Ministarstvo prosvete, nauke i tehnološkog razvoja Republike Srbije kroz međunarodni projekat između Republike Srbije i NR Kine: „Povećanje efikasnosti terapije karcinoma kombinacijom CAR-T ćelija ili PD-1/PD-L1 inhibitora pomoću imunomodulatora” (451-03-1203/2021-09).

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Ministarstvo prosvete, nauke i tehnološkog razvoja Republike Srbije kroz međunarodni projekat između Republike Srbije i NR Kine: „Povećanje efikasnosti terapije karcinoma kombinacijom CAR-T ćelija ili PD-1/PD-L1 inhibitora pomoću imunomodulatora” (451-03-1203/2021-09).

Authors

Publications

Prediction of adverse effects of sulforaphane by in silico testing of targeted genes, protein- protein interactions and molecular classes

Živančević, Katarina; Baralić, Katarina; Božić, Dragica; Javorac, Dragana; Marić, Đurđica; Antonijević-Miljaković, Evica; Buha-Đorđević, Aleksandra; Ćurčić, Marijana; Bulat, Zorica; Antonijević, Biljana; Đukić-Ćosić, Danijela

(Savez farmaceutskih udruženja Srbije (SFUS), 2022) 

TY  - CONF
AU  - Živančević, Katarina
AU  - Baralić, Katarina
AU  - Božić, Dragica
AU  - Javorac, Dragana
AU  - Marić, Đurđica
AU  - Antonijević-Miljaković, Evica
AU  - Buha-Đorđević, Aleksandra
AU  - Ćurčić, Marijana
AU  - Bulat, Zorica
AU  - Antonijević, Biljana
AU  - Đukić-Ćosić, Danijela
PY  - 2022
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/4632
AB  - Alternative form of cancer treatment includes targeting natural compounds such as
sulfur-rich dietary phytochemical sulforaphane (SFN). However, data on SFN safety,
interactions on the protein level and target of SFN in human organism are limited (1). The
aim of this study was to elucidate the target interactions of SFN in human body in order to
rationalize possible side-effects and predict off-targets by using in silico approach. STITCH
database (http://stitch.embl.de) was used to obtain the information about chemical–protein
interactions, while Metascape (https://metascape.org/) highlighted protein-protein
interaction enrichment (PPIE).
SwissTargetPrediction (http://www.swisstargetprediction.ch/) indicated the target
molecule classes of SFN in human. Human genes that had the strongest interaction with SFN
were NQO1, NFE2L2, CASP3, HSP90AA1, MAPK14, HDAC6, HPGDS, KEAP1, GSTA1 and
GSTM1. PPIE analysis singled out fluid shear stress and atherosclerosis, NRF2 pathway and
chemical carcinogenesis - reactive oxygen species (ROS) as the most significant interactions.
The most represented class of SFN targeted molecules in human organism were enzymes
(26.7%). Epidermal growth factor receptor erbB1, macrophage migration inhibitory factor,
nitric oxide synthase (inducible) showed the highest probability target rate. In our previous
study (2), we pointed out that the genome of cancer patients could affect SFN safety. The
current study provides a set of target genes, emphasizes the importance of oxidative stress in
the suggested genetic interactions and predicts classes of target molecules, which should
further be examined.
AB  - Alternativni oblik lečenja raka uključuje upotrebu prirodnih jedinjenja kao što je
fitohemikalija bogata sumporom, sulforafan (SFN). Međutim, podaci o interakcijama SFN na
nivou proteina i ciljnih mesta dejstva SFN u ljudskom organizmu su ograničeni (1). Cilj ove
studije bio je da se ukaže na ciljne interakcije SFN kod ljudi kako bi se racionalizovali mogući
neželjeni efekti i predvidela nova ciljna mesta toksičnosti korišćenjem in silico pristupa.
STITCH baza podataka (http://stitch.embl.de) korišć ena je za dobijanje informacija o
