Efficient prediction of drug–drug interaction using deep learning models

A drug–drug interaction or drug synergy is extensively utilised for cancer treatment. However, prediction of drug–drug interaction is defined as an ill‐posed problem, because manual testing is only implementable on small group of drugs. Predicting the drug–drug interaction score has been a popular research topic recently. Recently many machine learning models have proposed in the literature to predict the drug–drug interaction score efficiently. However, these models suffer from the over‐fitting issue. Therefore, these models are not so‐effective for predicting the drug–drug interaction score. In this work, an integrated convolutional mixture density recurrent neural network is proposed and implemented. The proposed model integrates convolutional neural networks, recurrent neural networks and mixture density networks. Extensive comparative analysis reveals that the proposed model significantly outperforms the competitive models.Inspec keywords: cancer, learning (artificial intelligence), drugs, recurrent neural nets, convolutional neural nets, drug delivery systemsOther keywords: drug synergy, drug–drug interaction score, drug–drug interaction prediction, deep learning, cancer treatment, machine learning, convolutional mixture density recurrent neural network     

Honokiol–camptothecin loaded graphene oxide nanoparticle towards combinatorial anti‐cancer drug delivery

Honokiol (HK) is a natural product isolated from the bark, cones, seeds and leaves of plants belonging to the genus Magnolia. It possesses anti‐cancer activity which can efficiently impede the growth and bring about apoptosis of a diversity of cancer cells. The major concerns of using HK are its poor solubility and lack of targeted drug delivery. In this study, a combinatorial drug is prepared by combining HK and camptothecin (CPT). Both CPT and HK belong to the Magnolian genus and induce apoptosis by cell cycle arrest at the S‐phase and G1 phase, respectively. The combinatorial drug thus synthesised was loaded onto a chitosan functionalised graphene oxide nanoparticles, predecorated with folic acid for site‐specific drug delivery. The CPT drug‐loaded nanocarrier was characterised by X‐ray diffractometer, scanning electron microscope, transmission electron microscope, UV–vis spectroscopy and fluorescence spectroscopy, atomic force microscopy. The antioxidant properties, haemolytic activity and anti‐inflammatory activities were analysed. The cellular toxicity was analysed by 3‐(4,5‐Dimethylthiazol‐2‐yl)‐2,5‐Diphenyltetrazolium Bromide (MTT assay) and Sulforhodamine B (SRB) assay against breast cancer (MCF‐7) cell lines.Inspec keywords: nanofabrication, cancer, nanoparticles, atomic force microscopy, graphene, scanning electron microscopy, cellular biophysics, toxicology, transmission electron microscopy, drug delivery systems, nanomedicine, tumours, solubilityOther keywords: targeted drug delivery, combinatorial drug, Magnolian genus, apoptosis, cell cycle, chitosan functionalised graphene oxide nanoparticles, site‐specific drug delivery, CPT drug‐loaded nanocarrier, transmission electron microscope, fluorescence spectroscopy, haemolytic activity, antiinflammatory activities, breast cancer cell lines, honokiol–camptothecin loaded graphene oxide nanoparticle, combinatorial anti‐cancer drug delivery, natural product, genus Magnolia, anticancer activity, cancer cells     

Prediction of drug synergy score using ensemble based differential evolution

Prediction of drug synergy score is an ill‐posed problem. It plays an efficient role in the medical field for inhibiting specific cancer agents. An efficient regression‐based machine learning technique has an ability to minimise the drug synergy prediction errors. Therefore, in this study, an efficient machine learning technique for drug synergy prediction technique is designed by using ensemble based differential evolution (DE) for optimising the support vector machine (SVM). Because the tuning of the attributes of SVM kernel regulates the prediction precision. The ensemble based DE employs two trial vector generation techniques and two control attributes settings. The initial generation technique has the best solution and the other is without the best solution. The proposed and existing competitive machine learning techniques are applied to drug synergy data. The extensive analysis demonstrates that the proposed technique outperforms others in terms of accuracy, root mean square error and coefficient of correlation.Inspec keywords: cancer, evolutionary computation, support vector machines, regression analysis, drugs, learning (artificial intelligence), medical computingOther keywords: ensemble based differential evolution, specific cancer agents, efficient regression‐based machine learning technique, drug synergy prediction errors, efficient machine learning technique, drug synergy prediction technique, support vector machine, prediction precision, trial vector generation techniques, initial generation technique, drug synergy data, drug synergy score prediction, medical field, SVM kernel attributes, ensemble based DE, control attribute settings, competitive machine learning techniques, root mean square error     

