Synthesis and biological evaluation of arylpiperazine derivatives as potential anti-prostate cancer agents

Tian, Xiumei; Wang, Cailu; Qian, Yuna; Deng, Zhaoze; Zhang, Jingxiao; Lv, Daojun; Zhang, Haibo; Shen, Jianliang; Yuan, Ming; Zhao, Shan‐Chao

doi:10.1016/j.bmc.2018.11.029

Cited by 11 publications

(17 citation statements)

References 52 publications

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“…Arjun et al (2019) reported some Benzohydrazine derivatives to bind via hydrophobic interactions. Anti-prostate compounds have been reported to bind with ARG (arginine), ASN (Asparagine), PHE (Phenylalanine), LYS (Lysine), VAL (Valine), ILE (Isoleucine), LEU (Leucine) protein residues of the androgen receptor (McNerney and Onate, 2015;Chen et al, 2018a;Arjun et al, 2019). The binding affinity of compounds 5 and 17 were within the range reported Arjun et al (2019).…”

Section: Dockingmentioning

confidence: 87%

“…Twenty nine (29) arylpiperazine derivatives were used in this study. Their structures and activities were obtained from literature (Chen et al, 2018a(Chen et al, , 2018b. Their activities were reported in IC 50 (μM).…”

Section: Datasetmentioning

confidence: 99%

“…Results obtained revealed that both compounds mainly bind to AR (5t8e) via hydrogen and hydrophobic bond interactions. Chen et al (2018a) reported some aryl piperazine derivatives to bind to the Ligand Binding Pocket (LBP) of AR through hydrogen bond interaction. Arjun et al (2019) reported some Benzohydrazine derivatives to bind via hydrophobic interactions.…”

Section: Dockingmentioning

confidence: 99%

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In silico studies of piperazine derivatives as potent anti-proliferative agents against PC-3 prostate cancer cell lines

Ikwu

Shallangwa

Mamza

et al. 2020

Heliyon

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Quantitative Structure Activity Relationship studies were carried out on arylpiperazine derivatives to investigate their anti-proliferate activity against prostate PC-3 cancer cell lines. The built model with statistical parameters; R 2 ¼ 0.8483, R 2 adj ¼ 0.8078, Q 2 cv ¼ 0.7122 and external validation (R 2 test) 0.6682 revealed that the antiproliferate activities were strongly dependent on the descriptors: MATS7c, MATS3e, maxwHBa and WPSA-3. The Variance Inflation Factor of the descriptors were all greater than one but less than two and all descriptors were poorly correlated (r < 0.4). A graph of the experimental activities and predicted activities showed a high correlation and a William's plot showed the presence of only one outlier compound. These results are similar to those reported for stable and robust models with high predicting power. Molecular docking studies of compounds 5 (1-phenyl-4-(4-(2-(p-tolyloxy)ethyl)benzyl)piperazine) and 17 (4-(4-((4-phenylpiperazin-1-yl)methyl)phenethoxy)benzonitrile) with the androgen receptor gave binding affinities of À7.5 and À7.1 kcal/mol respectively. Compound 5 formed a more stable complex having hydrogen, electrostatic and hydrophobic bond interactions while compound 17 had hydrogen and hydrophobic bond interactions only. This study provides a roadmap to the design of more potent anti-prostate cancer compounds.

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Section: Dockingmentioning

confidence: 87%

Section: Datasetmentioning

confidence: 99%

Section: Dockingmentioning

confidence: 99%

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In silico studies of piperazine derivatives as potent anti-proliferative agents against PC-3 prostate cancer cell lines

Ikwu

Shallangwa

Mamza

et al. 2020

Heliyon

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“…Thirty-seven (37) phenylpiperazine derivatives reported by Chen et al, [12,13] were employed in building a QSAR model that predicts their anti-proliferate activity against DU145 prostate cancer cell lines. Thirty (30) other derivatives having toxic (proliferative) activity against normal prostate epithelial cells were employed in building the QSTR model [12][13][14]. Figure 1 presents 2D structures of the compounds used to build the QSAR model while Fig.…”

Section: Datasetmentioning

confidence: 99%

QSAR, QSTR, and molecular docking studies of the anti-proliferative activity of phenylpiperazine derivatives against DU145 prostate cancer cell lines

