{"id":695,"date":"2023-03-15T13:41:24","date_gmt":"2023-03-15T06:41:24","guid":{"rendered":"https:\/\/conf.icgbio.ru\/bgrs98\/?page_id=695"},"modified":"2023-04-11T14:33:00","modified_gmt":"2023-04-11T07:33:00","slug":"053_classification-of-eukaryotic-transcription-factors-based-on-significant-b-dna-conformational-and-physico-chemical-properties-of-their-binding-sites","status":"publish","type":"page","link":"https:\/\/conf.icgbio.ru\/bgrs98\/abstracts\/abstract-list\/053_classification-of-eukaryotic-transcription-factors-based-on-significant-b-dna-conformational-and-physico-chemical-properties-of-their-binding-sites\/","title":{"rendered":"CLASSIFICATION OF EUKARYOTIC TRANSCRIPTION FACTORS BASED ON SIGNIFICANT B-DNA CONFORMATIONAL AND PHYSICO-CHEMICAL PROPERTIES OF THEIR BINDING SITES"},"content":{"rendered":"

PONOMARENKO J.V.<\/a><\/p>\n

Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 10 Lavrentiev Ave., Novosibirsk, 630090, Russia<\/p>\n

Keywords<\/a>: eukaryotic transcription factors, conformational and physico-chemical properties of DNA, classification<\/p>\n

 <\/p>\n

Local nonuniformity of DNA conformational and physico-chemical properties and their dependence on nucleotide content have been demonstrated in numerous studies [1, 2]. X-ray structure analysis of B-DNA duplexes and complexes with proteins provided for determination of the mean conformational parameters of each dinucleotide [3-5]. Mean values of a number of physico-chemical properties have been determined for each dinucleotide too [6-10].<\/p>\n

A method for classification of transcription factors based on significant context-dependent B-DNA conformational and physico-chemical properties of their binding sites, revealed by the system B-DNA-VIDEO [11] is proposed in this work. Sets of nucleotide sequences of transcription factor binding sites from the SAMPLES database without 100% homologues [12] (Table 1) were used for the analysis. The sequences in each set are aligned relative to the center of the experimentally determined binding sites of a definite transcription factor; their location was determined according to the information contained in the TRANSFAC database and published data (in case of YY1 site, the TRRD database, v 3.5, was also employed). The sequences considered was 120 bp long with flanks of 60 bp from the center of the site.<\/p>\n

Table 1. Eukaryotic transcription factor binding sites\u00a0<\/b>involved in the analysis<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
<\/td>\n\n

