Three- and four-class classification models for P-glycoprotein inhibitors using counter-propagation neural networks

Abstract

P-glycoprotein (P-gp) is an ATP binding cassette (ABC) transporter that helps to protect several certain human organs from xenobiotic exposure. This efflux pump is also responsible for multi-drug resistance (MDR), an issue of the chemotherapy approach in the fight against cancer. Therefore, the discovery of P-gp inhibitors is considered one of the most popular strategies to reverse MDR in tumour cells and to improve therapeutic efficacy of commonly used cytotoxic drugs. Until now, several generations of P-gp inhibitors have been developed but they have largely failed in preclinical and clinical studies due to lack of selectivity, poor solubility and severe pharmacokinetic interactions. In this study, three models (SION, SIO, SIN) to classify specific 'true' P-gp inhibitors as well as three other models (CPBN, CPB1, CPN) to distinguish between P-gp inhibitors, CYP 3A inhibitors and co-inhibitors of these proteins with rather high accuracy values for the test set and the external set were generated based on counter-propagation neural networks (CPG-NN). Such three and four-class classification models helped provide more information about the bioactivities of compounds not only on one target (P-gp), but also on a combination of multiple targets (P-gp, CYP 3A).

Synthesis, In Silico and In Vitro Evaluation of Some Flavone Derivatives for Acetylcholinesterase and BACE-1 Inhibitory Activity

“…During the last few years, flavonoids, including flavones, have attracted much interest because of their diverse bioactivities [ 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ]. Recent studies have indicated the abilities of flavones in inhibiting many enzymes [ 25 , 26 , 27 , 28 , 29 ], especially AChE [ 30 ] and BACE-1 [ 31 , 32 ].…”

Chalcone Derivatives as Potential Inhibitors of P-Glycoprotein and NorA: An In Silico and In Vitro Study

“…In this study, this model was applied to a novel dataset composed of 95 in-house designed chalcone derivatives, among which 27 molecules were predicted as potential regulators of P-gp, as their calculated IC50 values were below 15 μ M, the threshold to distinguish P-gp inhibitors from noninhibitors [ 47 ]. Interestingly, these chalcones were also deemed P-gp modulators by most of the machine learning classification models used for predicting regulators of this efflux pump that were reported in our previous study on this topic [ 48 ], denoting a high agreement level of these virtual screening tools on selecting potential inhibitors of P-gp from a pool of different chalconic compounds. The 2D structures of these 27 derivatives are provided in Figure S1 .…”

Synthesis of Novel Chalcones as Acetylcholinesterase Inhibitors

“…Docking process was utilized BioSolveIT LeadIT with the following options: The method in which base fragment placed in binding pocket was Triangle Matching; the maximum number of solutions per iteration was set to 1000; the maximum number of solutions per fragmentation was set to 200; the number of poses to keep for further analysis of interaction was set to 10. The best conformation is the one that has the most minus docking score [33][34][35].…”