Ikwu

Shallangwa

Mamza

2020

Beni-Suef Univ J Basic Appl Sci

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Background: Prostate cancer is the most common non-cutaneous cancer in males and accounts for about 4% of all cancer-related deaths in males annually. In silico methods provide faster, economical, and environmentally friendly alternatives to the traditional trial and error method of lead identification and optimization. This study, therefore, was aimed at building a robust QSAR and QSTR model to predict the anti-proliferate activity and toxicity of some phenylpiperazine compounds against the DU145 prostate cancer cell lines and normal prostate epithelial cells as well as carry out molecular docking studies between the compounds and the androgen receptor. Results: Genetic Function Algorithm-Multilinear Regression approach was employed in building the QSAR and QSTR model. The QSAR model built had statistical parameters R 2 = 0.7792, R 2 adj. = 0.7240, Q 2 cv = 0.6607, and R 2 ext = 0.6049 and revealed the anti-proliferate activity to be strongly dependent on the molecular descriptors: VR3_Dzp, VE3_Dzi, Kier3, RHSA, and RDF55v. The QSTR model, on the other hand, had statistical parameters R 2 = 0.8652, R 2 adj. = 0.8315, Q 2 cv = 0.7788, and R 2 ext = 0.6344. The toxicity of the compounds was observed to be dependent on the descriptors MATS8c, MATS3s, ETA_EtaP_F, and RDF95m. The molecular descriptors in both models were poorly correlated (R < 0.4) and had variance inflation factors < 3. Molecular docking studies between the androgen receptor and compounds 25 and 32 revealed the compounds primarily formed hydrogen, halogen, and hydrophobic interactions with the receptor. Conclusion: Findings from this study can be employed in in silico design of novel phenylpiperazine compounds. It can also be employed in predicting the toxicity and anti-proliferate activity of other phenylpiperazine compounds against DU145 prostate cancer cell lines.

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“…Some of these compounds have good receptor-blocking properties [13]. According to experiments of the testprostate cancer cells, arylpiperazine derivatives have displayed significant cytotoxic [14]. Although some crystal structures of arylpiperazine derivatives have been reported recently [15,16], the different functional groups and organic ligands would lead to different properties.…”

Section: Commentmentioning

confidence: 99%

Crystal structure of 1-(3-chlorophenyl)-4-(4-(((2,3-dihydro-1H-inden-5-yl)oxy)methyl)phenethyl)piperazine, C₂₈H₃₁ClN₂O

Feng

2020

Zeitschrift Für Kristallographie - New Crystal Structures

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Synthesis and biological evaluation of arylpiperazine derivatives as potential anti-prostate cancer agents

Cited by 11 publications

References 52 publications

In silico studies of piperazine derivatives as potent anti-proliferative agents against PC-3 prostate cancer cell lines

In silico studies of piperazine derivatives as potent anti-proliferative agents against PC-3 prostate cancer cell lines

QSAR, QSTR, and molecular docking studies of the anti-proliferative activity of phenylpiperazine derivatives against DU145 prostate cancer cell lines

Crystal structure of 1-(3-chlorophenyl)-4-(4-(((2,3-dihydro-1H-inden-5-yl)oxy)methyl)phenethyl)piperazine, C₂₈H₃₁ClN₂O

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Synthesis and biological evaluation of arylpiperazine derivatives as potential anti-prostate cancer agents

Cited by 11 publications

References 52 publications

In silico studies of piperazine derivatives as potent anti-proliferative agents against PC-3 prostate cancer cell lines

In silico studies of piperazine derivatives as potent anti-proliferative agents against PC-3 prostate cancer cell lines

QSAR, QSTR, and molecular docking studies of the anti-proliferative activity of phenylpiperazine derivatives against DU145 prostate cancer cell lines

Crystal structure of 1-(3-chlorophenyl)-4-(4-(((2,3-dihydro-1H-inden-5-yl)oxy)methyl)phenethyl)piperazine, C28H31ClN2O

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Crystal structure of 1-(3-chlorophenyl)-4-(4-(((2,3-dihydro-1H-inden-5-yl)oxy)methyl)phenethyl)piperazine, C₂₈H₃₁ClN₂O