Factor<\/p>\n<\/td>\n

\n

Class according to TRANSFAC<\/p>\n<\/td>\n

\n

Number of sequences in<\/p>\n<\/td>\n

\n

Size of footprint or TRANSFAC sequence element, bp<\/p>\n<\/td>\n<\/tr>\n

<\/td>\n<\/td>\n\n

Number<\/p>\n<\/td>\n

\n

Name<\/p>\n<\/td>\n

\n

set<\/p>\n<\/td>\n

\n

Mean<\/p>\n<\/td>\n

\n

Min<\/p>\n<\/td>\n

\n

Max<\/p>\n<\/td>\n<\/tr>\n

1<\/td>\nAP-1<\/td>\n\n

1.1<\/p>\n<\/td>\n

\n

Leucine zipper factors (bZIP)<\/p>\n<\/td>\n

\n

69<\/p>\n<\/td>\n

\n

14.9<\/p>\n<\/td>\n

\n

6<\/p>\n<\/td>\n

\n

53<\/p>\n<\/td>\n<\/tr>\n

2<\/td>\nc-Fos<\/td>\n\n

1.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

19<\/p>\n<\/td>\n

\n

13.9<\/p>\n<\/td>\n

\n

6<\/p>\n<\/td>\n

\n

29<\/p>\n<\/td>\n<\/tr>\n

3<\/td>\nc-Jun<\/td>\n\n

1.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

28<\/p>\n<\/td>\n

\n

14.6<\/p>\n<\/td>\n

\n

6<\/p>\n<\/td>\n

\n

43<\/p>\n<\/td>\n<\/tr>\n

4<\/td>\nNF-E2<\/td>\n\n

1.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

12<\/p>\n<\/td>\n

\n

10.7<\/p>\n<\/td>\n

\n

3<\/p>\n<\/td>\n

\n

20<\/p>\n<\/td>\n<\/tr>\n

5<\/td>\nCRE-BP1<\/td>\n\n

1.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

22<\/p>\n<\/td>\n

\n

12.7<\/p>\n<\/td>\n

\n

6<\/p>\n<\/td>\n

\n

25<\/p>\n<\/td>\n<\/tr>\n

6<\/td>\nATF<\/td>\n\n

1.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

25<\/p>\n<\/td>\n

\n

12.9<\/p>\n<\/td>\n

\n

5<\/p>\n<\/td>\n

\n

25<\/p>\n<\/td>\n<\/tr>\n

7<\/td>\nCREB<\/td>\n\n

1.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

37<\/p>\n<\/td>\n

\n

13.6<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n

\n

37<\/p>\n<\/td>\n<\/tr>\n

8<\/td>\nC\/EBP<\/td>\n\n

1.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

108<\/p>\n<\/td>\n

\n

19.1<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n

\n

96<\/p>\n<\/td>\n<\/tr>\n

9<\/td>\nNF-IL6<\/td>\n\n

1.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

21<\/p>\n<\/td>\n

\n

19.9<\/p>\n<\/td>\n

\n

8<\/p>\n<\/td>\n

\n

41<\/p>\n<\/td>\n<\/tr>\n

10<\/td>\nMyoD<\/td>\n\n

1.2<\/p>\n<\/td>\n

\n

Helix-loop-helix factors (bHLH)<\/p>\n<\/td>\n

\n

16<\/p>\n<\/td>\n

\n

18.5<\/p>\n<\/td>\n

\n

8<\/p>\n<\/td>\n

\n

59<\/p>\n<\/td>\n<\/tr>\n

11<\/td>\nE2F<\/td>\n\n

1.3<\/p>\n<\/td>\n

\n

(bHLH-ZIP)<\/p>\n<\/td>\n

\n

9<\/p>\n<\/td>\n

\n

13.2<\/p>\n<\/td>\n

\n

7<\/p>\n<\/td>\n

\n

30<\/p>\n<\/td>\n<\/tr>\n

12<\/td>\nUSF<\/td>\n\n

1.3<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

25<\/p>\n<\/td>\n

\n

14.1<\/p>\n<\/td>\n

\n

5<\/p>\n<\/td>\n

\n

30<\/p>\n<\/td>\n<\/tr>\n

13<\/td>\nNF-1<\/td>\n\n

1.4<\/p>\n<\/td>\n

\n

NF-1<\/p>\n<\/td>\n

\n

101<\/p>\n<\/td>\n

\n

17.2<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n

\n

53<\/p>\n<\/td>\n<\/tr>\n

14<\/td>\nRF-X<\/td>\n\n

1.5<\/p>\n<\/td>\n

\n

RF-X<\/p>\n<\/td>\n

\n

12<\/p>\n<\/td>\n

\n

17.0<\/p>\n<\/td>\n

\n

11<\/p>\n<\/td>\n

\n

24<\/p>\n<\/td>\n<\/tr>\n

15<\/td>\nCP1<\/td>\n\n

1.6<\/p>\n<\/td>\n

\n

Heteromeric CCAAT factors<\/p>\n<\/td>\n

\n

33<\/p>\n<\/td>\n

\n

17.2<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n

\n

41<\/p>\n<\/td>\n<\/tr>\n

16<\/td>\nER<\/td>\n\n

2.1<\/p>\n<\/td>\n

\n

Cys4 zinc finger of nuclear receptor type<\/p>\n<\/td>\n

\n

25<\/p>\n<\/td>\n

\n

17.5<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n