Classification of drug molecules for oxidative stress signalling pathway

In humans, oxidative stress is involved in the development of diabetes, cancer, hypertension, Alzheimers’ disease, and heart failure. One of the mechanisms in the cellular defence against oxidative stress is the activation of the Nrf2‐antioxidant response element (ARE) signalling pathway. Computation of activity, efficacy, and potency score of ARE signalling pathway and to propose a multi‐level prediction scheme for the same is the main aim of the study as it contributes in a big amount to the improvement of oxidative stress in humans. Applying the process of knowledge discovery from data, required knowledge is gathered and then machine learning techniques are applied to propose a multi‐level scheme. The validation of the proposed scheme is done using the K‐fold cross‐validation method and an accuracy of 90% is achieved for prediction of activity score for ARE molecules which determine their power to refine oxidative stress.Inspec keywords: cancer, cellular biophysics, biochemistry, drugs, molecular biophysics, proteins, learning (artificial intelligence), medical computingOther keywords: oxidative stress, Nrf2‐antioxidant response element signalling pathway, ARE signalling pathway, diabetes, cancer, hypertension, Alzheimers’ disease, heart failure, machine learning techniques, K‐fold cross‐validation method, ARE molecules     

MPGraph: multi‐view penalised graph clustering for predicting drug–target interactions

Identifying drug–target interactions has been a key step for drug repositioning, drug discovery and drug design. Since it is expensive to determine the interactions experimentally, computational methods are needed for predicting interactions. In this work, the authors first propose a single‐view penalised graph (SPGraph) clustering approach to integrate drug structure and protein sequence data in a structural view. The SPGraph model does clustering on drugs and targets simultaneously such that the known drug–target interactions are best preserved in the clustering results. They then apply the SPGraph to a chemical view with drug response data and gene expression data in NCI‐60 cell lines. They further generalise the SPGraph to a multi‐view penalised graph (MPGraph) version, which can integrate the structural view and chemical view of the data. In the authors'' experiments, they compare their approach with some comparison partners, and the results show that the SPGraph could improve the prediction accuracy in a small scale, and the MPGraph can achieve around 10% improvements for the prediction accuracy. They finally give some new targets for 22 Food and Drug Administration approved drugs for drug repositioning, and some can be supported by other references.Inspec keywords: graphs, drug delivery systems, drugs, proteins, molecular biophysics, molecular configurations, optimisation, eigenvalues and eigenfunctions, Laplace equations, cancer, cellular biophysics, gene therapy, medical computingOther keywords: MPGraph, multiview penalised graph clustering, drug‐target interactions, drug repositioning, drug discovery, drug design, computational methods, single‐view penalized graph clustering approach, drug structure, protein sequence data, SPGraph model, optimisation problem, spectral clustering, eigenvalue decomposition, Laplacian model, gene expression data, NCI‐60 cell lines     

Improvement in prediction of antigenic epitopes using stacked generalisation: an ensemble approach

The major intent of peptide vaccine designs, immunodiagnosis and antibody productions is to accurately identify linear B‐cell epitopes. The determination of epitopes through experimental analysis is highly expensive. Therefore, it is desirable to develop a reliable model with significant improvement in prediction models. In this study, a hybrid model has been designed by using stacked generalisation ensemble technique for prediction of linear B‐cell epitopes. The goal of using stacked generalisation ensemble approach is to refine predictions of base classifiers and to get rid of the worse predictions. In this study, six machine learning models are fused to predict variable length epitopes (6–49 mers). The proposed ensemble model achieves 76.6% accuracy and average accuracy of repeated 10‐fold cross‐validation is 73.14%. The trained ensemble model has been tested on the benchmark dataset and compared with existing sequential B‐cell epitope prediction techniques including APCpred, ABCpred, BCpred and AAPBCPred.Inspec keywords: generalisation (artificial intelligence), support vector machines, cellular biophysics, pattern classification, proteins, learning (artificial intelligence), bioinformaticsOther keywords: antigenic epitopes, stacked generalisation, peptide vaccine designs, immunodiagnosis, antibody productions, linear B‐cell epitopes, generalisation ensemble technique, generalisation ensemble approach, machine learning models, base classifiers     