interakcijama između hemikalija i proteina, dok je Metascape (https://metascape.org/)
izdvojio protein-protein interakcije (PPIE).
SwissTargetPrediction (http://vvv.svisstargetprediction.ch/) ukazao je na ciljana
mesta dejstva SFN kod ljudi. Izdvojeni su geni koji kod ljudi imaju najjaču interakciju sa SFN:
NQO1, NFE2L2, CASP3, HSP90AA1, MAPK14, HDAC6, HPGDS, KEAP1, GSTA1, GSTM1.
Ateroskleroza, NRF2 signalni put i hemijska karcinogeneza - reaktivne vrste kiseonika (ROS)
označeni su kao najznačajnije protein-protein interakcije. Najzastupljenija klasa SFN ciljanih
molekula u ljudskom organizmu bili su enzimi (26,7%). Receptor epidermalnog faktora rasta
erbB1, faktor inhibitora migracije makrofaga i sintaza azot oksida (inducibilna) pokazali su
najveć u stopu verovatnoć e ciljnog mesta dejstva. U našoj prethodnoj studiji (2) istakli smo
da bi genom pacijenata obolelih od raka mogao uticati na bezbednost primene SFN. Međutim,
ova studija daje dodatni set ciljnih gena i naglašava važnost oksidativnog stresa u
predloženim interakcijama između gena, kao i predviđenim klasama ciljnih molekula na koje
deluje SFN i koje bi trebalo dalje ispitati.
PB  - Savez farmaceutskih udruženja Srbije (SFUS)
C3  - Arhiv za farmaciju
T1  - Prediction of adverse effects of sulforaphane by in silico testing of targeted genes, protein- protein interactions and molecular classes
T1  - Predviđanje štetnih efekata sulforafana in silico ispitivanjem njegovog ciljanog dejstva na gene, protein‐protein interakcije i klase molekula
VL  - 72
IS  - 4 suplement
SP  - S591
EP  - S592
UR  - https://hdl.handle.net/21.15107/rcub_farfar_4632
ER  - 
@conference{
author = "Živančević, Katarina and Baralić, Katarina and Božić, Dragica and Javorac, Dragana and Marić, Đurđica and Antonijević-Miljaković, Evica and Buha-Đorđević, Aleksandra and Ćurčić, Marijana and Bulat, Zorica and Antonijević, Biljana and Đukić-Ćosić, Danijela",
year = "2022",
abstract = "Alternative form of cancer treatment includes targeting natural compounds such as
sulfur-rich dietary phytochemical sulforaphane (SFN). However, data on SFN safety,
interactions on the protein level and target of SFN in human organism are limited (1). The
aim of this study was to elucidate the target interactions of SFN in human body in order to
rationalize possible side-effects and predict off-targets by using in silico approach. STITCH
database (http://stitch.embl.de) was used to obtain the information about chemical–protein
interactions, while Metascape (https://metascape.org/) highlighted protein-protein
interaction enrichment (PPIE).
SwissTargetPrediction (http://www.swisstargetprediction.ch/) indicated the target
molecule classes of SFN in human. Human genes that had the strongest interaction with SFN
were NQO1, NFE2L2, CASP3, HSP90AA1, MAPK14, HDAC6, HPGDS, KEAP1, GSTA1 and
GSTM1. PPIE analysis singled out fluid shear stress and atherosclerosis, NRF2 pathway and
chemical carcinogenesis - reactive oxygen species (ROS) as the most significant interactions.
The most represented class of SFN targeted molecules in human organism were enzymes
(26.7%). Epidermal growth factor receptor erbB1, macrophage migration inhibitory factor,
nitric oxide synthase (inducible) showed the highest probability target rate. In our previous
study (2), we pointed out that the genome of cancer patients could affect SFN safety. The
current study provides a set of target genes, emphasizes the importance of oxidative stress in
the suggested genetic interactions and predicts classes of target molecules, which should
