2021
DOI: 10.1016/j.csbj.2021.05.018
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Scaffold fragmentation and substructure hopping reveal potential, robustness, and limits of computer-aided pattern analysis (C@PA)

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Cited by 17 publications
(28 citation statements)
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References 134 publications
(347 reference statements)
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“…By comparing parental and resistant cancer cell lines using molecular biology and cellular methods, researchers have identified numerous ABC transporter substrates (21,(30)(31)(32)(33)(34) as well as inhibitors (16,(35)(36)(37)(38)(39)(40). Computational strategies were also developed to boost the modulator discovery process especially multitarget modulators (41,42). Thus, establishing new cancer cell lines that overexpresses ABC transporters, especially those with limited knowledge like MRP7, will greatly enhance our understanding of MDR in cancer.…”
Section: Discussionmentioning
confidence: 99%
“…By comparing parental and resistant cancer cell lines using molecular biology and cellular methods, researchers have identified numerous ABC transporter substrates (21,(30)(31)(32)(33)(34) as well as inhibitors (16,(35)(36)(37)(38)(39)(40). Computational strategies were also developed to boost the modulator discovery process especially multitarget modulators (41,42). Thus, establishing new cancer cell lines that overexpresses ABC transporters, especially those with limited knowledge like MRP7, will greatly enhance our understanding of MDR in cancer.…”
Section: Discussionmentioning
confidence: 99%
“…The extracted substructures [ e.g ., single-standing/centered (hetero-)aromatic rings, condensed (hetero-)aromatic rings, (un)saturated side chains, extremities, and non-aromatic (hetero-)cycles, etc .] were derivatized by applying a heavy atom substitution scheme as already reported earlier 26 (scaffold fragmentation and substructure hopping). Especially the presence and positioning of (non-polar) hydrogens in the sense of a proton/non-proton pattern scheme was stressed.…”
Section: Methodsmentioning
confidence: 99%
“…On the other hand, 38, 212, and 58 dual ABCB1/ABCC1, ABCB1/ABCG2, and ABCC1/ABCG2 inhibitors are present, respectively, of which 7, 99, and 13 can be considered as potent dual ABCB1/ABCC1, ABCB1/ABCG2, and ABCC1/ABCG2 inhibitors, respectively (IC 50 < 10 µM). Finally, 187 triple ABCB1, ABCC1, and ABCG2 inhibitors can be defined, of which 54 can be considered as potent (IC 50 < 10 µM; so-called ‘Class 7’ compounds 7 , 26 , 27 ). Table 3 summarizes a survey of statistical parameters of the entire ABC_BPMDS as well as important sub-classes.…”
Section: Technical Validationmentioning
confidence: 99%
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