Identification of potential tubulin polymerization inhibitors by 3D-QSAR, molecular docking and molecular dynamics

Wang, Tian Chi; Li, Cheng; Huang, Xin; Zhao, Lei; Pang, Wan

doi:10.1039/c7ra04314g

Cited by 13 publications

(8 citation statements)

References 42 publications

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“…The inhibitory activities of flavonoids toward DPP-IV were expressed in terms of the negative logarithm of IC 50 (−log IC 50 , pIC 50 ) and used as dependent variables in 3D-QSAR analysis . Twenty-five compounds were chosen as a training set according to their structures and DPP-IV inhibitory IC 50 values and used to build 3D-QSAR models . The remaining compounds were applied in the test set.…”

Section: Materials and Methodsmentioning

confidence: 99%

“…20 Twenty-five compounds were chosen as a training set according to their structures and DPP-IV inhibitory IC 50 values and used to build 3D-QSAR models. 21 The remaining compounds were applied in the test set. All the 3D structures of flavonoids were constructed with ChemBioDraw Ultra 12.0 and then minimized by the SYBYL-X 2.1.1 software with Gasteiger−Huckel charge.…”

Section: Dpp-iv Inhibition Assaymentioning

confidence: 99%

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Effects of Different Dietary Flavonoids on Dipeptidyl Peptidase-IV Activity and Expression: Insights into Structure–Activity Relationship

Gao

et al. 2020

J. Agric. Food Chem.

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The inhibitory effects of 30 dietary flavonoids on dipeptidyl peptidase-IV (DPP-IV) were investigated to illustrate their quantitative structure−activity relationship (QSAR) and further explore their inhibition at the cellular level. Results of in vitro experiment show that isorhamnetin-3-O-glucoside (IC 50 , 6.53 ± 0.280 μM) had the strongest inhibition followed by cyanidin-3-Oglucoside (IC 50 , 8.26 ± 0.143 μM) and isorhamnetin-3-O-rutinoside (IC 50 , 8.57 ± 0.422 μM). A 3D QSAR model [comparative molecular field analysis, q 2 = 0.502, optimum number of components (ONC) = 3, R 2 = 0.983, F = 404.378, standard error of estimation (SEE) = 0.070, and two descriptors; comparative similarity index analysis, q 2 = 0.580, ONC = 10, R 2 = 0.999, F = 1617.594, SEE = 0.022, and four descriptors] indicates that the DPP-IV inhibition of flavonoid was facilitated by crucial structural factors. Position 3 of ring C favored bulky, hydrogen bond acceptors and hydrophilic and electron-donating substituents. The presence of minor and electron-withdrawing groups at position 4′ of ring B and positions 5 and 7 of ring A could improve DPP-IV inhibition. Moreover, the three flavonoids mentioned above could effectively suppress DPP-IV activity and expression in Caco-2 cells. This work may supply new insights into dietary flavonoids as DPP-IV inhibitors for controlling blood glucose.

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Section: Materials and Methodsmentioning

confidence: 99%

Section: Dpp-iv Inhibition Assaymentioning

confidence: 99%

Effects of Different Dietary Flavonoids on Dipeptidyl Peptidase-IV Activity and Expression: Insights into Structure–Activity Relationship

Gao

et al. 2020

J. Agric. Food Chem.

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“…71 Further to this, CA-4 is reported as one of the most potent tubulin polymerisation inhibitors with IC50 values reported to range from 0.53 to 2.4 M. [71][72][73][74] The inhibition of tubulin polymerisation correlated with the cytotoxicity towards cancer cell lines suggesting the main mode of action of these combretastatin derivatives is the inhibition of tubulin polymerisation. [73][74][75][76]…”

Section: Effect On Microtubulesmentioning

confidence: 86%

A 2-step synthesis of Combretastatin A-4 and derivatives as potent tubulin assembly inhibitors

Barnes

Parker

Ullah

et al. 2020

Bioorganic & Medicinal Chemistry

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A series of combretastatin derivatives were designed and synthesised by a two-step stereoselective synthesis by use of Wittig olefination followed by Suzuki cross-coupling. Interestingly, all new compounds (2a-2i) showed potent cell-based antiproliferative activities in nanomolar concentrations. Among the compounds, 2a, 2b and 2e were the most active across three cancer cell lines. In addition, these compounds inhibited the polymerisation of tubulin in vitro more efficiently than CA-4. They caused cell cycle arrest in G2/M phase further confirming their ability to inhibit tubulin polymerisation.

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“…For 3D‐QSAR studies, a data set of compounds with activities spanning five log units was selected from literature (Auzzas et al., ; Chen et al., ; Dallavalle et al., ; Gupta et al., ; Inks, Josey, Jesinkey, & Chou, ; Itoh et al., ; Jones et al., ; Kalin, Butler, Akimova, Hancock, & Kozikowski, ; Kozikowski, Tapadar, Luchini, Kim, & Billadeau, ; Kozikowski et al., ; Olsen & Ghadiri, ; Ontoria et al., ; Scarpelli et al., ; Smil et al., ). The HDAC6 inhibitory activities of the compounds were transformed into the corresponding pIC 50 (−log IC 50 ) values (Verma & Thareja, ; Wang, Cheng, Huang, Zhao, & Pang, ), which were then depicted as dependent variables in the CoMFA and CoMSIA analyses. Then, all the 54 inhibitors were distributed into training set and test set and categorized according to their pIC 50 values (Figure ; Supporting Information Figure S1).…”

Section: Methodsmentioning

confidence: 99%

Combined comparative molecular field analysis, comparative molecular similarity indices analysis, molecular docking and molecular dynamics studies of histone deacetylase 6 inhibitors

et al. 2019

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Human histone deacetylase isoform 6 (HDAC6) has been shown to have an immense role in cell motility and aggresome formation and is being an attractive selective target for the treatment of multiple tumour types and neurodegenerative conditions. The discovery of selective HDAC6 inhibitors with new chemical functionalities is therefore of utmost interest to researchers. In order to examine the structural requirements for HDAC6‐specific inhibitors and to derive predictive model which can be used for designing new selective HDAC6 inhibitors, a three‐dimensional quantitative structure–activity relationship study was carried out on a diverse set of ligands using common feature‐based pharmacophore alignment followed by employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The models displayed high correlation of 0.978 and 0.991 for best CoMFA and CoMSIA models, respectively, and a good statistical significance. The model could be used for predicting activities of the test set compounds as well as for deriving useful information regarding steric, electrostatic, hydrophobic properties of the molecules used in this study. Further, the training and test set molecules were docked into the HDAC6 binding site and molecular dynamics was carried out to suggest structural requirements for design of new inhibitors.

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Identification of potential tubulin polymerization inhibitors by 3D-QSAR, molecular docking and molecular dynamics

Abstract: View of the correlation between experimental and predicted pIC50c values, and the compound 22c docked into the binding site of 3UT5.

Cited by 13 publications

References 42 publications

Effects of Different Dietary Flavonoids on Dipeptidyl Peptidase-IV Activity and Expression: Insights into Structure–Activity Relationship

Effects of Different Dietary Flavonoids on Dipeptidyl Peptidase-IV Activity and Expression: Insights into Structure–Activity Relationship

A 2-step synthesis of Combretastatin A-4 and derivatives as potent tubulin assembly inhibitors

Combined comparative molecular field analysis, comparative molecular similarity indices analysis, molecular docking and molecular dynamics studies of histone deacetylase 6 inhibitors

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