Chitosan nanoparticles loaded with aspirin and 5‐fluororacil enable synergistic antitumour activity through the modulation of NF‐κB/COX‐2 signalling pathway

Based on the enhancement of synergistic antitumour activity to treat cancer and the correlation between inflammation and carcinogenesis, the authors designed chitosan nanoparticles for co‐delivery of 5‐fluororacil (5‐Fu: an as anti‐cancer drug) and aspirin (a non‐steroidal anti‐inflammatory drug) and induced synergistic antitumour activity through the modulation of the nuclear factor kappa B (NF‐κB)/cyclooxygenase‐2 (COX‐2) signalling pathways. The results showed that aspirin at non‐cytotoxic concentrations synergistically sensitised hepatocellular carcinoma cells to 5‐Fu in vitro. It demonstrated that aspirin inhibited NF‐κB activation and suppressed NF‐κB regulated COX‐2 expression and prostaglandin E2 (PGE2) synthesis. Furthermore, the proposed results clearly indicated that the combination of 5‐Fu and aspirin by chitosan nanoparticles enhanced the intracellular concentration of drugs and exerted synergistic growth inhibition and apoptosis induction on hepatocellular carcinoma cells by suppressing NF‐κB activation and inhibition of expression of COX‐2.Inspec keywords: proteins, molecular biophysics, cellular biophysics, biomedical materials, cancer, nanoparticles, drug delivery systems, enzymes, tumours, nanomedicine, drugsOther keywords: chitosan nanoparticles, aspirin, 5‐fluororacil, synergistic antitumour activity, anticancer drug, nonsteroidal antiinflammatory drug, hepatocellular carcinoma cells, NF‐κB activation, NF‐κB regulated COX‐2 expression, PGE2, synergistic growth inhibition, apoptosis induction, prostaglandin E2 synthesis, intracellular concentration, noncytotoxic concentrations, NF‐κB‐cyclooxygenase‐2 signalling pathways, cyclooxygenase‐2, nuclear factor kappa B     

Preparation and characterisation of magnetosomes based drug conjugates for cancer therapy

The authors report a novel, effective and enhanced method of conjugating anticancer drug, paclitaxel and gallic acid with magnetosomes. Here, anticancer drugs were functionalised with magnetosomes membrane by direct and indirect (via crosslinkers: glutaraldehyde and 3‐aminopropyltriethoxysilane) adsorption methods. The prepared magnetosome–drug conjugates were characterised by Fourier transform infrared, zeta potential, field‐emission scanning electron microscope and thermogravimetric analysis/differential scanning calorimetry. The drug‐loading efficiency and capacity were found to be 87.874% for paclitaxel (MP) and 71.3% for gallic acid (MG), respectively as calculated by ultraviolet spectroscopy and high‐performance liquid chromatography. The drug release demonstrated by the diffusion method in phosphate buffer (PBS), showing a prolonged drug release for MP and MG, respectively. The cytotoxicity effect of the MP and MG displayed cytotoxicity of 69.71%, 55.194% against HeLa and MCF‐7 cell lines, respectively. The reactive oxygen species, acridine orange and ethidium bromide and 4, 6‐diamidino‐2‐phenylindole staining of the drug conjugates revealed the apoptotic effect of MP and MG. Further, the regulation of tumour suppressor protein, p53 was determined by western blotting which showed an upregulation of p53. Comparatively, the magnetosome–drug conjugates prepared by direct adsorption achieved the best effects on the drug‐loading efficiency and the increased percentage of cancer cell mortality and the upregulation of P53. The proposed research ascertains that magnetosomes could be used as effective nanocarriers in cancer therapy.Inspec keywords: cancer, molecular biophysics, cellular biophysics, tumours, drug delivery systems, adsorption, scanning electron microscopy, biomedical materials, nanofabrication, biochemistry, drugs, proteins, nanomedicine, toxicology, nanobiotechnology, nanoparticles, Fourier transform spectra, electrokinetic effects, differential scanning calorimetry, infrared spectra, chromatographyOther keywords: magnetosomes based drug, cancer therapy, enhanced method, gallic acid, anticancer drugs, magnetosomes membrane, glutaraldehyde, 3‐aminopropyltriethoxysilane, prepared magnetosome–drug conjugates, zeta potential field‐emission scanning electron microscope, drug‐loading efficiency, high‐performance liquid chromatography, diffusion method, phosphate buffer saline, prolonged drug release, cytotoxicity effect, MCF‐7 cell lines, 6‐diamidino‐2‐phenylindole staining, apoptotic effect, direct adsorption, cancer cell mortality, effective nanocarriers     

