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1.
Botanical, Phytochemical, Anti-Microbial and Pharmaceutical Characteristics of Hawthorn (Crataegusmonogyna Jacq.), Rosaceae.
Martinelli, F, Perrone, A, Yousefi, S, Papini, A, Castiglione, S, Guarino, F, Cicatelli, A, Aelaei, M, Arad, N, Gholami, M, et al
Molecules (Basel, Switzerland). 2021;(23)
Abstract
Hawthorn (Crataegus monogyna Jacq.) is a wild edible fruit tree of the genus Crataegus, one of the most interesting genera of the Rosaceae family. This review is the first to consider, all together, the pharmaceutical, phytochemical, functional and therapeutic properties of C. monogyna based on numerous valuable secondary metabolites, including flavonoids, vitamin C, glycoside, anthocyanin, saponin, tannin and antioxidants. Previous reviews dealt with the properties of all species of the entire genera. We highlight the multi-therapeutic role that C. monogyna extracts could have in the treatment of different chronic and degenerative diseases, mainly focusing on flavonoids. In the first part of this comprehensive review, we describe the main botanical characteristics and summarize the studies which have been performed on the morphological and genetic characterization of the C. monogyna germplasm. In the second part, the key metabolites and their nutritional and pharmaceutical properties are described. This work could be an essential resource for promoting future therapeutic formulations based on this natural and potent bioactive plant extract.
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2.
An easy-to-use and general nuclear magnetic resonance method for the determination of partition coefficients of drugs and natural products.
Barthel, C, Massiot, G, Lavaud, C
Magnetic resonance in chemistry : MRC. 2021;(8):835-843
Abstract
The lipophilicity of a drug is an important parameter for its eventual development by the pharmaceutical industry. It is usually measured by HPLC following partition of the compound between water and 1-octanol. We present here an alternative, simple, sensitive and quantitative 1 H nuclear magnetic resonance (NMR) method for the experimental measurement of partition coefficients of natural compounds and pharmaceutical drugs. It is based on measuring concentrations in the water phase, before and after partitioning and equilibration between water and octanol, using the ERETIC (Electronic Reference To Access In Vivo Concentration) technique. The signal to noise ratio is improved by a Water Suppression by Excitation Sculpting sequence. Quantification is based on an electronic reference signal and does not need addition of a reference compound. The log P values of 22 natural metabolites and four pharmaceutical drugs were determined and the experimental results are in excellent agreement with literature data. The experiments were run on ~2 mg material. This technique proved to be robust, reproducible and suitable for log P values between -2 and +2.
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Prediction of hepatic drug clearance with a human microfluidic four-cell liver acinus microphysiology system.
Sakolish, C, Luo, YS, Valdiviezo, A, Vernetti, LA, Rusyn, I, Chiu, WA
Toxicology. 2021;:152954
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Abstract
Predicting human hepatic clearance remains a fundamental challenge in both pharmaceutical drug development and toxicological assessments of environmental chemicals, with concerns about both accuracy and precision of in vitro-derived estimates. Suggested sources of these issues have included differences in experimental protocols, differences in cell sourcing, and use of a single cell type, liver parenchymal cells (hepatocytes). Here we investigate the ability of human microfluidic four-cell liver acinus microphysiology system (LAMPS) to make predictions as to hepatic clearance for seven representative compounds: Caffeine, Pioglitazone, Rosiglitazone, Terfenadine, Tolcapone, Troglitazone, and Trovafloxacin. The model, whose reproducibility was recently confirmed in an inter-lab comparison, was constructed using primary human hepatocytes or human induced pluripotent stem cell (iPSC)-derived hepatocytes and 3 human cell lines for the endothelial, Kupffer and stellate cells. We calculated hepatic clearance estimates derived from experiments using LAMPS or traditional 2D cultures and compared the outcomes with both in vivo human clinical study-derived and in vitro human hepatocyte suspension culture-derived values reported in the literature. We found that, compared to in vivo clinically-derived values, the LAMPS model with iPSC-derived hepatocytes had higher precision as compared to primary cells in suspension or 2D culture, but, consistent with previous studies in other microphysiological systems, tended to underestimate in vivo clearance. Overall, these results suggest that use of LAMPS and iPSC-derived hepatocytes together with an empirical scaling factor warrants additional study with a larger set of compounds, as it has the potential to provide more accurate and precise estimates of hepatic clearance.
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Bell Peppers (Capsicum annum L.) Losses and Wastes: Source for Food and Pharmaceutical Applications.