\n

40<\/p>\n<\/td>\n<\/tr>\n

17<\/td>\nGR<\/td>\n\n

2.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

54<\/p>\n<\/td>\n

\n

12.6<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n

\n

39<\/p>\n<\/td>\n<\/tr>\n

18<\/td>\nPR<\/td>\n\n

2.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

20<\/p>\n<\/td>\n

\n

11.7<\/p>\n<\/td>\n

\n

5<\/p>\n<\/td>\n

\n

20<\/p>\n<\/td>\n<\/tr>\n

19<\/td>\nRAR<\/td>\n\n

2.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

16<\/p>\n<\/td>\n

\n

24.6<\/p>\n<\/td>\n

\n

7<\/p>\n<\/td>\n

\n

56<\/p>\n<\/td>\n<\/tr>\n

20<\/td>\nRXR<\/td>\n\n

2.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

21<\/p>\n<\/td>\n

\n

20.9<\/p>\n<\/td>\n

\n

10<\/p>\n<\/td>\n

\n

28<\/p>\n<\/td>\n<\/tr>\n

21<\/td>\nT3R<\/td>\n\n

2.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

21<\/p>\n<\/td>\n

\n

20.5<\/p>\n<\/td>\n

\n

10<\/p>\n<\/td>\n

\n

28<\/p>\n<\/td>\n<\/tr>\n

22<\/td>\nCOUP<\/td>\n\n

2.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

17<\/p>\n<\/td>\n

\n

20.6<\/p>\n<\/td>\n

\n

11<\/p>\n<\/td>\n

\n

35<\/p>\n<\/td>\n<\/tr>\n

23<\/td>\nGATA-1<\/td>\n\n

2.2<\/p>\n<\/td>\n

\n

Diverse Cys4 zinc fingers<\/p>\n<\/td>\n

\n

76<\/p>\n<\/td>\n

\n

16.1<\/p>\n<\/td>\n

\n

5<\/p>\n<\/td>\n

\n

41<\/p>\n<\/td>\n<\/tr>\n

24<\/td>\nSp1<\/td>\n\n

2.3<\/p>\n<\/td>\n

\n

Cys2His2 zinc finger domain<\/p>\n<\/td>\n

\n

176<\/p>\n<\/td>\n

\n

13.1<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n

\n

96<\/p>\n<\/td>\n<\/tr>\n

25<\/td>\nYY1<\/td>\n\n

2.3<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

27<\/p>\n<\/td>\n

\n

13.6<\/p>\n<\/td>\n

\n

6<\/p>\n<\/td>\n

\n

27<\/p>\n<\/td>\n<\/tr>\n

26<\/td>\nGAL4<\/td>\n\n

2.4<\/p>\n<\/td>\n

\n

Cys6 cysteine-zinc cluster<\/p>\n<\/td>\n

\n

16<\/p>\n<\/td>\n

\n

14.7<\/p>\n<\/td>\n

\n

3<\/p>\n<\/td>\n

\n

22<\/p>\n<\/td>\n<\/tr>\n

27<\/td>\nEN<\/td>\n\n

3.1<\/p>\n<\/td>\n

\n

Homeodomain<\/p>\n<\/td>\n

\n

12<\/p>\n<\/td>\n

\n

11.4<\/p>\n<\/td>\n

\n

6<\/p>\n<\/td>\n

\n

20<\/p>\n<\/td>\n<\/tr>\n

28<\/td>\nHNF-1<\/td>\n\n

3.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

38<\/p>\n<\/td>\n

\n

21.0<\/p>\n<\/td>\n

\n

5<\/p>\n<\/td>\n

\n

96<\/p>\n<\/td>\n<\/tr>\n

29<\/td>\nOCT<\/td>\n\n

3.1<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

73<\/p>\n<\/td>\n

\n

14.9<\/p>\n<\/td>\n

\n

7<\/p>\n<\/td>\n

\n

46<\/p>\n<\/td>\n<\/tr>\n

30<\/td>\nHNF-3<\/td>\n\n

3.3<\/p>\n<\/td>\n

\n

Fork head \/ winged helix<\/p>\n<\/td>\n

\n

10<\/p>\n<\/td>\n

\n

24.6<\/p>\n<\/td>\n

\n

8<\/p>\n<\/td>\n

\n

96<\/p>\n<\/td>\n<\/tr>\n

31<\/td>\nc-Myb<\/td>\n\n

3.5<\/p>\n<\/td>\n

\n

Tryptophan clusters<\/p>\n<\/td>\n

\n

19<\/p>\n<\/td>\n

\n

18.9<\/p>\n<\/td>\n

\n

5<\/p>\n<\/td>\n

\n

31<\/p>\n<\/td>\n<\/tr>\n

32<\/td>\nEts<\/td>\n\n

3.5<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

15<\/p>\n<\/td>\n

\n

20.9<\/p>\n<\/td>\n

\n

9<\/p>\n<\/td>\n

\n

45<\/p>\n<\/td>\n<\/tr>\n

33<\/td>\nIRF-1<\/td>\n\n

3.5<\/p>\n<\/td>\n

\n

– \u201c –<\/p>\n<\/td>\n

\n

7<\/p>\n<\/td>\n

\n

16.1<\/p>\n<\/td>\n

\n

5<\/p>\n<\/td>\n

\n

22<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n

Table2. Significant conformational and physico-chemical properties of the DNA transcription factor binding sites.<\/p>\n

