Hypo1 Case Study

Predictive ability of Hypo1
To confirm the predictive power of Hypo1, each compound in training set was estimated through regression analysis method. The training set compounds classified into three groups: highly active IC50 < 100 nM, +++; moderately active IC50 < 100 nM _ 1,000 nM, ++; inactive IC50 <1,000 nM _ > 10,000 nM, +. The estimated activities by Hypo1 pharmacophore model and experimental activities of 21 training set compounds presented in Table 1. The error value is calculated by the ratio between the estimated and experimental activities. The negative error value indicates that the estimated IC50 value is lower than the experimental activity whereas, the positive error value indicates that the estimated IC50 value is higher than
The best quantitative pharmacophore model, Hypo 1, was characterized by the highest cost difference (73.09), best correlation coefficient (0.95) and lowest RMSD (0.94) respectively. The best Hypo1 consisted of two HBA, one HY and one RA features. Hypo1 was further validated by test set, Fischer randomization test and decoy set methods. The test set containing 40 compounds was used for investigating the predictive ability of Hypo1 and resulted with a correlation coefficient of 0.914. Another validation method also has provided reliable results on the strength of Hypo 1. This was further validated Hypo1 was used as a 3D query in chembridge and Maybridge database screening. The hit compounds were then subjected to filtering by maximum omitted feature values greater than 10. The compounds were sorted by applying the drug-like filter such as ADMET and Lipinski’s rule of five. Further refine the retrieved hits of 2209 compounds along with training set were carried out for molecular docking studies. Finally six structurally diverse compounds BTB01875, BTB09994, BTB14527, BTB14784, Compound 2479 and BTB06317 with high GOLD score and binding energy for crystal structures of KIF11 were selected. It showed hydrogen bond interaction with Tyr104, Tyr352 and Asn289 with important active site residues similar to that of BI8 inhibitor. These results are quite consistent with the docking analysis which illustrates the participation of these six hit compounds; BTB06317 has strong moieties in the key ligand-receptor interactions. To calculate the electronic properties of our hit compounds were subjected to compute the DFT studies. By comparing the values of HOMO- LUMO and the energy gap between the HOMO and LUMO revealed that hit compounds have good electronic properties. Among the six hit compounds BTB01875, BTB09994,