Design and development of artemisinin and dexamethasone loaded topical nanodispersion for the effective treatment of age‐related macular degeneration

Age‐related macular degeneration (AMD) is a disease affecting the macula by the new blood vessels formation. AMD is widely treated with a combination of anti‐angiogenic and anti‐vascular endothelial growth factor (VEGF) agents. The topical administration of nanodispersions showed enhanced ocular residence time with controlled and prolonged drug delivery to the disease site at the back of the eye. In the present study we developed and characterized nanodispersion containing anti‐angiogenic (artemisinin) and anti‐VEGF agent (dexamethasone) for the topical ocular administration in order to obtain a required drug concentration in the posterior part of the eye. The nanodispersions were prepared with varying concentration of polymer, polyvinyl pyrrolidone K90 and polymeric surfactant, Poloxamer 407. The nanodispersions were found to be smooth and spherical in shape with a size range of 12–26 nm. In‐vitro drug release studies showed the 90–101% of artemisinin and 55–103% of dexamethasone release from the nanodispersions. The blank formulation with a high concentration of polymer and polymeric surfactant showed an acceptable level of haemolysis and DNA damage. The chorioallantoic membrane assay suggested that the nanodispersion possess good anti‐angiogenic effect. Hence the formulated artemisinin and dexamethasone nanodispersion may have the great potential for the AMD treatment.Inspec keywords: drug delivery systems, drugs, eye, blood vessels, DNA, biochemistry, nanofabrication, molecular biophysics, nanomedicine, diseases, biomedical materials, polymers, membranesOther keywords: topical administration, enhanced ocular residence time, controlled prolonged drug delivery, disease site, eye, topical ocular administration, polymeric surfactant, dexamethasone release, dexamethasone nanodispersion, AMD treatment, blood vessel formation, drug concentration, in‐vitro drug release, antiangiogenic effect, artemisinin, dexamethasone loaded topical nanodispersion, age‐related macular degeneration effective treatment, antivascular endothelial growth factor agents, antiangiogenic endothelial growth factor agents, antiVEGF agent, polyvinyl pyrrolidone K90, polymer concentration, Poloxamer 407, size 12.0 nm to 26.0 nm, chorioallantoic membrane assay, DNA damage, haemolysis     

CdO nanoparticles,c‐MWCNT nanoparticles and CdO nanoparticles/c‐MWCNT nanocomposite fibres: in vitro assessment of anti‐proliferative and apoptotic studies in HeLa cancer cell line