\"\"<\/a><\/p>\n

 <\/p>\n

Listed in Table 2 are the conformational and physico-chemical properties from the PROPERTY database used in this work. Basing on these data, the computer system B-DNA-VIDEO automatically performs the search for significant conformational and physico-chemical properties and the regions of sites where the mean value of a conformational and physico-chemical property in question differs significantly from the value characteristic of random nucleotide sequences.<\/p>\n

The system B-DNA-VIDEO employs the following algorithm. Consider a nucleotide sequence S={s1<\/sub>…si<\/sub>…sL<\/sub>}of length L. There is the dinucleotide si<\/sub>si+1<\/sub>\u00a0at the i-th position. The mean of the k-th property from Table 2, Xk<\/sub>, averaged for a region [a, b] (1<= a<= b<= L) with the starting position \u011ea\u011f and the terminal position \u011eb\u011f of the sequence S is calculated as follows:<\/p>\n\n\n\n
\"\"<\/a><\/td>\n(1)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Equation (1) was applied to each of the 27 properties and to each of the 33 sites listed in Table 2. All the possible sequence regions [a, b] not smaller than one dinucleotide were taken into account. Their number for a sequence L long was n(L)=L x (L-1)\/2. The total number of sequence regions was n(120)=120 x (120-1)\/2=7140 for a sample. A number of properties Xk,a,b<\/sub>\u00a0can be calculated N(L)=27 x n(L) for a sequence L long. Thus, a total number of N(70)=27 x 7140=192780 properties was tested for each sample.<\/p>\n

Applying Equation (1) to the set of site sequences {S} at a fixed k, a and b, we yield the distribution Xk,a,b<\/sub>{S} for the site. Similarly, the distribution Xk,a,b<\/sub>{R} is generated for random sequences {R} with the same nucleotide frequencies as in the real sequences. The difference between these distributions Xk,a,b<\/sub>{S} and Xk,a,b<\/sub>{R} is tested for significance using four statistical criteria [13]. B-DNA-VIDEO [11] processes the sets {S} and {R} and outputs the list of the significant B-DNA properties {Xk,a,b<\/sub>}.<\/p>\n

The results obtained by the described analysis of transcription factor binding sites are stored in the knowledge base on functional sites B-DNA-FEATURES, which is a constituent of the computer system B-DNA-VIDEO.<\/p>\n

We have analyzed 33 transcription factor binding sites; the results are summarized in Table 2. The conformational and physico-chemical properties, the mean value of which within certain regions of a site differs significantly from the values characteristic of random sequences, have been discovered for each site considered. If the mean value of a significant property for the site exceeded that for random sequences, it was indicates by “+” in Table 2; otherwise, “-“. The lengths of the significant regions vary in the range of 10 to 25 bp; this corresponds to 1-2.5 coils of B-DNA helix as well as to the mean length of the region of DNA interaction with transcription factors (see Table 1).<\/p>\n

An approach to classification of transcription factors based on the revealed sets of significant conformational and physico-chemical properties of their binding sites is suggested. The classification of transcription factor DNA-binding domains proposed by Wingender [14] distinguishes four superclasses: I superclass containing basic domains; II superclass, zinc-coordinated DNA-binding domains; III superclass, helix-turn-helix; and IV superclass, beta-scaffold factors with minor groove contacts. Fifteen transcription factors of thirty three considered belong to various classes of the I superclass according to the type of their domain; eleven sites, to the II superclass; and seven, to the III supercalss (Table 1).<\/p>\n

The information contained in Table 2 was processed by the program Cluster Analysis from software package STATISTICA (Windows\u201995) to construct the similarity tree for the transcription factors analyzed (Figure). Euclidean distance was used as a measure of similarity between two sites i and j:<\/p>\n\n\n\n
\"\"<\/a><\/td>\n(2)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

where xi,k<\/sub>\u00a0= 1, if the mean value of kth property on the region of the site i exceeds significantly the corresponding mean value for random sequences (indicated by “+” in Table 2); xi,k\u00a0<\/sub>= -1, if the mean value of the kth property on the region of the site i is significantly lower than the corresponding mean value for random sequences (indicated by “-” in Table 2); xi,k<\/sub>\u00a0= 0, if the mean value of the kth property on the region of site i equals the corresponding mean value for random sequences; and k is the number of the property considered, k = 1,…,27. The distances between clusters are determined by the greatest distance between any two objects in separate clusters (i.e., by the “furthest neighbors”).<\/p>\n

