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Bonczek O, Wang L, Gnanasundram SV, Chen S, Haronikova L, Zavadil-Kokas F, Vojtesek B. DNA and RNA Binding Proteins: From Motifs to Roles in Cancer. Int J Mol Sci 2022; 23:ijms23169329. [PMID: 36012592 PMCID: PMC9408909 DOI: 10.3390/ijms23169329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/15/2022] [Accepted: 08/17/2022] [Indexed: 11/16/2022] Open
Abstract
DNA and RNA binding proteins (DRBPs) are a broad class of molecules that regulate numerous cellular processes across all living organisms, creating intricate dynamic multilevel networks to control nucleotide metabolism and gene expression. These interactions are highly regulated, and dysregulation contributes to the development of a variety of diseases, including cancer. An increasing number of proteins with DNA and/or RNA binding activities have been identified in recent years, and it is important to understand how their activities are related to the molecular mechanisms of cancer. In addition, many of these proteins have overlapping functions, and it is therefore essential to analyze not only the loss of function of individual factors, but also to group abnormalities into specific types of activities in regard to particular cancer types. In this review, we summarize the classes of DNA-binding, RNA-binding, and DRBPs, drawing particular attention to the similarities and differences between these protein classes. We also perform a cross-search analysis of relevant protein databases, together with our own pipeline, to identify DRBPs involved in cancer. We discuss the most common DRBPs and how they are related to specific cancers, reviewing their biochemical, molecular biological, and cellular properties to highlight their functions and potential as targets for treatment.
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Affiliation(s)
- Ondrej Bonczek
- Research Centre for Applied Molecular Oncology (RECAMO), Masaryk Memorial Cancer Institute (MMCI), Zluty Kopec 7, 656 53 Brno, Czech Republic
- Department of Medical Biosciences, Umea University, 90187 Umea, Sweden
- Correspondence: (O.B.); (B.V.)
| | - Lixiao Wang
- Department of Medical Biosciences, Umea University, 90187 Umea, Sweden
| | | | - Sa Chen
- Department of Medical Biosciences, Umea University, 90187 Umea, Sweden
| | - Lucia Haronikova
- Research Centre for Applied Molecular Oncology (RECAMO), Masaryk Memorial Cancer Institute (MMCI), Zluty Kopec 7, 656 53 Brno, Czech Republic
| | - Filip Zavadil-Kokas
- Research Centre for Applied Molecular Oncology (RECAMO), Masaryk Memorial Cancer Institute (MMCI), Zluty Kopec 7, 656 53 Brno, Czech Republic
| | - Borivoj Vojtesek
- Research Centre for Applied Molecular Oncology (RECAMO), Masaryk Memorial Cancer Institute (MMCI), Zluty Kopec 7, 656 53 Brno, Czech Republic
- Correspondence: (O.B.); (B.V.)
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Li G, Du X, Li X, Zou L, Zhang G, Wu Z. Prediction of DNA binding proteins using local features and long-term dependencies with primary sequences based on deep learning. PeerJ 2021; 9:e11262. [PMID: 33986992 PMCID: PMC8101451 DOI: 10.7717/peerj.11262] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 03/22/2021] [Indexed: 12/12/2022] Open
Abstract
DNA-binding proteins (DBPs) play pivotal roles in many biological functions such as alternative splicing, RNA editing, and methylation. Many traditional machine learning (ML) methods and deep learning (DL) methods have been proposed to predict DBPs. However, these methods either rely on manual feature extraction or fail to capture long-term dependencies in the DNA sequence. In this paper, we propose a method, called PDBP-Fusion, to identify DBPs based on the fusion of local features and long-term dependencies only from primary sequences. We utilize convolutional neural network (CNN) to learn local features and use bi-directional long-short term memory network (Bi-LSTM) to capture critical long-term dependencies in context. Besides, we perform feature extraction, model training, and model prediction simultaneously. The PDBP-Fusion approach can predict DBPs with 86.45% sensitivity, 79.13% specificity, 82.81% accuracy, and 0.661 MCC on the PDB14189 benchmark dataset. The MCC of our proposed methods has been increased by at least 9.1% compared to other advanced prediction models. Moreover, the PDBP-Fusion also gets superior performance and model robustness on the PDB2272 independent dataset. It demonstrates that the PDBP-Fusion can be used to predict DBPs from sequences accurately and effectively; the online server is at http://119.45.144.26:8080/PDBP-Fusion/.
