potent multitarget inhibitor  (MultiTarget Pharmaceuticals)

Journal: Computational and Structural Biotechnology Journal

Article Title: Scaffold fragmentation and substructure hopping reveal potential, robustness, and limits of computer-aided pattern analysis (C@PA)

doi: 10.1016/j.csbj.2021.05.018

Figure Lengend Snippet: Broad-spectrum ABCB1, ABCC1, and ABCG2 inhibitors obtained from computational approaches. Compounds 7 – 11 were derived from C@PA as reported by Namasivayam et al. in 2021 . Compounds 12 – 15 resulted from a combined ligand-based approach using similarity search and pharmacophore modelling as reported by Silbermann et al. in 2019 . The corresponding IC 50 values can be found in . Red mark: suggested secondary positive hits as proposed before . (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Article Snippet: These C@PA-derived clear positive hit and clear negative hit substructures are an important framework to obtain potent multitarget ABCB1, ABCC1, and ABCG2 inhibitors .

Techniques: Derivative Assay

Journal: Computational and Structural Biotechnology Journal

Article Title: Scaffold fragmentation and substructure hopping reveal potential, robustness, and limits of computer-aided pattern analysis (C@PA)

doi: 10.1016/j.csbj.2021.05.018

Figure Lengend Snippet: The determined IC 50 values of compounds that resulted in an inhibition level of ≥20% [+ standard error or the mean (SEM)] in the preliminary screening ( Fig. 7 A–C) determined in calcein AM (ABCB1 and ABCC1) and pheophorbide A (ABCG2) assays, respectively, applying ABCB1-overexpressing A2780/ADR, ABCC1-overexpressing H69AR, and ABCG2-overexpressing MDCK II BCRP cells, respectively, as described earlier [15] , [43] , [45] , [67] , [101] . The reference inhibitors (ABCB1: 2 ; ABCC1: 26 ; ABCG2: 27 ) served as positive controls as already reported earlier [67] , [101] , defining 100% inhibition. Buffer medium served as a negative control (0%). Shown is mean ± SEM of at least three independent experiments. Light rose mark: IC 50 values of the triple ABCB1, ABCC1, and ABCG2 inhibitors 7 – 15 as reported earlier [15] , [67] ; dark rose mark: within this work discovered novel multitarget ABCB1, ABCC1, and ABCG2 inhibitors.

Article Snippet: These C@PA-derived clear positive hit and clear negative hit substructures are an important framework to obtain potent multitarget ABCB1, ABCC1, and ABCG2 inhibitors .

Techniques: Inhibition, Negative Control

Journal: Computational and Structural Biotechnology Journal

Article Title: Scaffold fragmentation and substructure hopping reveal potential, robustness, and limits of computer-aided pattern analysis (C@PA)

doi: 10.1016/j.csbj.2021.05.018

Figure Lengend Snippet: Visualization of the classification of modulators of ABCB1, ABCC1, and ABCG2 as proposed earlier : ‘class 7 compounds’ are defined as triple ABCB1, ABCC1, and ABCG2 inhibitors that exert their half-maximal effect against these transporters below 10 µM. This has up to date been reported for 56 compounds , , , , , , , , , , , , , , , , , , , , , , , , , . Amongst these molecules are the compounds revealed by C@PA, 8–9 and 11 .

Article Snippet: These C@PA-derived clear positive hit and clear negative hit substructures are an important framework to obtain potent multitarget ABCB1, ABCC1, and ABCG2 inhibitors .

Techniques:

Journal: Computational and Structural Biotechnology Journal

Article Title: Scaffold fragmentation and substructure hopping reveal potential, robustness, and limits of computer-aided pattern analysis (C@PA)

doi: 10.1016/j.csbj.2021.05.018

Figure Lengend Snippet: Hit molecules 16 – 25 derived from the herein presented virtual screening approach as well as the reference ABCC1 and ABCG2 inhibitors, 26 and Ko143 ( 27 ), respectively, used in the present study , . The corresponding IC 50 values of compounds 16 – 25 can be found in . Red Mark: extended positive pattern. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Article Snippet: These C@PA-derived clear positive hit and clear negative hit substructures are an important framework to obtain potent multitarget ABCB1, ABCC1, and ABCG2 inhibitors .

