Nucleoside‐Based Self‐Assembling Drugs for Localized Drug Delivery

Skilling, Katherine J; Stocks, Michael J.; Kellam, Barrie; Bradshaw, Tracey D.; Burroughs, Laurence; Marlow, Maria

doi:10.1002/cmdc.201800063

Cited by 5 publications

(4 citation statements)

References 34 publications

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“…N4-myristoyl gemcitabine (GEM C14) and low molecular weight gelator: N4octanoyl-2ʹ-deoxycytidine were synthesised as previously reported (KJ. Skilling et al, 2018;K.J. Skilling et al, 2016).…”

Section: Methodsmentioning

confidence: 99%

A novel low molecular weight nanocomposite hydrogel formulation for intra-tumoural delivery of anti-cancer drugs

Štaka

Cadete

Surikutchi

et al. 2019

International Journal of Pharmaceutics

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Herein, an injectable formulation composed of a low molecular weight gelator (LMWG) based hydrogel and drug-loaded polymeric nanocapsules (NCs) is described. The NCs, made of hyaluronic acid and polyglutamic acid and loaded with C14-Gemcitabine (GEM C14), showed a size of 40 and 80 nm and a encapsulation efficiency > 90%. These NCs exhibited a capacity to control the release of the encapsulated drug for more than 1 month. GEM C14-loaded NCs showed activity against various cancer cell lines in vitro; cell growth inhibition by 50% (GI50) values of 15 ± 6, 10 ± 9, 13 ± 3 and 410 ± 463 nM were obtained in HCT 116, MIA PaCa-2, Panc-1 and Panc-1 GEM resistant cell lines respectively. Nanocomposite hydrogels were prepared using the LMWG -N4-octanoyl-2ʹ-deoxycytidine and loaded for the first time with polymeric NCs. 2% and 4% w/v nanocapsule concentrations as compared to 8% w/v NC concentrations with 2 % and 3% w/v gelator concentrations gave mechanically stronger gels as determined by oscillatory rheology. Most importantly, the nanocomposite formulation reformed instantly into a gel after injection through a needle. Based on these properties, the nanocomposite gel formulation has potential for the intratumoural delivery of anticancer drugs. 1 Abbreviations: low molecular weight gelator (LMWG); nanocapsules (NCs); N4-myristoyl gemcitabine (GEM C14); low molecular weight (LMW); hexadecyltrimethylammonium bromide (CTAB); Sodium hyaluronate (HA); poly-L-glutamic acid (PGA); GEM hydrochloride (GEM-HCl); 9-Diethylamino-5Hbenzo[a]phenoxazine-5-one -Nile Red (NR); Linear visco-elastic (LVE) region; GEM resistant cell line

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Section: Methodsmentioning

confidence: 99%

A novel low molecular weight nanocomposite hydrogel formulation for intra-tumoural delivery of anti-cancer drugs

Štaka

Cadete

Surikutchi

et al. 2019

International Journal of Pharmaceutics

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“…An optimal ML model was constructed for nucleoside derivatives to predict the hydrogel-forming ability All the published nucleoside derivatives and the information on whether they have the hydrogel-forming ability were collected by systematic literature review, and 71 molecules were included in the dataset (gelator, n = 38, and non-gelator, n = 33, Supplementary Data 1, Supplementary Data 2) 5,[20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36] . As only a few dozen have clarified hydrogel-forming ability, more nucleoside hydrogels are urgently needed to discover.…”

Section: Resultsmentioning

confidence: 99%

Developing a machine learning model for accurate nucleoside hydrogels prediction based on descriptors

Li,

Wen,

Wang

et al. 2024

Nat Commun

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Supramolecular hydrogels derived from nucleosides have been gaining significant attention in the biomedical field due to their unique properties and excellent biocompatibility. However, a major challenge in this field is that there is no model for predicting whether nucleoside derivative will form a hydrogel. Here, we successfully develop a machine learning model to predict the hydrogel-forming ability of nucleoside derivatives. The optimal model with a 71% (95% Confidence Interval, 0.69−0.73) accuracy is established based on a dataset of 71 reported nucleoside derivatives. 24 molecules are selected via the optimal model external application and the hydrogel-forming ability is experimentally verified. Among these, two rarely reported cation-independent nucleoside hydrogels are found. Based on their self-assemble mechanisms, the cation-independent hydrogel is found to have potential applications in rapid visual detection of Ag+ and cysteine. Here, we show the machine learning model may provide a tool to predict nucleoside derivatives with hydrogel-forming ability.

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“…As a cross-discipline between supramolecular chemistry and materials chemistry, the structural study of supramolecular self-assembly can help to enhance the understanding of the microstructure of molecular materials [ 4 , 5 , 6 ]. In the process of chemical development, molecular self-assembly nanomaterials have attracted more and more attention due to their wide applications in sensing, separation [ 7 , 8 ], catalysis [ 9 , 10 ], biomedicine [ 11 , 12 , 13 ], pharmacology [ 14 , 15 , 16 ] and other fields.…”

Section: Introductionmentioning

confidence: 99%

Self-Assembled Nanotubes Based on Chiral H8-BINOL Modified with 1,2,3-Triazole to Recognize Bi3+ Efficiently by ICT Mechanism

Tao,

Guo,

Sun

et al. 2024

Micromachines

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A novel fluorescent “off” probe R-β-D-1 containing a 1,2,3-triazole moiety was obtained by the Click reaction with azidoglucose using H8-BINOL as a substrate, and the structure was characterized by 1H NMR and 13C NMR and ESI-MS analysis. The fluorescence properties of R-β-D-1 in methanol were investigated, and it was found that R-β-D-1 could be selectively fluorescently quenched by Bi3+ in the recognition of 19 metal ions and basic cations. The recognition process of Bi3+ by R-β-D-1 was also investigated by fluorescence spectroscopy, SEM, AFM, etc. The complex pattern of R-β-D-1 with Bi3+ was determined by Job’s curve as 1 + 1, and the binding constant Ka of R-β-D-1 and Bi3+ was valued by the Benesi–Hildebrand equation as 1.01 × 104 M−1, indicating that the binding force of R-β-D-1 and Bi3+ was medium. The lowest detection limit (LOD) of the self-assembled H8-BINOL derivative for Bi3+ was up to 0.065 µM. The mechanism for the recognition of Bi3+ by the sensor R-β-D-1 may be the intramolecular charge transfer effect (ICT), which was attributed to the fact that the N-3 of the triazole readily serves as an electron acceptor while the incorporation of Bi3+ serves as an electron donor, and the two readily undergo coordination leading to the quenching of fluorescence. The recognition mechanism and recognition site could be verified by DFT calculation and CDD (Charge Density Difference).

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Nucleoside‐Based Self‐Assembling Drugs for Localized Drug Delivery

Cited by 5 publications

References 34 publications

A novel low molecular weight nanocomposite hydrogel formulation for intra-tumoural delivery of anti-cancer drugs

A novel low molecular weight nanocomposite hydrogel formulation for intra-tumoural delivery of anti-cancer drugs

Developing a machine learning model for accurate nucleoside hydrogels prediction based on descriptors

Self-Assembled Nanotubes Based on Chiral H8-BINOL Modified with 1,2,3-Triazole to Recognize Bi3+ Efficiently by ICT Mechanism

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