Journal: Molecular pharmaceutics
HIV infection is associated with symptoms of accelerated or accentuated aging that are likely to be driven not only by HIV itself, but also by the toxicity of long-term use of antiretroviral drugs. Therefore, it is crucially important to understand the mechanisms by which antiretroviral drugs may contribute to aging. The aim of this study was to investigate the hypothesis that antiretroviral drugs cause increased reactive oxygen species (ROS) generation that results in mitochondrial dysfunction and culminates in promoting cellular senescence. In addition, we applied targeted nanoparticle (NP)-based delivery to specifically enrich mitochondria with coenzyme Q10 (CoQ10) in order to enhance antioxidant protection. The studies employed neural progenitor cells (NPCs), as differentiation of these cells into mature neurons is affected both during HIV infection and in the aging process. Exposure of cultured NPCs to various combinations of HIV antiretroviral therapy (ART) induced a more than two-fold increase in mitochondrial ROS generation and mitochondrial membrane potential, a more than 50% decrease in oxygen consumption and ATP levels, a 60% decrease in SIRT3 expression, and a 42% decrease in cell proliferation relative to control levels. These alterations were accompanied by a 37% increase in beta-galactosidase staining and telomeres length shortened to more half of the length of controls as assessed by quantitative telomere-FISH labeling, indicating accelerated NPC senescence in response to ART exposure. Importantly, targeted nanoparticles delivered by CoQ10 effectively attenuated these effects. Overall, these results indicate that ART promotes cellular senescence by causing mitochondrial dysfunction, which can be successfully reversed by supplementation with mitochondria-targeted CoQ10.
Molecular imaging is advantageous for screening diseases such as breast cancer by providing precise spatial information on disease-associated biomarkers, something neither blood tests nor anatomical imaging can achieve. However, the high cost and risks of ionizing radiation for several molecular imaging modalities have prevented a feasible and scalable approach for screening. Clinical studies have demonstrated the ability to detect breast tumors using nonspecific probes such as indocyanine green, but the lack of molecular information and required intravenous contrast agent does not provide a significant benefit over current noninvasive imaging techniques. Here we demonstrate that negatively charged sulfate groups, commonly used to improve solubility of near-infrared fluorophores, enable sufficient oral absorption and targeting of fluorescent molecular imaging agents for completely noninvasive detection of diseased tissue such as breast cancer. These functional groups improve the pharmacokinetic properties of affinity ligands to achieve targeting efficiencies compatible with clinical imaging devices using safe, nonionizing radiation (near-infrared light). Together, this enables development of a “disease screening pill” capable of oral absorption and systemic availability, target binding, background clearance, and imaging at clinically relevant depths for breast cancer screening. This approach should be adaptable to other molecular targets and diseases for use as a new class of screening agents.
Deep learning is rapidly advancing many areas of science and technology with multiple success stories in image, text, voice and video recognition, robotics and autonomous driving. In this paper we demonstrate how deep neural networks (DNN) trained on large transcriptional response data sets can classify various drugs to therapeutic categories solely based on their transcriptional profiles. We used the perturbation samples of 678 drugs across A549, MCF-7 and PC-3 cell lines from the LINCS project and linked those to 12 therapeutic use categories derived from MeSH. To train the DNN, we utilized both gene level transcriptomic data and transcriptomic data processed using a pathway activation scoring algorithm, for a pooled dataset of samples perturbed with different concentrations of the drug for 6 and 24 hours. When applied to normalized gene expression data for “landmark genes,” DNN showed cross-validation mean F1 scores of 0.397, 0.285 and 0.234 on 3-, 5- and 12-category classification problems, respectively. At the pathway level DNN performed best with cross-validation mean F1 scores of 0.701, 0.596 and 0.546 on the same tasks. In both gene and pathway level classification, DNN convincingly outperformed support vector machine (SVM) model on every multiclass classification problem. For the first time we demonstrate a deep learning neural net trained on transcriptomic data to recognize pharmacological properties of multiple drugs across different biological systems and conditions. We also propose using deep neural net confusion matrices for drug repositioning. This work is a proof of principle for applying deep learning to drug discovery and development.