Techniques: Derivative Assay

Journal: Computational and Structural Biotechnology Journal

Article Title: Scaffold fragmentation and substructure hopping reveal potential, robustness, and limits of computer-aided pattern analysis (C@PA)

doi: 10.1016/j.csbj.2021.05.018

Figure Lengend Snippet: Preliminary screening of compounds 16 – 25 against ABCB1 (A), ABCC1 (B), and ABCG2 (C) in calcein AM (A and B) and pheophorbide A (C) assays, respectively, using ABCB1-overexpressing A2780/ADR (A), ABCC1-overexpressing H69AR (B), and ABCG2-overexpressing MDCK II BCRP (C) cells as described earlier , , , , . The data were normalized by defining 100% inhibition by the effect value of 10 µM of the reference inhibitors 2 (ABCB1; A), 26 (ABCC1, B), and 27 (ABCG2, C) as reported earlier , . Shown is mean ± standard error of the mean (SEM) of at least three independent experiments. Red mark: triple ABCB1, ABCC1, and ABCG2 inhibitors. a no inhibition; b apparent ABCC1 activation (effect at 10 µM: 12.7% ± 2.4%). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Article Snippet: These C@PA-derived clear positive hit and clear negative hit substructures are an important framework to obtain potent multitarget ABCB1, ABCC1, and ABCG2 inhibitors .

Techniques: Inhibition, Activation Assay

Journal: Computational and Structural Biotechnology Journal

Article Title: Scaffold fragmentation and substructure hopping reveal potential, robustness, and limits of computer-aided pattern analysis (C@PA)

doi: 10.1016/j.csbj.2021.05.018

Figure Lengend Snippet: Concentration-effect curves of compound 23 (●) against ABCB1 (A), ABCC1 (B), and ABCG2 (C) as obtained in calcein AM (A and B) and pheophorbide A (C) assays, respectively, compared to the reference inhibitors 2 (A;■), 26 (B; ■), and 27 (C; ■) applying ABCB1-overexpressing A2780/ADR (A), ABCC1-overexpressing H69AR (B), and ABCG2-overexpressing MDCK II BCRP (C) cells, respectively, as reported earlier , , , , . Shown is mean ± SEM of at least three independent experiments.

Article Snippet: These C@PA-derived clear positive hit and clear negative hit substructures are an important framework to obtain potent multitarget ABCB1, ABCC1, and ABCG2 inhibitors .

Techniques: Concentration Assay

Journal: Computational and Structural Biotechnology Journal

Article Title: Scaffold fragmentation and substructure hopping reveal potential, robustness, and limits of computer-aided pattern analysis (C@PA)

doi: 10.1016/j.csbj.2021.05.018

Figure Lengend Snippet: Pharmacophore model of the most potent triple ABCB1, ABCC1, and ABCG2 inhibitor presented in this work, compound 23 . The five multitarget ABCB1, ABCC1, and ABCG2 features [(i–iv) F1–F4: aromatic/hydrophobic; and (v) F5: acceptor] as reported before are depicted (A), to which compound 23 was aligned to (B). In comparison, the five features for ABCC1 inhibition [(i) F1: aromatic; (ii–iii) F2 and F3: aromatic/hydrophobic; (iv) F4: hydrophobic; and (v) F5: acceptor] as reported before are shown (C), and the respective conformer pose of compound 23 (D). The distances between the pharmacophore features are shown as light green lines. While nonpolar hydrogen atoms were omitted, carbon, oxygen, and nitrogen atoms were colored in green, red, and blue, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Article Snippet: These C@PA-derived clear positive hit and clear negative hit substructures are an important framework to obtain potent multitarget ABCB1, ABCC1, and ABCG2 inhibitors .

Techniques: Comparison, Inhibition