further be examined., Alternativni oblik lečenja raka uključuje upotrebu prirodnih jedinjenja kao što je
fitohemikalija bogata sumporom, sulforafan (SFN). Međutim, podaci o interakcijama SFN na
nivou proteina i ciljnih mesta dejstva SFN u ljudskom organizmu su ograničeni (1). Cilj ove
studije bio je da se ukaže na ciljne interakcije SFN kod ljudi kako bi se racionalizovali mogući
neželjeni efekti i predvidela nova ciljna mesta toksičnosti korišćenjem in silico pristupa.
STITCH baza podataka (http://stitch.embl.de) korišć ena je za dobijanje informacija o
interakcijama između hemikalija i proteina, dok je Metascape (https://metascape.org/)
izdvojio protein-protein interakcije (PPIE).
SwissTargetPrediction (http://vvv.svisstargetprediction.ch/) ukazao je na ciljana
mesta dejstva SFN kod ljudi. Izdvojeni su geni koji kod ljudi imaju najjaču interakciju sa SFN:
NQO1, NFE2L2, CASP3, HSP90AA1, MAPK14, HDAC6, HPGDS, KEAP1, GSTA1, GSTM1.
Ateroskleroza, NRF2 signalni put i hemijska karcinogeneza - reaktivne vrste kiseonika (ROS)
označeni su kao najznačajnije protein-protein interakcije. Najzastupljenija klasa SFN ciljanih
molekula u ljudskom organizmu bili su enzimi (26,7%). Receptor epidermalnog faktora rasta
erbB1, faktor inhibitora migracije makrofaga i sintaza azot oksida (inducibilna) pokazali su
najveć u stopu verovatnoć e ciljnog mesta dejstva. U našoj prethodnoj studiji (2) istakli smo
da bi genom pacijenata obolelih od raka mogao uticati na bezbednost primene SFN. Međutim,
ova studija daje dodatni set ciljnih gena i naglašava važnost oksidativnog stresa u
predloženim interakcijama između gena, kao i predviđenim klasama ciljnih molekula na koje
deluje SFN i koje bi trebalo dalje ispitati.",
publisher = "Savez farmaceutskih udruženja Srbije (SFUS)",
journal = "Arhiv za farmaciju",
title = "Prediction of adverse effects of sulforaphane by in silico testing of targeted genes, protein- protein interactions and molecular classes, Predviđanje štetnih efekata sulforafana in silico ispitivanjem njegovog ciljanog dejstva na gene, protein‐protein interakcije i klase molekula",
volume = "72",
number = "4 suplement",
pages = "S591-S592",
url = "https://hdl.handle.net/21.15107/rcub_farfar_4632"
}
Živančević, K., Baralić, K., Božić, D., Javorac, D., Marić, Đ., Antonijević-Miljaković, E., Buha-Đorđević, A., Ćurčić, M., Bulat, Z., Antonijević, B.,& Đukić-Ćosić, D.. (2022). Prediction of adverse effects of sulforaphane by in silico testing of targeted genes, protein- protein interactions and molecular classes. in Arhiv za farmaciju
Savez farmaceutskih udruženja Srbije (SFUS)., 72(4 suplement), S591-S592.
https://hdl.handle.net/21.15107/rcub_farfar_4632
Živančević K, Baralić K, Božić D, Javorac D, Marić Đ, Antonijević-Miljaković E, Buha-Đorđević A, Ćurčić M, Bulat Z, Antonijević B, Đukić-Ćosić D. Prediction of adverse effects of sulforaphane by in silico testing of targeted genes, protein- protein interactions and molecular classes. in Arhiv za farmaciju. 2022;72(4 suplement):S591-S592.
https://hdl.handle.net/21.15107/rcub_farfar_4632 .
Živančević, Katarina, Baralić, Katarina, Božić, Dragica, Javorac, Dragana, Marić, Đurđica, Antonijević-Miljaković, Evica, Buha-Đorđević, Aleksandra, Ćurčić, Marijana, Bulat, Zorica, Antonijević, Biljana, Đukić-Ćosić, Danijela, "Prediction of adverse effects of sulforaphane by in silico testing of targeted genes, protein- protein interactions and molecular classes" in Arhiv za farmaciju, 72, no. 4 suplement (2022):S591-S592,
https://hdl.handle.net/21.15107/rcub_farfar_4632 .