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Affiliation(s)
- Guobin Li
- School of Artificial Intelligence and Big Data, Hefei University, Hefei, China
| | - Xiuquan Du
- School of Computer Science and Technology, Anhui University, Hefei, China
| | - Xinlu Li
- School of Artificial Intelligence and Big Data, Hefei University, Hefei, China
| | - Le Zou
- School of Artificial Intelligence and Big Data, Hefei University, Hefei, China
| | - Guanhong Zhang
- School of Artificial Intelligence and Big Data, Hefei University, Hefei, China
| | - Zhize Wu
- School of Artificial Intelligence and Big Data, Hefei University, Hefei, China
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3
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D'Agostino L. Native DNA electronics: is it a matter of nanoscale assembly? NANOSCALE 2018; 10:12268-12275. [PMID: 29946628 DOI: 10.1039/c8nr03153c] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The genomic DNA is enveloped by nanotubes formed by the nuclear aggregates of polyamines (NAPs) that induce DNA conformational changes and provide protection and increased interaction abilities for the double strands. In a physiological environment, the nanotube arrangement is initiated by spontaneous interaction among the terminal amino groups of the polyamines and the phosphate ions, with the consequent formation of cyclic monomers that hook at the DNA grooves. The polymer thus formed has the morphological features of an organic semiconductor and therefore, it can be considered to be able to conduct electric charges. Phosphate ions positioned on the NAP external surface could regulate, as in a physical electric circuit, both linear and rotational (histones) protein motion, in accordance with the basilar principles of the electronics. A model of a carrier system for protein motion along the polymer wrapping the DNA strands, based on the phosphate-phosphate complexation, is proposed.
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DNABP: Identification of DNA-Binding Proteins Based on Feature Selection Using a Random Forest and Predicting Binding Residues. PLoS One 2016; 11:e0167345. [PMID: 27907159 PMCID: PMC5132331 DOI: 10.1371/journal.pone.0167345] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2016] [Accepted: 11/12/2016] [Indexed: 12/24/2022] Open
Abstract
DNA-binding proteins are fundamentally important in cellular processes. Several computational-based methods have been developed to improve the prediction of DNA-binding proteins in previous years. However, insufficient work has been done on the prediction of DNA-binding proteins from protein sequence information. In this paper, a novel predictor, DNABP (DNA-binding proteins), was designed to predict DNA-binding proteins using the random forest (RF) classifier with a hybrid feature. The hybrid feature contains two types of novel sequence features, which reflect information about the conservation of physicochemical properties of the amino acids, and the binding propensity of DNA-binding residues and non-binding propensities of non-binding residues. The comparisons with each feature demonstrated that these two novel features contributed most to the improvement in predictive ability. Furthermore, to improve the prediction performance of the DNABP model, feature selection using the minimum redundancy maximum relevance (mRMR) method combined with incremental feature selection (IFS) was carried out during the model construction. The results showed that the DNABP model could achieve 86.90% accuracy, 83.76% sensitivity, 90.03% specificity and a Matthews correlation coefficient of 0.727. High prediction accuracy and performance comparisons with previous research suggested that DNABP could be a useful approach to identify DNA-binding proteins from sequence information. The DNABP web server system is freely available at http://www.cbi.seu.edu.cn/DNABP/.
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Cloning and sequencing of a rice (Oryza sativa L.) RAPB cDNA using yeast one-hybrid system. SCIENCE IN CHINA. SERIES C, LIFE SCIENCES 2008; 42:354-61. [PMID: 18763125 DOI: 10.1007/bf02882054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/1998] [Indexed: 10/22/2022]
Abstract
Cis-acting elements containing CCAAT core sequence are located in 5' upstream regions of numerous eukaryotic genes. CCAAT-binding factors interact with thesecis acting elements as heteromeric complex and therefore control the gene transcription. CCAAT binding factors contain at least three subunits and each subunit alone cannot bind to CCAAT box. The cloning of a rice cDNA called RAPB which homologizes to yeast HAP2 (one of the subunits in CCAAT-binding factors) using yeast one-hybrid system and functional complementation approaches is reported. The analytic results indicate that the deduced amino acid sequence in the C terminal of RAPB also contains the functional domain of 60 amino acids highly homologous with yeast HAP2, whereas the deduced amino acids in N terminal region differs significantly, and no Gln-rich region is found in the RAPB protein as in HAP2. The Southern blotting analysis demonstrates that only one copy of RAPB gene exists in rice genome.
