Cocrystals of Praziquantel: Discovery by Network-Based Link Prediction

Devogelaer, Jan-Joris; Charpentier, Maxime D.; Tijink, Arnoud; Dupray, Valérie; Coquerel, G.; Johnston, Karen; Meekes, Hugo; Tinnemans, Paul; Vlieg, E.; Horst, Joop H. ter; Gelder, René de

doi:10.1021/acs.cgd.1c00211

Cited by 35 publications

(56 citation statements)

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“…Therefore, it is very important to improve the water solubility of praziquantel to reduce the dosage of praziquantel for better development of pediatric drug use and to reduce the probability of drug resistance and adverse reactions, as well as to protect global public health security [ 7 ].The solubility of praziquantel can be improved by preparing praziquantel solid dispersions, lipid nanoparticles or cyclodextrin inclusion compounds, but are limited by instability during preparation or storage. Considering the advantages of cocrystal technology in improving the physical and chemical properties of compounds, many researchers have carried out related studies on PRA [ 8 , 9 , 10 , 11 ]. At present, 27 cocrystals of PRA have been reported in the Cambridge Structural Database (CSD), and based on the analysis of their structural information, the cocrystal coformers (CCFs) of PRA were all carboxylic acid compounds or compounds with polyphenol hydroxyl groups.…”

Section: Introductionmentioning

confidence: 99%

Cocrystals of Praziquantel with Phenolic Acids: Discovery, Characterization, and Evaluation

Yang

Liu

et al. 2022

Molecules

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Solvent-assisted grinding (SAG) and solution slow evaporation (SSE) methods are generally used for the preparation of cocrystals. However, even by using the same solvent, active pharmaceutical ingredient (API), and cocrystal coformer (CCF), the cocrystals prepared using the two methods above are sometimes inconsistent. In the present study, in the cocrystal synthesis of praziquantel (PRA) with polyhydroxy phenolic acid, including protocatechuic acid (PA), gallic acid (GA), and ferulic acid (FA), five different cocrystals were prepared using SAG and SSE. Three of the cocrystals prepared using the SAG method have the structural characteristics of carboxylic acid dimer, and two cocrystals prepared using the SSE method formed cocrystal solvates with the structural characteristics of carboxylic acid monomer. For phenolic acids containing only one phenolic hydroxyl group (ferulic acid), when preparing cocrystals with PRA by using SAG and SSE, the same product was obtained. In addition, the weak molecular interactions that were observed in the cocrystal are explained at the molecular level by using theoretical calculation methods. Finally, the in vitro solubility of cocrystals without crystal solvents and in vivo bioavailability of PRA-FA were evaluated to further understand the influence on the physicochemical properties of API for the introduction of CCF.

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Section: Introductionmentioning

confidence: 99%

Cocrystals of Praziquantel with Phenolic Acids: Discovery, Characterization, and Evaluation

Yang

Liu

et al. 2022

Molecules

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“…17 The latest study predicted 30 CCFs (mostly benzoic acid compounds with similar structures) that can form cocrystals with PRA using the network-based link prediction method, and 12 cocrystals were obtained. 18 Twenty-three PRA cocrystals have been reported in the Cambridge Crystallographic Data Center database. However, only the flavonoid cocrystals of PRA and PRA−L-MA had been subjected to solubility experiments, in which PRA's solubility decreased whereas PRA−L-MA's solubility increased in pH 1.0 medium.…”

Section: ■ Introductionmentioning

confidence: 99%

“…In 2016, the R and S configurations of PRA were separated by forming a cocrystal between PRA and l -malic acid (PRA– l -MA) . The latest study predicted 30 CCFs (mostly benzoic acid compounds with similar structures) that can form cocrystals with PRA using the network-based link prediction method, and 12 cocrystals were obtained . Twenty-three PRA cocrystals have been reported in the Cambridge Crystallographic Data Center database.…”

Section: Introductionmentioning

confidence: 99%

Insights into the Solubility and Structural Features of Four Praziquantel Cocrystals

Liu

Yang

Chen

et al. 2021

Crystal Growth & Design

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Cocrystal technology can effectively improve the solubility and other physicochemical properties of compounds. The structural features of cocrystals are the key factors that affect the physicochemical properties. The present study aimed to investigate the solubility of the cocrystals formed between praziquantel and carboxylic acid compounds and understand the structural features of the cocrystals by exploring the intermolecular weak interactions between the components through theoretical computations. Four cocrystals were obtained, and their solubilities were all improved. The structures of the cocrystals were solved for the first time to reveal the structural features. Topology analysis based on the quantum theory of atoms in molecules and electron density difference analysis revealed the existence of classical and nonclassical hydrogen bonds. Energy decomposition analysis based on the symmetry-adapted perturbation theory was further applied to classify and quantify the interaction energy to better understand the composition of the interactions between the components. Notably, the tendency of the endothermic peak values of the cocrystals obtained from thermal analysis was consistent with the tendency of the physical component of maximum classical Coulomb interactions in the energy decomposition analysis and opposite to the tendency of the molecular weight of these cocrystals. In the end, the most promising one of the four cocrystals was selected as a candidate drug after taking into account safety and the improvement of the physicochemical properties.

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“…Various ML models have been applied for cocrystal prediction, including support vector machines (SVMs) [30], multivariate adaptive regression splines [31], random forest (RF) [32], and network-based link-prediction [33]. In our previous work, we developed a virtual screening model based on an artificial neural network (ANN) algorithm for cocrystal prediction [34].…”

Section: Introductionmentioning

confidence: 99%

Novel Cocrystals of Vonoprazan: Machine Learning-Assisted Discovery

Lee

Kim

et al. 2022

Pharmaceutics

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Vonoprazan (VPZ) is the first-in-class potassium-competitive acid blocker (P-CAB), and has many advantages over proton pump inhibitors (PPIs). It is administered as a fumarate salt for the treatment of acid-related diseases, including reflux esophagitis, gastric ulcer, and duodenal ulcer, and for eradication of Helicobacter pylori. To discover novel cocrystals of VPZ, we adopted an artificial neural network (ANN)-based machine learning model as a virtual screening tool that can guide selection of the most promising coformers for VPZ cocrystals. Experimental screening by liquid-assisted grinding (LAG) confirmed that 8 of 19 coformers selected by the ANN model were likely to create new solid forms with VPZ. Structurally similar benzenediols and benzenetriols, i.e., catechol (CAT), resorcinol (RES), hydroquinone (HYQ), and pyrogallol (GAL), were used as coformers to obtain phase pure cocrystals with VPZ by reaction crystallization. We successfully prepared and characterized three novel cocrystals: VPZ–RES, VPZ–CAT, and VPZ–GAL. VPZ–RES had the highest solubility among the novel cocrystals studied here, and was even more soluble than the commercially available fumarate salt of VPZ in solution at pH 6.8. In addition, novel VPZ cocrystals had superior stability in aqueous media than VPZ fumarates, demonstrating their potential for improved pharmaceutical performance.

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Cocrystals of Praziquantel: Discovery by Network-Based Link Prediction

Cited by 35 publications

References 50 publications

Cocrystals of Praziquantel with Phenolic Acids: Discovery, Characterization, and Evaluation

Cocrystals of Praziquantel with Phenolic Acids: Discovery, Characterization, and Evaluation

Insights into the Solubility and Structural Features of Four Praziquantel Cocrystals

Novel Cocrystals of Vonoprazan: Machine Learning-Assisted Discovery

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