C@PA: Computer-Aided Pattern Analysis to Predict Multitarget ABC Transporter Inhibitors

Abstract

Based on literature reports of the last two decades, a computer-aided pattern analysis (C@PA) was implemented for the discovery of novel multitarget ABCB1 (P-gp), ABCC1 (MRP1), and ABCG2 (BCRP) inhibitors. C@PA included basic scaffold identification, substructure search and statistical distribution, as well as novel scaffold extraction to screen a large virtual compound library. Over 45,000 putative and novel broad-spectrum ABC transporter inhibitors were identified, from which 23 were purchased for biological evaluation. Our investigations revealed five novel lead molecules as triple ABCB1, ABCC1, and ABCG2 inhibitors. C@PA is the very first successful computational approach for the discovery of promiscuous ABC transporter inhibitors.

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

“…Unfortunately, only a small fraction of the 49 existing ABC transporters can be considered as well-studied, in particular ABCB1 [8] , [14] , [15] , [16] , [17] , [18] , [19] , ABCB11 [20] , [21] , [22] , ABCC1 [1] , [4] , [14] , [15] , [17] , [23] , [24] , and ABCG2 [14] , [15] , [17] , [25] . Less-studied ABC transporters that have found much less attention are ABCC2, ABCC4–5, and ABCC10 [1] , [4] , [14] , [24] , [26] , as well as – to a lesser extend – ABCA1 [27] , [28] , [29] , [30] , ABCB4 [14] , ABCC3 [1] , [4] , [14] , [24] , as well as ABCC7–9 and ABCC11 [1] , [4] , [31] , [32] .…”

“…As a logical consequence, the number of synthetic approaches to gain novel lead structures and potent modulators of ABC transporters is also very unequally distributed amongst the ABC transport proteins, and very scarce for under-studied ABC transporters. While many hundreds of small-molecule modulators of ABCB1 [14] , [15] , [16] , [17] , [18] , [19] , ABCC1 [1] , [4] , [14] , [15] , [17] , [23] , [24] , and ABCG2 [14] , [15] , [17] , [25] exist, synthetic approaches to target other ABC transporters have barely been reported. Rare exceptions are, for example, ABCC4 [33] , [34] , ABCC8 [35] , or ABCC10 [36] .…”

“…However, these approaches always took only one transporter into account, completely leaving out the potential of multitarget inhibition. Multitargeting is a promising approach to explore under-studied ABC transporters by targeting similar or mutually overlapping binding sites [15] , [73] , [74] . Several pharmacological drugs have already been revealed as (weak) pan-ABC transporter inhibitors (=inhibiting several ABC transporters simultaneously), as for example, benzbromarone ( 1 ; ABCB1 [75] , ABCB11 [20] , ABCC1-6 [23] , [24] , [58] , [76] , [77] , and ABCG2 [75] ), cyclosporine A ( 2 ; ABCA1 [27] , ABCB1 [16] , ABCB4 [78] , ABCB11 [20] , ABCC1–2 [23] , [58] , ABCC10 [24] , ABCG1–2 [75] , [79] ), glibenclamide (glyburide, 3 ; ABCA1 [29] , ABCB11 [20] , ABCC1 [23] , ABCC5 [80] , ABCC7–9 [81] , [82] , [83] , ABCG2 [58] ), probenecid ( 4 ; ABCA8 [84] , ABCC1–6 [23] , [24] , [85] , [86] , [87] , ABCC10 [88] ), verapamil ( 5 ; ABCA8 [84] , ABCB1 [16] , ABCB4–5 [54] , [78] , ABCB11 [89] , ABCC1 [23] , ABCC4 [90] , ABCC10 [88] , ABCG2 [58] ), or verlukast (MK571, 6 ; ABCA8 [84] , ABCB4 [78] , ABCB11 [20] , ABCC1–5 [23] , [58] , [80] , [87] , [91] , ABCC10–11 [24] , [92] , ABCG2 [58] ).…”

“…As indicated above, ABCB1, ABCC1, and ABCG2 are the most investigated and understood ABC transporters, and hence, represent model targets for the generation of pan-ABC transporter inhibitors [15] . However, even for these well-studied ABC transporters, only 133 broad-spectrum ABCB1, ABCC1, and ABCG2 inhibitors were described to date [15] , [43] , [45] , [62] , [67] , [75] , [93] , [94] , [95] , [96] , [97] , [98] , [99] , [100] , [101] , [102] , [103] , [104] , [105] , [106] , [107] , [108] , [109] , [110] , [111] , [112] , [113] , [114] , [115] , [116] , [117] , [118] , [119] , [120] , [121] , [122] , [123] , [124] , [125] , [126] , amongst which only 56 exerted their effects below 10 µM [15] , [43] , [45] , [62] , [67] , [75] , [93] , [94] , [95] , [98] , [99] , [101] , [103] , [107] , [109] , [110] , [111] , [112] , [113] , [118] , [119] , [120] , [121] ,…”

“…Recently, we were the first to report on a novel computer-aided pattern analysis (C@PA) approach for the prediction of potent multitarget ABCB1, ABCC1, and ABCG2 inhibitors, discovering compounds 7 – 11 ( Fig. 2 ) [15] . As the data regarding ABCB1, ABCC1, and ABCG2 is much more advanced than toward other transporters, we continued to improve C@PA’s prediction capabilities, which is reported in the presented study.…”