ABSTRACT
Most α2-AR agonists derived from dexme-detomidine have few structure differences between them and have no selectivity for α2A/2B-AR or Gi/Gs,that can lead to the side effect of drugs.To get novel and potent α2A-AR agonists,we built the homology model for human α 2A-AR and α2B-AR to find α2A-AR agonists with higher selectivity.Compound P300-2342 and its 3 analogs sig-nificantly decreased the locomotor activity of mice(P＜0.05).Furthermore,P300-2342 and its 3 analogs inhibited the binding of[3H]rauwolscine to α 2A-AR and α 2B-AR respectively.In α2A-AR-HEK293 cells,P300-2342 decre-ased forskolinstimulatedcAMPpruductionwithoutincreas-ing cAMP pruduction,that indicated the P300-2342 acti-vating α2A-AR coupling with Gαi/o pathway without Gαs coupling.P300-2342 had no agonistic and antagonistic activities on α 2B-AR.Similar results were shown in 3 analogs of P300-2342.The docking results showed that P300-2342 formed the π-hydrogen bonds with Y394,V114 of α2A-AR,and with V93 of α2B-AR.3 analogs of P300-2342 formed several π-hydrogen bonds with V114,Y196,F390 of α 2A-AR and with V93 of α 2B-AR.We believe that these molecules can serve as leads for fur-ther optimization of α2A-AR agonists with potentially few side effects.
ABSTRACT
Objective:To investigate the characteristics of attention bias in Wilson disease(WD) patients with different levels of state-trait anxiety.Methods:The emotional Stroop paradigm and the state-trait anxiety inventory(STAI) were used to evaluate the anxiety level and the characteristics of attention bias in 49 inpatients with WD.SPSS 25.0 software was used for statistical analysis.Independent sample t-test was used for comparison between the two groups.Multiple linear regression analysis was used to evaluated the influencing factors of attentional bias response time. Results:(1) In WD patients, the response times measured under the positive, negative and neutral words in the high trait anxiety group((867.0±172.1)ms, (877.0±167.7)ms, (898.4±169.8)ms, respectively) were significantly higher than the low trait anxiety group((771.9±128.9)ms, (770.9±110.4)ms, (778.4±120.1)ms, respectively) and the differences were statistically significant( t=-2.183, -2.605, -2.847, all P<0.05). The response times under the positive, negative and neutral word measured in the high state anxiety group((866.9±171.9)ms, (867.8±173.8)ms, (889.8±173.5)ms, respectively) were higher than those of the low state anxiety group((771.9±129.2)ms, (780.4±109.3)ms, (787.3±123.0)ms, respectively) and the differences were statistically significant( t=-2.177, -2.116, -2.378, all P<0.05). (2) Multiple linear regression analysis showed that the total score of trait anxiety ( B=4.584, 4.671, 5.376, P=0.020, 0.015, 0.008) and age ( B=9.314, 7.864, 7.505, P=0.002, 0.008, 0.014) were the influencing factors of response times measured under the positive, negative and neutral emotion words. Conclusion:Anxiety will lead patients with WD to show more negative attention bias, and trait anxiety can significantly predict the characteristics of attention bias.