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
Authors
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

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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
chem...ical 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 - reak...tivne 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.
Source:
Arhiv za farmaciju, 2022, 72, 4 suplement, S591-S592Publisher:
- Savez farmaceutskih udruženja Srbije (SFUS)
Funding / projects:
- 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).
Note:
- VIII Kongres farmaceuta Srbije sa međunarodnim učešćem, 12-15.10.2022. Beograd
Collections
Institution/Community
PharmacyTY - 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 .