Anaya-Esparza, LM, Mora, ZV, Vázquez-Paulino, O, Ascencio, F, Villarruel-López, A
Molecules (Basel, Switzerland). 2021;(17)
Abstract
Currently, the high added-value compounds contained in plant by-products and wastes offer a wide spectrum of opportunities for their reuse and valorization, contributing to the circular economy. The bell pepper (Capsicum annum L.) is an exotic vegetable with high nutritional value that, after processing, leaves wastes (peel, seeds, and leaves) that represent desirable raw material for obtaining phytochemical compounds. This review summarizes and discusses the relevant information on the phytochemical profile of bell peppers and their related biological properties as an alternative to revalorize losses and wastes from bell peppers for their application in the food and pharmaceutical industries. Bell pepper fruits, seeds, and leaves contain bioactive compounds (phenols, flavonoids, carotenoids, tocopherol, and pectic polysaccharides) that exhibit antioxidant, antibacterial, antifungal, immunosuppressive and immunostimulant properties, and antidiabetic, antitumoral and neuroprotective activities, and have a potential use as functional food additives. In this context, the revalorization of food waste is positioned as a technological and innovative research area with beneficial effects for the population, the economy, and the environment. Further studies are required to guarantee the safety use of these compounds and to understand their mechanisms of action.
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5.
EmbedDTI: Enhancing the Molecular Representations via Sequence Embedding and Graph Convolutional Network for the Prediction of Drug-Target Interaction.
Jin, Y, Lu, J, Shi, R, Yang, Y
Biomolecules. 2021;(12)
Abstract
The identification of drug-target interaction (DTI) plays a key role in drug discovery and development. Benefitting from large-scale drug databases and verified DTI relationships, a lot of machine-learning methods have been developed to predict DTIs. However, due to the difficulty in extracting useful information from molecules, the performance of these methods is limited by the representation of drugs and target proteins. This study proposes a new model called EmbedDTI to enhance the representation of both drugs and target proteins, and improve the performance of DTI prediction. For protein sequences, we leverage language modeling for pretraining the feature embeddings of amino acids and feed them to a convolutional neural network model for further representation learning. For drugs, we build two levels of graphs to represent compound structural information, namely the atom graph and substructure graph, and adopt graph convolutional network with an attention module to learn the embedding vectors for the graphs. We compare EmbedDTI with the existing DTI predictors on two benchmark datasets. The experimental results show that EmbedDTI outperforms the state-of-the-art models, and the attention module can identify the components crucial for DTIs in compounds.
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The Transporter-Mediated Cellular Uptake and Efflux of Pharmaceutical Drugs and Biotechnology Products: How and Why Phospholipid Bilayer Transport Is Negligible in Real Biomembranes.
Kell, DB
Molecules (Basel, Switzerland). 2021;(18)
Abstract
Over the years, my colleagues and I have come to realise that the likelihood of pharmaceutical drugs being able to diffuse through whatever unhindered phospholipid bilayer may exist in intact biological membranes in vivo is vanishingly low. This is because (i) most real biomembranes are mostly protein, not lipid, (ii) unlike purely lipid bilayers that can form transient aqueous channels, the high concentrations of proteins serve to stop such activity, (iii) natural evolution long ago selected against transport methods that just let any undesirable products enter a cell, (iv) transporters have now been identified for all kinds of molecules (even water) that were once thought not to require them, (v) many experiments show a massive variation in the uptake of drugs between different cells, tissues, and organisms, that cannot be explained if lipid bilayer transport is significant or if efflux were the only differentiator, and (vi) many experiments that manipulate the expression level of individual transporters as an independent variable demonstrate their role in drug and nutrient uptake (including in cytotoxicity or adverse drug reactions). This makes such transporters valuable both as a means of targeting drugs (not least anti-infectives) to selected cells or tissues and also as drug targets. The same considerations apply to the exploitation of substrate uptake and product efflux transporters in biotechnology. We are also beginning to recognise that transporters are more promiscuous, and antiporter activity is much more widespread, than had been realised, and that such processes are adaptive (i.e., were selected by natural evolution). The purpose of the present review is to summarise the above, and to rehearse and update readers on recent developments. These developments lead us to retain and indeed to strengthen our contention that for transmembrane pharmaceutical drug transport "phospholipid bilayer transport is negligible".
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7.
Water molecules at protein-drug interfaces: computational prediction and analysis methods.
Samways, ML, Taylor, RD, Bruce Macdonald, HE, Essex, JW
Chemical Society reviews. 2021;(16):9104-9120
Abstract
The fundamental importance of water molecules at drug-protein interfaces is now widely recognised and a significant feature in structure-based drug design. Experimental methods for analysing the role of water in drug binding have many challenges, including the accurate location of bound water molecules in crystal structures, and problems in resolving specific water contributions to binding thermodynamics. Computational analyses of binding site water molecules provide an alternative, and in principle complete, structural and thermodynamic picture, and their use is now commonplace in the pharmaceutical industry. In this review, we describe the computational methodologies that are available and discuss their strengths and weaknesses. Additionally, we provide a critical analysis of the experimental data used to validate the methods, regarding the type and quality of experimental structural data. We also discuss some of the fundamental difficulties of each method and suggest directions for future study.
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8.
Hepatic drug-metabolizing enzymes and drug transporters in Wilson's disease patients with liver failure.