A simple ultrasonic assisted chemical technique was used to synthesise cadmium oxide (CdO) nanoparticles (NPs) and CdO NPs/c‐Multiwalled carbon nanotube (c‐MWCNT) nanocomposite fibres.To confirm the physio‐chemico properties and to analyse surface morphology of the obtained nanomaterials X‐Ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and field emission scanning electron microscopy (FESEM) were performed. To evaluate the anti‐cancer property of CdO NPs, c‐MWCNT NPs and CdO NPs/c‐MWCNT nanocomposite fibres, an anti‐proliferative assay test (Methylthiazolyl diphenyl‐ tetrazolium bromide ‐ MTT assay) were performed on HeLa cells which further estimated IC50 value (Least concentration of sample in which nearly 50% of cells remain alive) under in‐vitro conditions. On comparison, CdONPs/c‐MWCNT based system was found to be superior by achieving 52.3% cell viability with its minimal IC50 value of 31.2 μg/ml. Lastly, the CdO NPs based system was taken up for an apoptotic study using DNA fragmentation assay for estimating its ability to cleave the DNA of the HeLa cells into internucleosomal fragments using the agarose gel electrophoresis method. In conclusion, based on our observations, CdO NPs/c‐MWCNT hybrid based system can be further used for the development of efficient drug delivery and therapeutic systems.Inspec keywords: drug delivery systems, electrophoresis, oxidation, toxicology, DNA, nanoparticles, drugs, field emission electron microscopy, scanning electron microscopy, nanofabrication, surface morphology, cancer, X‐ray diffraction, nanomedicine, cellular biophysics, filled polymers, biomedical materials, molecular biophysics, biochemistry, Fourier transform infrared spectra, multi‐wall carbon nanotubesOther keywords: c‐MWCNT nanoparticles, apoptotic study, HeLa cancer cell line, cadmium oxide nanoparticles, c‐MWCNT NPs, anti‐proliferative assay test [methyl thiazolyl diphenyl‐tetrazolium bromide assay], human epithelioid cervix carcinoma cells, live cells, CdO NP‐based system, IC50 concentration, HeLa cell line, cell deaths, CdO‐C     

Nano‐encapsulated Tinospora cordifolia (Willd.) using poly (D,L‐lactide) nanoparticles educe effective control in streptozotocin‐induced type 2 diabetic rats

The therapeutics for type 2 diabetes mellitus has emerged in the current century towards nanomedicine incorporated with plant active compounds. In this study, Tinospora cordifolia loaded poly (D, L‐lactide) (PLA) nanoparticles (NPs) were evaluated in vivo for their anti‐hyperglycemic potency towards streptozotocin‐induced type 2 diabetic rats. T. cordifolia loaded PLA NPs were synthesised by the double solvent evaporation method using PLA polymer. The NPs were then characterised and administrated orally for 28 successive days to streptozotocin‐induced diabetic rats. The PLA NPs had significant anti‐diabetic effects which were equal to the existing anti‐diabetic drug glibenclamide. The antidiabetic activity is due to the synergism of compounds present in stem extract of the plant which reduced the side effects and anti‐diabetic.Inspec keywords: blood, nanofabrication, drug delivery systems, biochemistry, evaporation, nanoparticles, nanomedicine, drugs, diseases, polymers, biomedical materialsOther keywords: PLA nanoparticles, antidiabetic effects, nanoencapsulated Tinospora cordifolia, streptozotocin‐induced type 2 diabetic rats, type 2 diabetes mellitus, poly(d, l‐lactide) nanoparticles, diabetic drug glibenclamide, nanomedicine, antihyperglycemic potency, double‐solvent evaporation     

Overcoming the blood–brain barrier in neurodegenerative disorders and brain tumours

Drug delivery is one of the major challenges in the treatment of central nervous system disorders. The brain needs to be protected from harmful agents, which are done by the capillary network, the so‐called blood–brain barrier (BBB). This protective guard also prevents the delivery of therapeutic agents to the brain and limits the effectiveness of treatment. For this reason, various strategies have been explored by scientists for overcoming the BBB from disruption of the BBB to targeted delivery of nanoparticles (NPs) and cells and immunotherapy. In this review, different promising brain drug delivery strategies including disruption of tight junctions in the BBB, enhanced transcellular transport by peptide‐based delivery, local delivery strategies, NP delivery, and cell‐based delivery have been fully discussed.Inspec keywords: drugs, tumours, neurophysiology, blood, biochemistry, brain, drug delivery systems, nanoparticles, biomedical materials, molecular biophysics, cellular biophysics, nanomedicine, diseases, proteins, reviewsOther keywords: blood–brain barrier, neurodegenerative disorders, central nervous system disorders, BBB, therapeutic agents, targeted delivery, peptide‐based delivery, local delivery strategies, NP delivery, cell‐based delivery, brain drug delivery strategies, brain tumours, nanoparticles, immunotherapy, review     

HER‐2 aptamer‐targeted Ecoflex® nanoparticles loaded with docetaxel promote breast cancer cells apoptosis and anti‐metastatic effect

