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. 2020 May 28;7(13):1903451. doi: 10.1002/advs.201903451

Figure 2.

Figure 2

Virtual screening of small‐molecule candidates using virtual screening model score algorithm. a) Top 10 candidate small molecules with the highest score were most likely predicted to target the loop of miR‐214 and ATF4 mRNA. OB‐1: 3′‐geranyl‐4′,7‐dihydroxyisoflavone; OB‐2: 6‐hydroxykaempferol 3,6‐diglucoside; OB‐3: 3′‐hydroxygenkwanin; OB‐4: quercetin‐3‐O‐d‐glucosyl]‐(1‐2)‐l‐rhamnoside; OB‐5: 3′,7‐dihydroxy‐4′‐methoxyisoflavone‐7‐beta‐d‐glucopyranoside; OB‐6: hydroxyevodiamine; OB‐7: cycloastragenol; OB‐8: kaempferol‐7‐O‐β‐d‐glucopyranoside; OB‐9: sutchuenmedin A; OB‐10: 2″‐O‐beta‐l‐galactopyranosylorientin. b) Top 10 candidate small molecules with the highest score were most likely predicted to target the loop of miR‐214 and TRAF3 mRNA. OC‐1: 28‐hydroxy‐3‐oxoolean‐12‐en‐29‐oic acid; OC‐2: 17,21‐dihydroxypregnenolone; OC‐3: 7‐hydroxyflavone‐beta‐d‐glucoside; OC‐4: 3,6,7‐trimethylquercetagetin; OC‐5: 3‐O‐acetyl‐16alpha‐hydroxytrametenolic acid; OC‐6: naringenin‐7‐O‐glucuronide; OC‐7: persicoside; OC‐8: tectorigenin 7‐O‐xylosylglucoside; OC‐9: cajaninstilbene acid: OC‐10: 1‐O‐deacetyl‐2α‐hydroxykhayanolide E.