Studies on the antibacterial activities and molecular mechanism of GyrB inhibitors by 3D-QSAR, molecular docking and molecular dynamics simulation

Wang, Fangfang; Yang, Wei; Zhou, Bo

doi:10.1016/j.arabjc.2022.103872

Cited by 6 publications

(1 citation statement)

References 67 publications

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“…One of the advantages of CoMSIA is the ability to isolate and observe the effects of various physical and chemical properties on biological activity through 3D correlation contour maps. This Frontiers in Pharmacology frontiersin.org contour map helps to identify the important regions of the molecular field that affect the biological activity, and also to mark the molecular field features that contribute significantly to the active site of ligands and receptors (Chen et al, 2021;Wang et al, 2022).…”

Section: Comsia Contour Mapsmentioning

confidence: 99%

3D,2D-QSAR study and docking of novel quinazolines as potential target drugs for osteosarcoma

Lian

Sang

et al. 2023

Front. Pharmacol.

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Background: Quinazolines are an important class of benzopyrimidine heterocyclic compounds with a promising antitumor activity that can be used for the design and development of osteosarcoma target compounds.Objective: To predict the compound activity of quinazoline compounds by constructing 2D- and 3D-QSAR models, and to design new compounds according to the main influencing factors of compound activity in the two models.Methods: First, heuristic method and GEP (gene expression programming) algorithm were used to construct linear and non-linear 2D-QSAR models. Then a 3D-QSAR model was constructed using CoMSIA method in SYBYL software package. Finally, new compounds were designed according to molecular descriptors of 2D-QSAR model and contour maps of 3D-QSAR model. Several compounds with optimal activity were used for docking experiments with osteosarcoma related targets (FGFR4).Results: The non-linear model constructed by GEP algorithm was more stable and predictive than the linear model constructed by heuristic method. A 3D-QSAR model with high Q2 (0.63) and R2 (0.987) values and low error values (0.05) was obtained in this study. The success of the model fully passed the external validation formula, proving that the model is very stable and has strong predictive power. 200 quinazoline derivatives were designed according to molecular descriptors and contour maps, and docking experiments were carried out for the most active compounds. Compound 19g.10 has the best compound activity with good target binding capability.Conclusion: To sum up, the two novel QSAR models constructed were very reliable. The combination of descriptors in 2D-QSAR with COMSIA contour maps provides new design ideas for future compound design in osteosarcoma.

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Section: Comsia Contour Mapsmentioning

confidence: 99%