Breast cancer is a major cause of cancer mortality. Regarding the advantages of polymeric nanoparticles as drug delivery systems with targeting potential, in this study the antitumor mechanism of targeted docetaxel polymeric nanoparticles of Ecoflex^® was exploited. Since the overexpression of HER‐2 receptor in breast cancer cases is associated with poor prognosis and more aggressive disease, the proposed nanoparticles were conjugated to HER‐2 specific aptamer molecules. In vitro cytotoxicity was evaluated by MTT assay. Flow‐cytometry analysis was performed to evaluate the cellular uptake of nanoparticles loaded with a fluorescent probe. Anti‐migration effects of samples were studied. Annexin IV‐FITC and propidium iodide were implemented to investigate apoptosis induction and cell cycle analysis. Enhanced cytotoxicity compared with free docetaxel was explained considering improved cellular uptake of the nanoparticles and induced apoptosis in a larger portion of cells. Lower relative migration demonstrated enhanced anti‐migration effect of nanoparticles, and cell cycle was arrested in G2/M phase using both formulations so the anti‐microtubule mechanism of the drug was not altered. Therefore, this system could offer a potential substitute for the currently marketed docetaxel formulations, which may reduce adverse effects of the drug, while further in vivo and clinical investigations are required.Inspec keywords: cancer, molecular biophysics, drug delivery systems, fluorescence, biomedical materials, drugs, tumours, nanomedicine, proteins, toxicology, biochemistry, nanoparticles, diseases, cell motility, polymersOther keywords: antitumor mechanism, targeted docetaxel polymeric nanoparticles, HER‐2 specific aptamer molecules, MTT assay, flow‐cytometry analysis, annexin IV‐FITC, apoptosis induction, cell cycle, lower relative migration, cancer mortality, drug delivery systems, aggressive disease, in vitro cytotoxicity, cellular uptake, breast cancer cell apoptosis, antimetastatic effect, HER‐2 aptamer‐targeted Ecoflex nanoparticles, antimigration effect, antimicrotubule mechanism, HER‐2 receptor, fluorescent probe, propidium iodide     

Prognostic alternative splicing signature in cervical squamous cell carcinoma

Basing on alternative splicing events (ASEs) databases, the authors herein aim to explore potential prognostic biomarkers for cervical squamous cell carcinoma (CESC). mRNA expression profiles and relevant clinical data of 223 patients with CESC were obtained from The Cancer Genome Atlas (TCGA). Correlated genes, ASEs and percent‐splice‐in (PSI) were downloaded from SpliceSeq, respectively. The PSI values of survival‐associated alternative splicing events (SASEs) were used to construct the basis of a prognostic index (PI). A protein–protein interaction (PPI) network of genes related to SASEs was generated by STRING and analysed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Consequently, 41,776 ASEs were discovered in 19,724 genes, 2596 of which linked with 3669 SASEs. The PPI network of SASEs related genes revealed that TP53 and UBA52 were core genes. The low‐risk group had a longer survival period than high‐risk counterparts, both groups being defined according to PI constructed upon the top 20 splicing events or PI on the overall splicing events. The AUC value of ROC reached up to 0.88, demonstrating the prognostic potential of PI in CESC. These findings suggested that ASEs involve in the pathogenesis of CESC and may serve as promising prognostic biomarkers for this female malignancy.Inspec keywords: gynaecology, molecular biophysics, genomics, proteins, cellular biophysics, genetics, medical computing, cancer, ontologies (artificial intelligence), RNAOther keywords: protein‐protein interaction network, CESC pathogenesis, gene ontology, Kyoto‐encyclopedia‐of‐genes‐and‐genomes, SASEs related genes, PPI network, survival‐associated alternative splicing events, PSI values, percent‐splice‐in, Cancer Genome Atlas, mRNA expression profiles, prognostic biomarkers, alternative splicing events databases, cervical squamous cell carcinoma, prognostic alternative splicing signature     