Szeląg-Pieniek, S, Oswald, S, Post, M, Łapczuk-Romańska, J, Droździk, M, Kurzawski, M
Pharmacological reports : PR. 2021;(5):1427-1438
Abstract
BACKGROUND Wilson's disease is a genetic disorder inherited in a recessive manner, caused by mutations in the copper-transporter ATP7B. Although it is a well-known disease, currently available treatments are far from satisfactory and their efficacy varies in individual patients. Due to the lack of information about drug-metabolizing enzymes and drug transporters profile in Wilson's disease livers, we aimed to evaluate the mRNA expression and protein abundance of selected enzymes and drug transporters in this liver disorder. METHODS We analyzed gene expression (qPCR) and protein abundance (LC-MS/MS) of 14 drug-metabolizing enzymes and 16 drug transporters in hepatic tissue from Wilson's disease patients with liver failure (n = 7, Child-Pugh class B and C) and metastatic control livers (n = 20). RESULTS In presented work, we demonstrated a downregulation of majority of CYP450 and UGT enzymes. Gene expression of analyzed enzymes ranged between 18 and 65% compared to control group and significantly lower protein content of CYP1A1, CYP1A2, CYP2C8, CYP2C9, CYP3A4 and CYP3A5 enzymes was observed in Wilson's disease. Moreover, a general decrease in hepatocellular uptake carriers from SLC superfamily (significant at protein level for NTCP and OATP2B1) was observed. As for ABC transporters, the protein abundance of BSEP and MRP2 was significantly lower, while levels of P-gp and MRP4 transporters were significantly higher in Wilson's disease. CONCLUSIONS Altered hepatic expression of drug-metabolizing enzymes and drug transporters in Wilson's disease patients with liver failure may result in changes of drug pharmacokinetics in that group of patients.
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9.
PreDTIs: prediction of drug-target interactions based on multiple feature information using gradient boosting framework with data balancing and feature selection techniques.
Mahmud, SMH, Chen, W, Liu, Y, Awal, MA, Ahmed, K, Rahman, MH, Moni, MA
Briefings in bioinformatics. 2021;(5)
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Abstract
Discovering drug-target (protein) interactions (DTIs) is of great significance for researching and developing novel drugs, having a tremendous advantage to pharmaceutical industries and patients. However, the prediction of DTIs using wet-lab experimental methods is generally expensive and time-consuming. Therefore, different machine learning-based methods have been developed for this purpose, but there are still substantial unknown interactions needed to discover. Furthermore, data imbalance and feature dimensionality problems are a critical challenge in drug-target datasets, which can decrease the classifier performances that have not been significantly addressed yet. This paper proposed a novel drug-target interaction prediction method called PreDTIs. First, the feature vectors of the protein sequence are extracted by the pseudo-position-specific scoring matrix (PsePSSM), dipeptide composition (DC) and pseudo amino acid composition (PseAAC); and the drug is encoded with MACCS substructure fingerings. Besides, we propose a FastUS algorithm to handle the class imbalance problem and also develop a MoIFS algorithm to remove the irrelevant and redundant features for getting the best optimal features. Finally, balanced and optimal features are provided to the LightGBM Classifier to identify DTIs, and the 5-fold CV validation test method was applied to evaluate the prediction ability of the proposed method. Prediction results indicate that the proposed model PreDTIs is significantly superior to other existing methods in predicting DTIs, and our model could be used to discover new drugs for unknown disorders or infections, such as for the coronavirus disease 2019 using existing drugs compounds and severe acute respiratory syndrome coronavirus 2 protein sequences.
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10.
Chemical Approaches for Studying the Biology and Pharmacology of Membrane Transporters: The Histidine/Large Amino Acid Transporter SLC7A5 as a Benchmark.
Scalise, M, Scanga, R, Console, L, Galluccio, M, Pochini, L, Indiveri, C
Molecules (Basel, Switzerland). 2021;(21)
Abstract
The localization of membrane transporters at the forefront of natural barriers makes these proteins very interesting due to their involvement in the absorption and distribution of nutrients and xenobiotics, including drugs. Over the years, structure/function relationship studies have been performed employing several strategies, including chemical modification of exposed amino acid residues. These approaches are very meaningful when applied to membrane transporters, given that these proteins are characterized by both hydrophobic and hydrophilic domains with a different degree of accessibility to employed chemicals. Besides basic features, the chemical targeting approaches can disclose information useful for pharmacological applications as well. An eminent example of this picture is the histidine/large amino acid transporter SLC7A5, known as LAT1 (Large Amino Acid Transporter 1). This protein is crucial in cell life because it is responsible for mediating the absorption and distribution of essential amino acids in peculiar body districts, such as the blood brain barrier and placenta. Furthermore, LAT1 can recognize a large variety of molecules of pharmacological interest and is also considered a hot target for drugs due to its over-expression in virtually all human cancers. Therefore, it is not surprising that the chemical targeting approach, coupled with bioinformatics, site-directed mutagenesis and transport assays, proved fundamental in describing features of LAT1 such as the substrate binding site, regulatory domains and interactions with drugs that will be discussed in this review. The results on LAT1 can be considered to have general applicability to other transporters linked with human diseases.