 <\/p>\n

\"\"<\/a><\/p>\n

Figure. The similarity tree for transcription factors.<\/p>\n

 <\/p>\n

The tree obtained has two branches (Figure). The left branch unites all transcription factors that belong to the III superclass according to the type of DNA-binding domains and eight transcription factors of the I and II superclass according to the classification of Wingender [14]. The factors belonging to the III superclass contain the DNA-binding domain of HTH type. The probability that a transcription factor is attributed to the III superclass accidentally is a <0.004. In turn, the right branch divides in two branches: one containing six transcription factors of the II superclass; the other, eleven factors of the I superclass. The probabilities of accidental attribution to these classes are \"\"<0.0014 and \"\"<0.0012, respectively. These probabilities were calculated basin of binomial distribution as follows:<\/p>\n\n\n\n
\"\"<\/a><\/td>\n(3)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

where m is the number of factors in the tree branch considered; n, the number of factors of a definite superclass contained in this branch; N, total number of the factors in this superclass; M, total number of factors considered (33); and P = N\/M, the probability of accidental attribution of one factor to the superclass considered.<\/p>\n

The classification of transcription factor binding sites obtained by this procedure is consistent with the X-ray and NMR structures of DNA-protein complexes as well as with other available data on DNA-protein interactions. Thus, the transcription factors of the III superclass interact with the DNA as a rule in a form of monomers forming abundant H-bonds and van der Waals (hydrophobic) contacts with bases and sugar-phosphate backbone of the DNA in both major and minor grooves as well as a plenty of water-mediated contacts. The transcription factors of the I superclass and class 2.1 (Cys4 zinc finger of nuclear receptor type) bind to the DNA in major groove in a form of homo- and heterodimers mainly through electrostatic interactions. The transcription factors belonging to the rest classes of the second superclass interact with the major groove mainly as monomers. Interaction of GATA-1 with DNA is more likely to the interaction type of HTH domains with DNA. The NMR structure of GATA-1\/DNA complex indicate that the protein binds to both grooves mainly through hydrophobic interactions.<\/p>\n

Thus, the result obtained indicates a certain correlation between the transcription binding site classification based on their significant conformational and physico-chemical properties, on the one hand, and the classification of the transcription factors binding to these sites according to their DNA-binding domains, on the other.<\/p>\n

I am grateful to Ms. Galina Chirikova for help in translation. This work was supported by Russian Foundation for Basic Research<\/p>\n

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    \n
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  13. Lehman,E.L. (1959) Testing statistical hypotheses. Willey. New York.<\/li>\n
  14. Wingender E (1997) Mol Biol (Mosk), 31, 584-600.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

    PONOMARENKO J.V. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 10 Lavrentiev Ave., Novosibirsk, 630090, Russia Keywords: eukaryotic transcription factors, conformational and physico-chemical properties of DNA, classification   Local nonuniformity of DNA conformational and physico-chemical … Continue reading →<\/span><\/a><\/p>\n","protected":false},"author":13,"featured_media":0,"parent":97,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/conf.icgbio.ru\/bgrs98\/wp-json\/wp\/v2\/pages\/695"}],"collection":[{"href":"https:\/\/conf.icgbio.ru\/bgrs98\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/conf.icgbio.ru\/bgrs98\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/conf.icgbio.ru\/bgrs98\/wp-json\/wp\/v2\/users\/13"}],"replies":[{"embeddable":true,"href":"https:\/\/conf.icgbio.ru\/bgrs98\/wp-json\/wp\/v2\/comments?post=695"}],"version-history":[{"count":3,"href":"https:\/\/conf.icgbio.ru\/bgrs98\/wp-json\/wp\/v2\/pages\/695\/revisions"}],"predecessor-version":[{"id":1390,"href":"https:\/\/conf.icgbio.ru\/bgrs98\/wp-json\/wp\/v2\/pages\/695\/revisions\/1390"}],"up":[{"embeddable":true,"href":"https:\/\/conf.icgbio.ru\/bgrs98\/wp-json\/wp\/v2\/pages\/97"}],"wp:attachment":[{"href":"https:\/\/conf.icgbio.ru\/bgrs98\/wp-json\/wp\/v2\/media?parent=695"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}