains) is compiled for use as templates for synthesizing bound structures. The DBD2BS provides users with an easy-to-use interface for visualizing the PWMs predicted based on different templates and the spatial relationships of the query protein, the DBDs and the DNAs. The DBD2BS is the first attempt to predict PWMs of DBDs from unbound structures rather than from bound ones. This approach increases the number of existing protein structures that can be exploited when analyzing protein–DNA interactions. In a recent study, the authors showed that the kernel adopted by the DBD2BS can generate PWMs consistent with those obtained from the experimental data. The use of DBD2BS to predict PWMs can be incorporated with sequence-based methods to discover binding sites in genome-wide studies.Available at: http://dbd2bs.csie.ntu.edu.tw/, http://dbd2bs.csbb.ntu.edu.tw/, and http://dbd2bs.ee.ncku.edu.tw.

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Predicting Target DNA Sequences of DNA-Binding Proteins Based on Unbound Structures

Cited by 23 publications

References 31 publications

A Structural-Based Strategy for Recognition of Transcription Factor Binding Sites

A Structural-Based Strategy for Recognition of Transcription Factor Binding Sites

Toward Single-Molecule Optical Mapping of the Epigenome

DBD2BS: connecting a DNA-binding protein with its binding sites

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