Investigating receptor enzyme activity using time‐scale analysis

At early drug discovery, purified protein‐based assays are often used to characterise compound potency. In the context of dose response, it is often perceived that a time‐independent inhibitor is reversible and a time‐dependent inhibitor is irreversible. The legitimacy of this argument is investigated using a simple kinetics model, where it is revealed by model‐based analytical analysis and numerical studies that dose response of an irreversible inhibitor may appear time‐independent under certain parametric conditions. Hence, the observation of time‐independence cannot be used as sole evidence for identification of inhibitor reversibility. It has also been discussed how the synthesis and degradation of a target receptor affect drug inhibition in an in vitro cell‐based assay setting. These processes may also influence dose response of an irreversible inhibitor in such a way that it appears time‐independent under certain conditions. Furthermore, model‐based steady‐state analysis reveals the complexity nature of the drug–receptor process.Inspec keywords: enzymes, molecular biophysics, drugs, biochemistry, reaction kinetics, cellular biophysicsOther keywords: receptor enzyme activity, time‐scale analysis, drug discovery, purified protein‐based assays, compound potency, dose response, reversible time‐independent inhibitor, irreversible time‐dependent inhibitor, kinetics model, target receptor degradation, drug inhibition, in vitro cell‐based assay setting, model‐based steady‐state analysis, drug‐receptor process     

Folate encapsulation in PEG‐diamine grafted mesoporous Fe3 O4 nanoparticles for hyperthermia and in vitro assessment

Effective and targeted delivery of the antitumour drugs towards the specific cancer spot is the major motive of drug delivery. In this direction, suitably functionalised magnetic iron oxide nanoparticles (NPs) have been utilised as a theranostic agent for imaging, hyperthermia and drug delivery applications. Herein, the authors reported the preparation of multifunctional polyethyleneglycol‐diamine functionalised mesoporous superparamagnetic iron oxide NPs (SPION) prepared by a facile solvothermal method for biomedical applications. To endow targeting ability towards tumour site, folic acid (FA) is attached to the amine groups which are present on the NPs surface by 1‐ethyl‐3‐(3‐dimethylaminopropyl) carbodiimide hydrochloride/N‐hydroxysuccinimide chemistry. FA attached SPION shows good colloidal stability and possesses high drug‐loading efficiency of ∼ 96% owing to its mesoporous nature and the electrostatic attachment of daunosamine (NH₃ ⁺) group of doxorubicin (DOX) towards the negative surface charge of carboxyl and hydroxyl group. The NPs possess superior magnetic properties in result endowed with high hyperthermic ability under alternating magnetic field reaching the hyperthermic temperature of 43°C within 223 s at NP''s concentration of 1 mg/ml. The functionalised NPs possess non‐appreciable toxicity in breast cancer cells (MCF‐7) which is triggered under DOX‐loaded SPION.Inspec keywords: nanoparticles, nanocomposites, mesoporous materials, colloids, biochemistry, nanomagnetics, molecular biophysics, tumours, superparamagnetism, drugs, toxicology, biomedical materials, nanofabrication, hyperthermia, cancer, magnetic particles, cellular biophysics, nanomedicine, iron compounds, drug delivery systems, filled polymers, biological organs, liquid phase depositionOther keywords: NP surface, colloidal stability, drug‐loading efficiency, hydroxyl group, magnetic properties, high hyperthermic ability, magnetic field, DOX‐loaded SPION, folate encapsulation, targeted delivery, antitumour drugs, specific cancer spot, magnetic iron oxide nanoparticles, theranostic agent, drug delivery applications, multifunctional polyethyleneglycol‐diamine, facile solvothermal method, biomedical applications, tumour site, amine groups, mesoporous superparamagnetic nanoparticles, PEG‐diamine grafted mesoporous nanoparticles, 1‐ethyl‐3‐(3‐dimethylaminopropyl) carbodiimide hydrochloride‐N‐hydroxysuccinimide chemistry, daunosamine group, carboxyl group, breast cancer cells, temperature 43.0 degC, Fe₃ O₄      

Design,characterisation and drug release study of polymeric,drug‐eluting single layer thin films on the surface of intraocular lenses

