iven on the introduction of electro Caspase 10 Purity & Documentation unfavorable groups to improve compound activity in this model. The -CF3 group close to C-4 is surrounded by significant red blocks, indicating that the bulkly and negatively charged group has a good contribution for the activity, for instance, compound 33 (pIC50 = six.056) compound 31 (pIC50 = five.658), compound four (pIC50 = 5.051) compound 3 (pIC50 = 4.602). As shown in Fig. 6(f), the red contour lines on the R3 group indicate that it can be advantageous to boost the electronegativity of the group here. Among the 35 compounds, compounds 31, 32, and 33 are compounds with fluorine atom of R3 , which have high inhibitory activity against SARS-CoV-2 (pIC50 value is five.658, five.509, 6.056, respectively). The activity of compound 33(pIC50 = 6.056, R3 =-F) is larger than that of compound 28 (pIC50 = five.602, R3 =-H), and nearly all compounds with negative R3 groups show better inhibitory activity. three.1.3. HQSAR evaluation The efficiency on the HQSAR model is affected by parameters which include HL (hologram length), FD (fragment discrimination kind) and FS (fragment size), and these parameters need to be refined and optimized. We initially use the default FS (4-7), all HLs and various FD combinations to produce the model. Then selecting different FS to study its influence around the HQSAR evaluation outcomes and acquiring the optimal HQSAR model. The HQSAR model of 37 statistical parameters is shown in Table S3. The outcomes show that the model produce when FD is “A + B + C + Ch” and FS is “4-7” could be the greatest HQSAR model: 71 for hologram length andJ.-B. TONG, X. ZHANG, D. LUO et al.HIV-1 web Chinese Journal of Analytical Chemistry 49 (2021) 63Fig. 7. Regression evaluation graph (a) and line graph (b) of experimental activity and predicted activity of the data set of HQSAR model.Fig. 8. HQSAR contribution maps of compound 3(a), 7(b), 25(c),26(d), 27(e) and 29(f). The red finish in the spectrum (red, orange-red, and orange) reflects the unfavorable contribution for the activity, the green end (yellow, blue and green) represents a optimistic impact, along with the middle contribution is represented by white.four for fragment size, showing the highest 2 (0.704) and two (0.958) with six elements and also the typical error of 0.091. Fig. 7(a) shows the pIC50 correlation diagram in the experimental and predicted values with the HQSAR model data set. All samples are evenly distributed close to the Y=X line, displaying a good linear connection. Fig. 7(b) shows that the predicted pIC50 values of these compounds are virtually in agreement using the experimental values. Both the low activity compounds (2,3,7,8,25,26,27,29) and the highest activity compounds (33) have fantastic predictive capability, indicating that the HQSAR model includes a satisfactory predictive capability. These outcomes confirm that the HQSAR model has excellent predictive capability for cyclic sulfonamide derivatives. Thus, the established HQSAR model may be made use of for the screening and style of novel inhibitor molecules. three.1.4. Interpretation of HQSAR contribution map HQSAR supplies color-coded diagrams as direct evidence from the contribution of person atoms to biological activity. Within this study, the selected compound 33 using the very best activity is taken because the representative for the color-coded HQSAR model analysis, and its single atomic contribution is shown in Fig. S3. Fig. eight shows the atomic contribution diagrams (3, 7, 25, 26, 27, 29) of every series of representative molecules with lowest activity. It is worth noting that the frequent skelet