QSAR modeling identified effective pyrimidine analogues as BCL2 and EGFR inhibitors, suggesting potential therapeutic avenues.
The CoMFA models MMFF94 were generated from training set of 45 molecules with pIC50 value ranging from 3.4661 to 5.2749 using leave-one-out PLS analysis with an optimized component of 1 to give a good cross-validated correlation coefficient q2 of 0.787, which suggest that the model should be reasonable tool for predicting the IC50 values. The CoMSIA model, consisting steric (S), electrostatic (E), hydrophobic (H), Donor (D) and acceptor (A) fields, can be generated using these fields in different combinations. The results of CoMSIA analysis with different combination on different charge. The CoMSIA model with a combination of steric, electrostatic, hydrophobic, donor and acceptor fields gave a good cross-validated correlation coefficient q2 of 0.805 with an optimized component of 1. A good non-cross-validated correlation coefficient r2 of 0.833 was attained. All the designed compounds as per QSAR, docking were subjected to evaluate from previously generated QSAR model their activity were predicted .While predicting the activity, it was found that out of thirty nine designed compounds, seven compounds were supposed to having a better activity Keywords: CoMSIA, CoMFA, HQSAR, Docking, Pyrimidine, BCL2 proteins inhibitors, EGFR
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Mandal et al. (2025) studied this question.
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