QSAR, molecular dynamics, and biological evaluation of novel myeloperoxidase inhibitors via ligand-based pharmacophore modeling as potential anticancer agents
Aug 2026· Journal of Computer-Aided Molecular Design· Vol 40· 0 citations· 57 references
Medicine
TL;DR
The findings from molecular docking, 500-ns molecular dynamics simulations, MM-GBSA calculations, and alanine scanning analyses collectively corroborate a stable binding mode of BTB11556 within the MPO active site, support further investigation of BTB11556 as a candidate compound associated with MPO-targeted therapeutic strategies.
This study highlights natural diterpenoids and coumarin glycosides as promising scaffolds for caspase-1 inhibition and demonstrates that integrating QSAR modeling with structure-based approaches provides an efficient strategy for discovering potential anti-inflammatory drug candidates.
Yusuf Şeflekçi, Alper Yılmaz, Abdulilah Ece· Molecules· 0 citations
Several structurally novel compounds are identified as promising potential VEGFR2 inhibitors and supports the effectiveness of integrating pharmacophore modeling, QSAR analysis, molecular docking, and experimental validation for anticancer drug discovery.
O. Meziani, Samira Ait Kaki, F. Ferkous et al.· Journal of Computer-Aided Mo...· 0 citations
Genistein and hematoxylin demonstrate promising molecular interactions and pharmacological profiles as potential natural RR inhibitors and supports further preclinical development as anticancer agents.
Oun Deli Khudhair, Muhammad Azrul Zabidi, A. M. Gazzali et al.· Current Computer - Aided Dru...· 0 citations
Breast cancer is characterised by the uncontrolled growth of cells within
the mammary glands, which can later spread to adjacent tissues. The current treatment options include alkylating agents, intercalating agents, topoisomerase inhibitors, antimetabolites, and antimitotic drugs. Computer-aided drug design has contributed in a large way to the development of anticancer drugs. The objective of this study was to perform pharmacophore optimisation of 4-
aminoquinoline derivatives using QSARINS software for the development of QSAR models for anticancer activity.
A series of thirty-six 4-aminoquinoline derivatives was used to generate 2D and fingerprint-based QSAR models using the Genetic Algorithm-Multiple Linear Regression (GA-MLR)
method. The resulting statistical parameters and graphical data were evaluated, and models with
strong statistical performance were selected for further analysis.
The 2D QSAR model exhibited R² = 0.9757 and Q² = 0.9490, and the fingerprint-based
QSAR model displayed values of R² = 0.9884 and Q² = 0.9736. Both models showed internal robustness with limited external predictive capability.
The results indicate that electronic and steric factors around the 4-aminoquinoline nucleus strongly influence anticancer activity. The optimised pharmacophore provides a framework
for designing new, more potent anticancer agents.
The optimised pharmacophore indicates the contribution of electronegative substituents at the 7th position of the quinoline ring, along with a dimethylamino biphenyl group at the 3rd
position, for better anticancer activity. Considering the limitations of the present study, namely, limited external predictive capability, further refinement of the models would be required.
S. Patil, K. Asgaonkar, Darshani Gholap et al.· Current Enzyme Inhibition· 0 citations
Computational findings support the prioritization of X14 for further experimental validation in glioblastoma therapy, and generally favorable ADMET profiles were observed, hepatotoxicity alerts were predicted for all compounds, which represents an important limitation supporting the prioritization of X14.
Youssef Briach, M. Er-rajy, Jamal Elkhabchi et al.· Biointerface Research in App...· 0 citations