As the Ebola outbreak in West Africa continues and cases appear in the United States and other countries, the need for long-lasting vaccines to preserve global health is imminent. Here, we evaluate the long-term efficacy of a respiratory and sublingual (SL) adenovirus-based vaccine in non-human primates in two phases. In the first, a single respiratory dose of 1.4 × 10 (9) infectious virus particles (ivp)/kg of Ad-CAGoptZGP induced strong Ebola-glycoprotein (GP) specific CD8+ and CD4+ T cell responses and Ebola GP-specific antibodies in systemic and mucosal compartments and was partially (67%) protective from challenge 62 days after immunization. The same dose given by the SL route induced Ebola GP-specific CD8+ T cell responses similar to those induced by intramuscular (IM) injection, however, the Ebola GP-specific antibody response was low. All primates succumbed to infection. Three primates were then given the vaccine in an IN formulation that improved the immune response to Ebola in rodents. Three primates were immunized with 2.0 × 10(10) ivp/kg of vaccine by the SL route. Diverse populations of polyfunctional Ebola GP-specific CD4+ and CD8+ T cells and significant anti-Ebola GP antibodies were present in samples collected 150 days after respiratory immunization. The formulated vaccine was fully protective against challenge 21 weeks after immunization. While diverse populations of Ebola GP-specific CD4+ T cells were produced after SL immunization, antibodies were not neutralizing and the vaccine was not protective. To our knowledge, this is the first time that durable protection from a single dose respiratory recombinant adenovirus-based Ebola vaccine has been demonstrated in primates.
Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this data may be useful for biomarker identification and drug discovery, the bulk of it remains underutilized. Deep neural networks (DNNs) are efficient algorithms based on the use of compositional layers of neurons, with advantages well matched to the challenges -omics data presents. While achieving state-of-the-art results and even surpassing human accuracy in many challenging tasks, the adoption of deep learning in biomedicine has been comparatively slow. Here, we discuss key features of deep learning that may give this approach an edge over other machine learning methods. We then consider limitations and review a number of applications of deep learning in biomedical studies demonstrating proof of concept and practical utility.
Cancer is one of the most life-threatening diseases, which causes 7.6 million deaths and around 1 trillion dollars economic loss every year. Theranostic materials are expected to improve early detection and safe treatment through personalized medicine. Driven by the needs, we report the development of a theranostic plasmonic shell-magnetic core star shape nanomaterial based approach for the targeted isolation of rare tumor cells from the whole blood sample, followed by diagnosis and photothermal destruction. Experimental data with whole blood sample spiked with SK-BR-3 cancer cell shows that Cy3 attached S6 aptamer conjugated theranostic plasmonic/magnetic nanoparticles can be used for fluorescence imaging and magnetic separation even in 0.001% mixtures. A targeted photothermal experiment using 1064 nm near-IR light at 2-3 W/cm for 10 min resulted in selective irreparable cellular damage to most of the SK-BR-3 cancer cells. We discuss the possible mechanism and operating principle for the targeted imaging, separation, and photothermal destruction using theranostic magnetic/plasmonic nanotechnology. After the optimization of different parameters, this theranostic nanotechnology-driven assay could have enormous potential for applications as contrast agent and therapeutic actuators for cancer.
Huntington’s disease (HD) is a rare autosomal dominant neurodegenerative disease caused by the expression of a toxic Huntingtin (HTT) protein. The use of short interfering RNAs (siRNAs) to silence the mutant protein is one of the most promising therapeutic strategies under investigation. The biggest caveat to siRNA-based approaches is the lack of efficient and nontoxic delivery vectors for siRNA delivery to the central nervous system. In this study, we investigated the potential of modified amphiphilic β-cyclodextrins (CDs), oligosaccharide-based molecules, as novel siRNA neuronal carriers. We show that CDs formed nanosize particles which were stable in artificial cerebrospinal fluid. Moreover, these complexes were able to reduce the expression of the HTT gene in rat striatal cells (ST14A-HTT120Q) and in human HD primary fibroblasts. Only limited toxicity was observed with CD·siRNA nanoparticles in any of the in vitro models used. Sustained knockdown effects were observed in the striatum of the R6/2 mouse model of HD after single direct injections of CD·siRNA nanoparticles. Repeated brain injections of CD·siRNA complexes resulted in selective alleviation of motor deficits in this mouse model. Together these data support the utility of modified β-CDs as efficient and safe siRNA delivery vectors for RNAi-based therapies for neuropsychiatric and neurodegenerative disorders.