To design, develop and study a novel drug delivery system for intraocular applications. The spin coating technique was applied to develop a polymeric, drug‐eluting thin film consisting of a blend of organic polymers [poly (D, L lactide coglycolide) lactide: glycolide 75: 25, PLGA and polycaprolactone, PCL] and dexamethasone on the surface of intraocular lenses (IOLs). The initial durability of the IOLs during spinning was assessed. Information about the structural and optical properties of the modified IOLs was extracted using atomic force microscopy, scanning electron microscopy and spectroscopic ellipsometry. A drug release study was conducted for 8 weeks. The IOLs were durable in spinning speeds higher than the ones used to develop thin films. Single‐layer thin films were successfully developed on the optics and the haptics of the lenses. The films formed nanopores with encapsulated aggregates of dexamethasone. The spectroscopic ellipsometry showed an acceptable optical transparency of the lenses regardless of the deposition of the drug‐eluting films on their surface. The drug release study demonstrated gradual dexamethasone release over the selected period. In conclusion, the novel drug‐eluting IOL system exhibited desired properties regarding its transparency and drug release rate. Further research is necessary to assess their suitability as an intraocular drug delivery system.Inspec keywords: ellipsometry, encapsulation, nanoporous materials, spin coating, polymer blends, biodegradable materials, surface treatment, polymer films, atomic force microscopy, transparency, nanomedicine, durability, scanning electron microscopy, drug delivery systemsOther keywords: drug release, intraocular lenses, intraocular applications, spin coating technique, modified IOLs, spectroscopic ellipsometry, dexamethasone release, transparency, drug release rate, intraocular drug delivery system, drug‐eluting IOL system, polymeric drug‐eluting single‐layer thin films, optical properties, structural properties     

Lobelia trigona Roxb ‐based nanomedicine with enhanced biological applications: in vitro and in vivo approach

This is the first study to report the green synthesis of Lobelia trigona Roxb‐ mediated silver nanoparticles (LTAgNPs). The optical and structural properties of the synthesised LTAgNPs were analysed using ultraviolet–visible spectroscopy, scanning electron microscopy, Fourier transform infrared, dynamic light scattering and energy dispersive X‐ray. LTAgNps were evaluated for their anti‐bacterial and anti‐fungal properties against 18 pathogens and exhibited significant inhibition against all the strains tested. LTAgNPs had potential scavenging effects on the DPPH, ^• OH, O₂ ^•− free radical scavenging assays and reducing power assay. LTAgNps possess strong anti‐cancer activity against five human cancer cell lines (A549, MCF‐7, MDA‐MB‐231, HeLa and KB) in a dose‐dependent manner. The antiproliferative, anti‐inflammatory and genotoxicity effects of LTAgNPs were further confirmed by the lactate dehydrogenase release assay, nitric oxide inhibitory assay and comet assay. Furthermore, the incision, excision and burn wound‐healing activity of formulated LTAgNPs ointment was assessed in rats. All the wounds had significant healing in groups treated with LTAgNPs ointment compared to the groups treated with the commonly prescribed ointment (Silverex^TM). This study shows and suggests that the previously unreported LTAgNPs could be used as a nanomedicine with significant biological applications.Inspec keywords: molecular biophysics, biomedical materials, scanning electron microscopy, biochemistry, cancer, microorganisms, silver, cellular biophysics, nanofabrication, wounds, nanomedicine, ultraviolet spectra, toxicology, antibacterial activity, light scattering, nanoparticles, enzymes, visible spectra, Fourier transform infrared spectraOther keywords: Lobelia trigona Roxb‐based nanomedicine, biological applications, Lobelia trigona Roxb‐mediated silver nanoparticles, optical properties, structural properties, ultraviolet‐visible spectroscopy, dynamic light scattering, antibacterial properties, antifungal properties, scavenging effects, free radical scavenging, power assay, anticancer activity, antiinflammatory effects, genotoxicity effects, lactate dehydrogenase release assay, nitric oxide inhibitory assay, excision, burn wound‐healing activity, formulated LTAgNPs ointment, in vivo approach, in vitro approach, scanning electron microscopy, Fourier transform infrared spectroscopy, energy dispersive X‐ray analysis, pathogens, strains, A549 human cancer cell lines, MCF‐7 human cancer cell lines, MDA‐MB‐231 human cancer cell lines, HeLa human cancer cell lines, antiproliferative effects, comet assay, Ag