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Daniel DC, Thompson M, Woodbury NW. DNA-binding interactions and conformational fluctuations of Tc3 transposase DNA binding domain examined with single molecule fluorescence spectroscopy. Biophys J 2002; 82:1654-66. [PMID: 11867477 PMCID: PMC1301963 DOI: 10.1016/s0006-3495(02)75516-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The fluorescent dye tetramethylrhodamine (TMR) was conjugated to a synthetic peptide containing the sequence-specific DNA binding domain of Tc3 transposase. Steady-state and single molecule fluorescence spectroscopy was used to investigate protein conformational fluctuations and the thermodynamics of binding interactions. Evidence is presented to show that the TMR-Tc3 conjugate exists in at least two conformational states. The most stable conformation is one in which the TMR fluorescence is quenched. Upon binding to DNA, the total fluorescence from TMR-Tc3 increases by three- to fourfold. Single molecule measurements of TMR-Tc3 bound to DNA shows that this complex also fluctuates between a fluorescent and quenched form. The fluorescent form of the conjugate is stabilized when bound to DNA, and this accounts for part of the increase in total fluorescence. In addition, the inherent photodynamics of the dye itself is also altered (e.g., fluorescent lifetime or triplet yield) in such a way that the total fluorescence from the conjugate bound to DNA is enhanced relative to the unbound form.
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Affiliation(s)
- Douglas C Daniel
- Department of Chemistry and Biochemistry, Arizona State University, Tempe, Arizona 85287-1604, USA
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Schjerling P, Holmberg S. Comparative amino acid sequence analysis of the C6 zinc cluster family of transcriptional regulators. Nucleic Acids Res 1996; 24:4599-607. [PMID: 8967907 PMCID: PMC146297 DOI: 10.1093/nar/24.23.4599] [Citation(s) in RCA: 208] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
The C6 zinc cluster family of fungal regulatory proteins shares as DNA-binding motif the C6 zinc cluster, also known as the Zn(II)2Cys6 binuclear cluster. This family includes transcriptional activators like Gal4p, Leu3p, Hap1p, Put3p and Cha4p from Saccharomyces cerevisiae, qutA and amdR from Aspergillus, nit4 from Neurospora and Ntf1 from Schizosaccharomyces pombe. Seventy-nine proteins were retrieved from databases by homology to the C6 zinc cluster. All were fungal and 56 were found in the entire genome sequence of S.cerevisiae. Sequence analysis suggests that 60 of the 79 proteins possess one or more coiled-coil dimerization regions succeeding the C6 zinc cluster. Previous comparisons of Gal4p and seven other C6 zinc cluster proteins identified an additional region with weak homology. This region, designated the middle homology region (MHR), was shown to be present in 50 of the 79 proteins. Although reported mutation and deletion analyses suggest a role of MHR in regulation of protein activity, no function has yet been assigned specifically to this region. We find that the family of MHR sequences is confined to C6 zinc cluster proteins and hypothesize that one MHR function is to assist the C6 zinc cluster in DNA target discrimination.
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Affiliation(s)
- P Schjerling
- Department of Genetics, Institute of Molecular Biology, University of Copenhagen, Denmark
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Cutts SM, Parsons PG, Sturm RA, Phillips DR. Adriamycin-induced DNA adducts inhibit the DNA interactions of transcription factors and RNA polymerase. J Biol Chem 1996; 271:5422-9. [PMID: 8621397 DOI: 10.1074/jbc.271.10.5422] [Citation(s) in RCA: 39] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
Adriamycin is known to specifically induce DNA interstrand cross-links at 5'-GC sequences. Because 5'-GC sequences are a predominant feature of 5'-untranslated regions (transcription factor-binding sites, promoter, and enhancer regions), it is likely that adriamycin adducts at GC sites would affect the binding of DNA-interacting proteins. Two model systems were chosen for the analysis: the octamer-binding proteins Oct-1, N-Oct-3 and N-Oct-5, which bind to ATGCAAAT and TAATGARAT recognition sites, and Escherichia coli RNA polymerase binding to the lac UV5 promoter. Electrophoretic mobility shift studies showed that adriamycin adducts at GC sites inhibited the binding of octamer proteins to their consensus motifs at drug levels as low as 1 micoM, but no effect was observed with a control sequence lacking a GC site. Adriamycin adducts at GC sites also inhibited the binding of RNA polymerase to the lac UV5 promoter. Adriamycin may therefore function by down-regulating the expression of specific genes by means of inactivation of short but critical motifs containing one or more GC sites.
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Affiliation(s)
- S M Cutts
- School of Biochemistry, La Trobe University, Bundoora, Victoria 3083, Australia
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9
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Wilson DB. Transcription factors: regulators of gene expression in normal and pathological states. Ann Med 1996; 28:1-3. [PMID: 8932497 DOI: 10.3109/07853899608999065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
Initiation of transcription is the major control point for gene expression. The protein factors regulating transcription, the transcription factors, are modular proteins with distinct domains responsible for different functions including DNA binding, ligand binding, nuclear localization, and protein-protein interactions. Abnormal transcription has been associated with various human diseases from neoplasia to birth defects. These can result from chromosomal translocation or transcription factor genes (e.g. Burkitt's lymphoma) or by inappropriate activation of these factors due to synthesis of fusion genes (e.g. BCR-ABL fusion gene in Philadelphia positive leukaemia). More recently, abnormalities in transcription factor genes have been linked to such human birth defects as Waardenburg syndrome, vesicoureteral reflux and craniosynostosis.