A conventional human pharmacokinetic in vivo study is often considered as the “gold standard” to determine bioequivalence (BE) of drug products. However, this BE approach is not always applicable to the products not intended to be delivered into the systemic circulation. For locally acting gastrointestinal (GI) products, well designed in vitro approaches might be more practical in that they are not only able to qualitatively predict the presence of the active substance at the site of action, but also to specifically assess the performance of the active substance. For example, lanthanum carbonate chewable tablet, a locally acting GI phosphate binder when orally administrated, can release free lanthanum ions in the acid environment of the upper GI tract. The lanthanum ions directly reach the site of action to bind with dietary phosphate released from food to form highly insoluble lanthanum-phosphate complexes. This prevents the absorption of phosphate consequently reducing the serum phosphate. Thus, using conventional PK approach to demonstrate BE is meaningless since plasma levels are not relevant for local efficacy in the GI tract. Additionally the bioavailability of lanthanum carbonate is less than 0.002 %, and therefore, PK approach is not feasible. Therefore, an alternative assessment method is required. This paper presents an in vitro approach that can be used in lieu of PK or clinical studies to determine the BE of lanthanum carbonate chewable tablets. It is hoped that this information can be used to finalize an in vitro guidance for BE studies of lanthanum carbonate chewable tablets as well as to assist with “in vivo” biowaiver decision making. The scientific information might be useful to the pharmaceutical industry for the purpose of planning and designing future BE studies.
The co-processing of active pharmaceutical ingredient (API) with an excipient which has a high glass transition temperature (Tg) is a recognised strategy to stabilise the amorphous form of a drug. This work investigates whether co-processing a model API, sulfadimidine (SDM) with a series of low Tg excipients prevents or reduces amorphisation of the crystalline drug. It was hypothesised that these excipients could exert a Tg lowering effect, resulting in composite Tg values lower than that of the API alone and promote crystallisation of the drug. Milled SDM and co-milled SDM with glutaric acid (GA), adipic acid (AA), succinic acid (SA) and malic acid (MA) were characterised with respect to their thermal, X-Ray diffraction, spectroscopic and vapour sorption properties. SDM was predominantly amorphous when milled alone, with an amorphous content of 82 %. No amorphous content was detected by dynamic vapour sorption (DVS) on co-milling SDM with 50 % w/w GA, and amorphous content of the API was reduced by almost 30 %, relative to the API milled alone, on co-milling with 50 % w/w AA. In contrast, amorphisation of SDM was promoted on co-milling with 50 % w/w SA and MA, as indicated by near infrared (NIR) spectroscopy. Results indicated that the API was completely amorphised in the SDM:MA co-milled composite. The saturated solubility of GA and AA in the amorphous API was estimated by thermal methods. It was observed that the Tg of the co-melt quenched composites reached a minimum and levelled out at this solubility concentration. Maximum crystallinity of API on co-milling was reached at excipient concentrations comparable to the saturated concentration solubility of excipient in the API. Moreover, the closer the Hildebrand solubility parameter of the excipient to the API, the greater was the inhibition of API amorphisation on co-milling. The results reported here indicate that an excipient with a low Tg coupled with high solubility in the API can prevent or reduce the generation of an amorphous phase on co-milling. Keywords: glass transition, amorphous, co-milling, solubility, excipient, thermal methods, vapour sorption, X- Ray diffraction.
We show that viruslike particles (VLPs) reassembled in vitro with the RNA bacteriophage MS2 coat protein and an RNA conjugate encompassing a siRNA and a known capsid assembly signal can be targeted to HeLa cells by covalent attachment of human transferrin. The siRNA VLPs protect their cargoes from nuclease, have a double-stranded conformation in the capsid and carry multiple drug and targeting ligands. The relative efficiency of VLP reassembly has been assessed, and conditions have been determined for larger scale production. Targeted VLPs have been purified away from unmodified VLPs for the first time allowing improved analysis of the effects of this synthetic virion system. The particles enter cells via receptor-mediated endocytosis and produce siRNA effects at low nanomolar concentrations. Although less effective than a commercial cationic lipid vector at siRNA delivery, the smaller amounts of internalized RNA with VLP delivery had an effect as good as if not better than the lipid transfection route. This implies that the siRNAs delivered by this route are more accessible to the siRNA pathway than identical RNAs delivered in complex lipid aggregates. The data suggest that the MS2 system continues to show many of the features that will be required to create an effective targeted drug delivery system. The fluorescence assays of siRNA effects described here will facilitate the combinatorial analysis of both future formulations and dosing regimes.