1Department of Chemistry, Faculty of Science and Technology, Universitas Sembilanbelas November Kolaka, Kolaka, Indonesia
2Department of Mathematics, Faculty of Science and Technology, Universitas Sembilanbelas November Kolaka, Kolaka, Indonesia
BibTex Citation Data :
@article{JKSA76970, author = {Muhamad Jalil Baari and Salim Salim and Firnayanti Mbuli}, title = {Rational Design of Cyanopyridine Derivatives as PIM-1 Kinase Inhibitors: In Silico Studies of QSAR, ADMET, and Interaction Analysis}, journal = {Jurnal Kimia Sains dan Aplikasi}, volume = {29}, number = {2}, year = {2026}, keywords = {Anti-breast cancer; Cyanopyridine derivatives; In silico; PIM-1 kinase; QSAR}, abstract = { Breast cancer is one of the most prevalent diseases among women and ranks among the top five leading causes of cancer-related deaths worldwide. Current therapeutic approaches remain suboptimal in addressing the highly aggressive progression of cancer cells. A simple method to initiate the drug discovery process is Quantitative Structure-Activity Relationship (QSAR) analysis. Previous experimental studies have reported that cyanopyridine derivatives exhibit potent inhibitory effects on PIM-1 kinase, a key regulator in MCF-7 human breast cancer cells. In this study, we performed QSAR analysis on structurally modified cyanopyridine derivatives to design novel anti-breast cancer agents. The research methodology included: (1) molecular geometry optimization using the PM3 semi-empirical method, (2) calculation of QSAR descriptors (hydrophobic, electronic, and steric parameters), and (3) rational molecular design based on the derived QSAR model. Optimizations and calculations were performed using HyperChem software. Multiple Linear Regression (MLR) analysis and external validation generated the best QSAR equation for Model 1: log (1/IC 50 ) = 151.273 + 1884.726qC 1 − 4663.478qC 4 + 5431.564qC 5 + 1501.074qN 7 + 592.015qO 10 . This model exhibits better core statistical metrics, with an R = 0.868, R 2 = 0.753, SEE = 0.272, R 2 ext = 0.9342, and Q 2 ext = 0.8717. In addition, statistical parameters of the Y-scrambling test indicate the robustness of the best QSAR model (average R scramble = 0.3881; average R 2 scramble = 0.1558). A promising drug candidate was identified based on antiproliferative activity predicted by the best QSAR model. A subsequent in silico evaluation comprehensively assessed their pharmacokinetic and toxicity profiles. The results revealed that synthesized and designed derivatives successfully satisfied most critical pharmaceutical criteria. The pharmacokinetic profile of this compound was comparable to the native ligand (VRV), as well as established reference drugs like tamoxifen and doxorubicin. 2-[4-(5-Cyano-6’-fluoro-1-methyl-6-oxo-1,6-dihydro-[2,3’]bipyridinyl-4-yl)-2-methoxy-phenoxy]- N -phenyl-acetamide (8M) was considered the best potential drug candidate due to its high anti-breast cancer efficacy and relatively low toxicity. The molecular docking study demonstrates that the binding affinity of the designed cyanopyridine derivatives for the PIM-1 kinase receptor was in the range of −9.5 to −9.7 kcal·mol −1 , which is comparable to that of doxorubicin (10.0 kcal·mol −1 ). Moreover, these values surpass the binding affinity of the native ligand (9.2 kcal·mol −1 ) and tamoxifen (8.0 kcal·mol −1 ). This finding was further corroborated by molecular dynamics simulations, which demonstrated the stability of the interactions. Therefore, these designed compounds have potential as novel anti-breast cancer drugs. }, issn = {2597-9914}, doi = {10.14710/jksa.29.2.%p}, url = {https://ejournal.undip.ac.id/index.php/ksa/article/view/76970} }
Refworks Citation Data :
Breast cancer is one of the most prevalent diseases among women and ranks among the top five leading causes of cancer-related deaths worldwide. Current therapeutic approaches remain suboptimal in addressing the highly aggressive progression of cancer cells. A simple method to initiate the drug discovery process is Quantitative Structure-Activity Relationship (QSAR) analysis. Previous experimental studies have reported that cyanopyridine derivatives exhibit potent inhibitory effects on PIM-1 kinase, a key regulator in MCF-7 human breast cancer cells. In this study, we performed QSAR analysis on structurally modified cyanopyridine derivatives to design novel anti-breast cancer agents. The research methodology included: (1) molecular geometry optimization using the PM3 semi-empirical method, (2) calculation of QSAR descriptors (hydrophobic, electronic, and steric parameters), and (3) rational molecular design based on the derived QSAR model. Optimizations and calculations were performed using HyperChem software. Multiple Linear Regression (MLR) analysis and external validation generated the best QSAR equation for Model 1: log (1/IC50) = 151.273 + 1884.726qC1 − 4663.478qC4 + 5431.564qC5 + 1501.074qN7 + 592.015qO10. This model exhibits better core statistical metrics, with an R = 0.868, R2 = 0.753, SEE = 0.272, R2ext = 0.9342, and Q2ext = 0.8717. In addition, statistical parameters of the Y-scrambling test indicate the robustness of the best QSAR model (average Rscramble = 0.3881; average R2scramble = 0.1558). A promising drug candidate was identified based on antiproliferative activity predicted by the best QSAR model. A subsequent in silico evaluation comprehensively assessed their pharmacokinetic and toxicity profiles. The results revealed that synthesized and designed derivatives successfully satisfied most critical pharmaceutical criteria. The pharmacokinetic profile of this compound was comparable to the native ligand (VRV), as well as established reference drugs like tamoxifen and doxorubicin. 2-[4-(5-Cyano-6’-fluoro-1-methyl-6-oxo-1,6-dihydro-[2,3’]bipyridinyl-4-yl)-2-methoxy-phenoxy]-N-phenyl-acetamide (8M) was considered the best potential drug candidate due to its high anti-breast cancer efficacy and relatively low toxicity. The molecular docking study demonstrates that the binding affinity of the designed cyanopyridine derivatives for the PIM-1 kinase receptor was in the range of −9.5 to −9.7 kcal·mol−1, which is comparable to that of doxorubicin (10.0 kcal·mol−1). Moreover, these values surpass the binding affinity of the native ligand (9.2 kcal·mol−1) and tamoxifen (8.0 kcal·mol−1). This finding was further corroborated by molecular dynamics simulations, which demonstrated the stability of the interactions. Therefore, these designed compounds have potential as novel anti-breast cancer drugs.
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