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10
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Kel OV, Romaschenko AG, Kel AE, Wingender E, Kolchanov NA. A compilation of composite regulatory elements affecting gene transcription in vertebrates. Nucleic Acids Res 1995; 23:4097-103. [PMID: 7479071 PMCID: PMC307349 DOI: 10.1093/nar/23.20.4097] [Citation(s) in RCA: 57] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
Over the past years, evidence has been accumulating for a fundamental role of protein-protein interactions between transcription factors in gene-specific transcription regulation. Many of these interactions run within composite elements containing binding sites for several factors. We have selected 101 composite regulatory elements identified experimentally in the regulatory regions of 64 genes of vertebrates and of their viruses and briefly described them in a compilation. Of these, 82 composite elements are of the synergistic type and 19 of the antagonistic type. Within the synergistic type composite elements, transcription factors bind to the corresponding sites simultaneously, thus cooperatively activating transcription. The factors, binding to their target sites within antagonistic type composite elements, produce opposing effects on transcription. The nucleotide sequence and localization in the genes, the names and brief description of transcription factors, are provided for each composite element, including a representation of experimental data on its functioning. Most of the composite elements (3/4) fall between -250 bp and the transcription start site. The distance between the binding sites within the composite elements described varies from complete overlapping to 80 bp. The compilation of composite elements is presented in the database COMPEL which is electronically accessible by anonymous ftp via internet.
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Affiliation(s)
- O V Kel
- Institute of Cytology and Genetics, Novosibirsk, Russia
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11
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Sevaljević LJ, Marinković-Pajović S, Grigorov I, Bogojević D, Ivanović-Matić S, Petrović M. Acute phase-dependent changes in the binding of rat liver nucleoproteins to the cytokine response element of the rat haptoglobin gene. Int J Biochem Cell Biol 1995; 27:185-94. [PMID: 7539335 DOI: 10.1016/1357-2725(94)00073-k] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Hormones released during the acute phase reaction promote the transcriptional activation of the haptoglobin (Hp) gene and a consequent increase of Hp protein synthesis in the liver. The mechanisms underlying the alterations of basal transcription rates of eukaryotic genes are assumed to result from modulations of the binding affinities between nucleoproteins and specific DNA sequences in the enhancer and promoter elements. In order to characterize the changes in the interaction of nucleoproteins with the promoter that accompany the induction of the Hp gene, nuclear extracts from normal and inflamed livers were probed with hormone responsive element (HRE) of the rat Hp gene by gel mobility shift and Southwestern assays. Each of the three cis-acting sequences of the HRE, elements A, B, and C, recognized a distinct set of proteins. Together they conferred an additional level of specificity to the protein binding sites of the entire ABC-element. These sites were recognized by proteins in liver nuclear extracts isolated from both control and treated rats. The differences in the gel shift and Southwestern patterns of the corresponding DNA-protein complexes suggested that transcriptional activation of the Hp gene relied on changes in the concentrations and/or functional modifications of preexisting proteins rather than on the induction of new trans-acting factors.
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12
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Weber JM, Cai F, Horvath J, Guillemette JG. Predicted structure of the adenovirus DNA binding protein. Virus Genes 1995; 9:171-5. [PMID: 7732662 DOI: 10.1007/bf01702660] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
The DNA sequence of a portion of the MAV1 SmaI-D fragment coding for the C-terminal 147 amino acids of the adenoviral DNA-binding protein (DBP) has been determined. A multiple sequence alignment was constructed of the MAV1 fragment and the DBPs of Ad.2, 4, 5, 7, 12, 40, and 41 to examine the degree of conservation of features that have been mapped on the Ad.2 DBP and to identify further conserved features. The less conserved N-terminal segment of the protein contains two nuclear localization signals and two acidic regions, the host range region, and all of the 11 phosphorylation sites. The highly conserved C-terminal segment contains a potential leucine zipper and zinc finger motifs. These sequence features were mapped onto a predicted secondary structure of the Ad.2 DBP.
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Affiliation(s)
- J M Weber
- Department of Microbiology, Faculty of Medicine, Université de Sherbrooke, Québec, Canada
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13
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Johnson PF, Sterneck E, Williams SC. Activation domains of transcriptional regulatory proteins. J Nutr Biochem 1993. [DOI: 10.1016/0955-2863(93)90069-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Lanzendörfer M, Langer D, Hain J, Klenk HP, Holz I, Arnold-Ammer I, Zillig W. Structure and Function of the DNA-Dependent RNA Polymerase of Sulfolobus. Syst Appl Microbiol 1993. [DOI: 10.1016/s0723-2020(11)80337-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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