Table 2 Performance of FLSF (FLuorescence prediction with fluoroScaFfold-driven model) in predicting four photophysical parameters towards different fluorescent scaffolds
From: A modular artificial intelligence framework to facilitate fluorophore design
Scaffold | MAE (Number of data) | |||
|---|---|---|---|---|
λabs (nm) | λem (nm) | ΦPL | εmax (in log10εmax) | |
Squaraine | 15.43 (83) | 15.52 (30) | 0.17 (14) | 0.24 (24) |
Naphthalimide | 12.36 (88) | 17.46 (72) | 0.21 (70) | 0.21 (40) |
Coumarin | 10.77 (272) | 13.58 (220) | 0.10 (165) | 0.22 (248) |
Carbazole | 12.59 (388) | 14.77 (309) | 0.11 (180) | 0.21 (99) |
Cyanine | 11.79 (310) | 16.20 (258) | 0.12 (185) | 0.16 (209) |
BODIPY | 6.44 (1412) | 7.37 (1315) | 0.11 (1215) | 0.14 (515) |
Triphenylamine | 16.91 (641) | 18.11 (353) | 0.17 (211) | 0.22 (162) |
Porphyrin | 29.43 (31) | 11.15 (20) | 0.06 (18) | 0.20 (825) |
PAH | 11.70 (630) | 16.02 (591) | 0.13 (465) | 0.30 (322) |
Acridine | 16.59 (242) | 14.42 (182) | 0.14 (99) | 0.27 (720) |
[6 + 5] | 15.21 (689) | 16.77 (540) | 0.12 (390) | 0.25 (349) |
[6 + 6] | 14.86 (259) | 17.02 (210) | 0.13 (159) | 0.27 (305) |
6-n-5 | 12.00 (361) | 12.68 (282) | 0.11 (214) | 0.25 (233) |
6-n-6 | 13.30 (591) | 12.91 (521) | 0.10 (405) | 0.25 (599) |
Benzene | 20.42 (197) | 13.97 (161) | 0.12 (129) | 0.34 (138) |
