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Pregled bibliografske jedinice broj: 369309

Atypical cytostatic mechanism of N -1-sulfonylcytosine derivatives determined by in vitro screening and computational analysis


Supek, Fran; Kralj, Marijeta; Marjanović, Marko; Šuman, Lidija; Šmuc, Tomislav; Krizmanić, Irena; Žinić, Biserka
Atypical cytostatic mechanism of N -1-sulfonylcytosine derivatives determined by in vitro screening and computational analysis // Investigational new drugs, 26 (2008), 2; 97-110 doi:10.1007/s10637-007-9084-1 (međunarodna recenzija, članak, znanstveni)


Naslov
Atypical cytostatic mechanism of N -1-sulfonylcytosine derivatives determined by in vitro screening and computational analysis

Autori
Supek, Fran ; Kralj, Marijeta ; Marjanović, Marko ; Šuman, Lidija ; Šmuc, Tomislav ; Krizmanić, Irena ; Žinić, Biserka

Izvornik
Investigational new drugs (0167-6997) 26 (2008), 2; 97-110

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Nucleobases; antitumor agents; In vitro screening; bioinformatics; Random Forest

Sažetak
We have previously shown that N-1-sulfonylpyrimidine derivatives have strong antiproliferative activity on human tumor cell lines, whereby 1-(p-toluenesulfonyl)cytosine showed good selectivity with regard to normal cells and was easily synthesized on a large scale. In the present work we have used an interdisciplinary approach to elucidate the compounds’ mechanistic class. An augmented number of cell lines (11) has allowed a computational search for compounds with similar activity profiles and/or mechanistic class by integrating our data with the comprehensive DTP– NCI database. We applied supervised machine learning methodology (Random Forest classifier), which offers information complementary to unsupervised algorithms commonly used for analysis of cytostatic activity profiles, such as self-organizing maps. The computational results taken together with cell cycle perturbation and apoptosis analysis of the cell lines point to an unusual mechanism of cytostatic action, possibly a combination of nucleic acid antimetabolite activity and a novel molecular mechanism.

Izvorni jezik
Engleski

Znanstvena područja
Kemija, Temeljne medicinske znanosti, Informacijske i komunikacijske znanosti



POVEZANOST RADA


Projekt / tema
098-0000000-3168 - Strojno učenje prediktivnih modela u računalnoj biologiji (Tomislav Šmuc, )
098-0982464-2514 - Uloga različitih mehanizama odgovora stanica na terapiju oštećenjem DNA (Marijeta Kralj, )
098-0982914-2935 - Sinteza novih biološki aktivnih derivata nukleobaza i nukleotida (Biserka Žinić, )

Ustanove
Pliva-Istraživački institut,
Institut "Ruđer Bošković", Zagreb

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


Uključenost u ostale bibliografske baze podataka:


  • BIOSIS Previews (Biological Abstracts)
  • CA Search (Chemical Abstracts)
  • EMBASE (Excerpta Medica)
  • MEDLINE
  • Current Awareness in Biological Sciences (CABS)
  • Medical Documentation Service
  • Reference Update
  • Scopus


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