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Fig. 5 | Journal of Cheminformatics

Fig. 5

From: The polypharmacology browser: a web-based multi-fingerprint target prediction tool using ChEMBL bioactivity data

Fig. 5

Prediction of targets of CIS22a using PPB and comparison with other web-based tools. In case of ChEMBLPred target prediction models (10 μM) were downloaded from ChEMBL website and implemented locally using RDkit and python. a Structure of CIS22a. b Confirmed side targets of CIS22a. c Targets detected with no significant binding affinity for CIS22a. Targets which were found and not found by the fingerprints used in PPB and external web-based tools are indicated with green and black dots, respectively. For external web-based tools, at the maximum top 30 predicted targets were considered. The prediction performance of ChemProt, HitPick, TarPred, SPiDER, PASS, TarFishDock and Drar web based tools listed in Table 1 are not shown due to technical failures or no applicability in the context. d Structure, ChEMBL id and tanimoto coefficient for bioactive compounds which linked the targets to CIS22a, indicated with the name of fingerprints in parentheses. Target full names: Adrenergic α1A (ADRA1A) and α2A (ADRA2A) receptor, Adrenergic β1 (ADRB1) and β2 (ADRB2) receptor, Cannabinoid 1 (CB1) and 2 (CB2) receptor, Voltage dependent L- (CACNA1S) and N-type (CACNA1B) Ca2+ channel, Cholinergic muscarinic receptor 1 (CHRM1) and 2 (CHRM2), Dopamine receptor subtypes D1-4 (DRD1-4), Gamma aminobutyric acid receptor (GABA), 5-hydroytryptamine receptor 3 (5-HT3), 5-hydroytryptamine receptor 1A (HTR1A), 1B (HTR1B), 2A (HTR2A) and 2B (HTR2B), Voltage gated potassium channel subfamily H member 2 (HERG), N-methyl-d-aspartate receptor (NMDA), µ opioid receptor (OPRM), voltage gated Na+ channel (SCN2A)

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