CoMFA and docking studies of 2-phenylindole derivatives with anticancer activity

Liao, Si Yan; Li, Qian; Miao, Ti Fang; Lu, Hai Liang; Zheng, Kang

doi:10.1016/j.ejmech.2008.12.020

Cited by 42 publications

(18 citation statements)

References 24 publications

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“…The steric and electrostatic energies from CoMFA and CoMSIA were quite effective for understanding important non-covalent and shape-dependent interactions between small compounds and their target protein because CoMFA and CoMSIA models are derived based upon the assumption that 3D structures of input compounds are aligned according to their biologically active conformations when compounds bind to and interact with their target protein [16,17]. Although there is no particular alignment method which produces biologically active conformations of compounds, plausible bioactive conformations of compounds can be produced by several different alignment methods: ligandbased, pharmacophore-based, and receptor-guided.…”

Section: Alignments For Comfa and Comsiamentioning

confidence: 99%

QM/MM based 3D QSAR models for potent B-Raf inhibitors

Chung

Cho

et al. 2010

J Comput Aided Mol Des

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Three dimensional (3D) quantitative structure-activity relationship studies of 37 B-Raf inhibitors, pyrazole-based derivatives, were performed. Based on the co-crystallized compound (PDB ID: 3D4Q), several alignment methods were utilized to derive reliable comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. Receptor-guided alignment with quantum mechanics/molecular mechanics (QM/MM) minimization led to the best CoMFA model (q (2) = 0.624, r (2) = 0.959). With the same alignment, a statistically reliable CoMSIA model with steric, H-bond acceptor, and hydrophobic fields was also derived (q (2) = 0.590, r (2) = 0.922). Both models were validated with an external test set, which gave satisfactory predictive r (2) values of 0.926 and 0.878, respectively. Contour maps from CoMFA and CoMSIA models revealed important structural features responsible for increasing biological activity within the active site and explained the correlation between biological activity and receptor-ligand interactions. New fragments were identified as building blocks which can replace R1-3 groups through combinatorial screening methods. By combining these fragments a compound with a high bioactivity level prediction was found. These results can offer useful information for the design of new B-Raf inhibitors.

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Section: Alignments For Comfa and Comsiamentioning

confidence: 99%

QM/MM based 3D QSAR models for potent B-Raf inhibitors

Chung

Cho

et al. 2010

J Comput Aided Mol Des

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“…This is also correlated with a previous comparative molecular field analysis (CoMFA) study of 2-phenylindole derivatives by Liao and co-workers. 33 On the other hand, the presence of partially negative charged functions is suitable around the R position ( Figure 1) as suggested by the macro red contours of the CoMSIA contour maps ( Figure 6). This result seemed to signify the importance of the para-methoxy substitution on the phenyl ring of the R position and matching with the previous study.…”

Section: -39 Etc)mentioning

confidence: 99%

“…This result seemed to signify the importance of the para-methoxy substitution on the phenyl ring of the R position and matching with the previous study. 33 The unfavourable hydrophobic field (cyan contour) cover the R′ substitution and cover a part of the phenyl ring of Y substitution (Figure 1) of the indole-based derivatives. Similarly, the D r a f t hydrogen bond acceptor field was found to be unfavourable near the R′ substitution ( Figure 1).…”

Section: -39 Etc)mentioning

confidence: 99%

Exploring structural requirements of unconventional Knoevenagel-type indole derivatives as anticancer agents through comparative QSAR modeling approaches

et al. 2016

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Indole ring system is considered as a versatile scaffold in the pharmaceutical field. In this article, comparative QSAR modeling (2D-QSAR, 3D-QSAR; kNN-MFA and CoMSIA) was performed on some Knoevenagel-type cytotoxic indole derivatives to understand the structural requirements for the cytotoxic property of these compounds. The 2D-QSAR model was statistically significant and imparted high predictive ability (n Train = 30; R = 0.917; R However, hydrophobic features in R′ region are unfavourable for the biological activity. The chemical and structural features identified from the study may provide important avenues to modulate the structure of these indoles to a desirable biological end point.

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“…As a useful methodology for studying the interaction mechanism, receptor based molecular docking analysis can offer vivid interaction on picture between a ligand and an acceptor [9]. Combined 3D-QSAR and docking study could offer more information to understand the structural features of bonding site of protein and the detail of proteinligand interactions for purposive directing the design of new potential molecules [10].…”

Section: Androgen Receptor In Prostate Cancermentioning

confidence: 99%

Human Androgen Receptor Inhibitors: Computational 3D QSAR Studies to Design Lead Compounds for Treatment of Prostate Cancer

Suresh¹

2013

Turk J Bioch

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CoMFA and docking studies of 2-phenylindole derivatives with anticancer activity

Cited by 42 publications

References 24 publications

QM/MM based 3D QSAR models for potent B-Raf inhibitors

QM/MM based 3D QSAR models for potent B-Raf inhibitors

Exploring structural requirements of unconventional Knoevenagel-type indole derivatives as anticancer agents through comparative QSAR modeling approaches

Human Androgen Receptor Inhibitors: Computational 3D QSAR Studies to Design Lead Compounds for Treatment of Prostate Cancer

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