Introduction Young people aged 18-24 years old are a key demographic target for eliminating HIV transmission globally. Pre-exposure prophylaxis (PrEP), a prevention medication, reduces HIV transmission. Despite good uptake by gay and bisexual men who have sex with men, hesitancy to use PrEP has been observed in other groups, such as young people and people from ethnic minority backgrounds. The aim of this study was to explore young people's perceptions and attitudes to using PrEP. Design A qualitative transcendental phenomenological design was used. Participants and setting A convenience sample of 24 young people aged between 18 and 24 years was recruited from England. Methods Semistructured interviews and graphical elicitation were used to collect data including questions about current experiences of HIV care, awareness of using PrEP and decision-making about accessing PrEP. Thematic and visual analyses were used to identify findings. Results Young people had good levels of knowledge about HIV but poor understanding of using PrEP. In this information vacuum, negative stigma and stereotypes about HIV and homosexuality were transferred to using PrEP, which were reinforced by cultural norms portrayed on social media, television and film-such as an association between using PrEP and being a promiscuous, white, gay male. In addition, young people from ethnic minority communities appeared to have negative attitudes to PrEP use, compared with ethnic majority counterparts. This meant these young people in our study were unable to make decisions about when and how to use PrEP. Conclusion Findings indicate an information vacuum for young people regarding PrEP. A strength of the study is that theoretical data saturation was reached. A limitation of the study is participants were largely from Northern England, which has low prevalence of HIV. Further work is required to explore the information needs of young people in relation to PrEP.

COVID-19, which was first identified in 2019 in Wuhan, China, is a respiratory illness caused by a virus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although some patients infected with COVID-19 can remain asymptomatic, most experience a range of symptoms that can be mild to severe. Common symptoms include fever, cough, shortness of breath, fatigue, loss of taste or smell and muscle aches. In severe cases, complications can arise including pneumonia, acute respiratory distress syndrome, organ failure and even death, particularly in older adults or individuals with underlying health conditions. Treatments for COVID-19 include remdesivir, which has been authorised for emergency use in some countries, and dexamethasone, a corticosteroid used to reduce inflammation in severe cases. Biological drugs including monoclonal antibodies, such as casirivimab and imdevimab, have also been authorised for emergency use in certain situations. While these treatments have improved the outcome for many patients, there is still an urgent need for new treatments. Medicinal plants have long served as a valuable source of new drug leads and may serve as a valuable resource in the development of COVID-19 treatments due to their broad-spectrum antiviral activity. To date, various medicinal plant extracts have been studied for their cellular and molecular interactions, with some demonstrating anti-SARS-CoV-2 activity in vitro. This review explores the evaluation and potential therapeutic applications of these plants against SARS-CoV-2. This review summarises the latest evidence on the activity of different plant extracts and their isolated bioactive compounds against SARS-CoV-2, with a focus on the application of plant-derived compounds in animal models and in human studies.

The indole ring system is an important scaffold in a great number of biologically significant molecules and hence there are numerous methods to access this heterocyclic ring system. The Fischer indole reaction is one of the oldest methods, and due to its versatility, it is a widely employed method of preparing substituted indoles. This review will cover the period from 2016 to June 2022 and will focus on the application of the method in the area of medicinal chemistry.

This chapter mentions the forms of common analgesic ibuprofen, which have mostly identical physical properties but have three-dimensional shapes that are different. The three-dimensional shape of biological molecules and drugs is profoundly important for their action. The chapter introduces the concepts of isomerism, structure, and shape, particularly with reference to the activity of drugs and relates strongly to hybridization and bonding. The chapter defines the term ‘isomerism’, which is used to describe the ways in which molecules can have identical compositions in terms of carbon, hydrogen, and nitrogen. However, differences in their patterns of bonding or conformation may lead to dramatically different three-dimensional shapes. There are many drugs used in medicine which exhibit isomerism and it is essential to have a good understanding of this.

Diseases are often caused by defective proteins; these proteins rarely operate in isolation and may have several roles in the cell. Thus over time a defective protein may be involved in several disorders, either directly or indirectly. The multiple roles lead to the concept of a disease module or cluster. This work describes how we generate overlapping clusters from complex networks to explore the dynamic nature of diseases, the genes implicated with them and the drugs used to treat them. Link clustering is vital for community detection as it enables the integration of disparate sources of data and provides a better understanding of community hierarchy and community dynamics than non-link methods. Furthermore, we view not just the genes directly shared between diseases but also indirectly connected genes in the network neighborhood. We use data and information from the STITCH protein and drug interaction databases, OMIM disease database, lists of diseases categorized by MeSH and the DrugBank repository. The gene ontology, disease ontology and KEGG provide biological validity for the disease communities. We demonstrate how the detection of overlapping clusters enables the identification of biologically plausible communities consisting of cooperating proteins. We verify their role in disease with respect to targeting drugs more effectively with expert opinion. We have been able to identify various modules that make sense from a biological and medical perspective and validate drug repositioning candidates with clinicaltrials.gov.

Despite the significant progress in managing patients infected with HIV through the development of Highly Active Anti-Retroviral Therapy (HAART), major challenges and opportunities remain to be explored. Of particular interest, is the binding of glycoprotein 120 (gp120) to the primary cellular receptor Cluster of Differentiation 4 (CD4). In this work we describe our two phased computational process to identify useful compounds capable of binding to the gp120 protein for therapeutic purposes. We identified 187 compounds from the literature that conform to active binding sites on these proteins and use these as training/test sets. The data in the form of quantitative structure-activity relationships (QSAR) is downloaded from the ZINC database and transformed using principal components analysis. In the first phase we developed a Radial Basis Function neural network model that identifies potential inhibitors from a virtual screen of a subset of the ZINC database. In the second phase we modelled the top performing compounds using the Discovery Studio docking and screening software. By employing this approach, we identified that those compounds with a LogP value of approx 2–4 performed well in the binding simulations while the lower scoring compounds do not bind well.

Microreservoir-type transdermal drug delivery systems (MTDDS) can prevent drug crystallization; however, no current predictive model considers the impact of drug load and hydration on their physical stability. We investigated MTDDS films containing polyvinylpyrrolidone (PVP) as polymeric drug stabilizer in lipophilic pressure-sensitive adhesive (silicone). Medicated and unmedicated silicone films with different molar N-vinylpyrrolidone:drug ratios were prepared and characterized by Fourier transform infrared spectroscopy, differential scanning calorimetry, scanning electron microscopy, microscopy, dynamic vapor sorption (DVS), and stability testing for 4 months at different storage conditions. Homogeneously distributed drug-PVP associates were observed when nonaqueous emulsions, containing drug-PVP (inner phase) and silicone adhesive (outer phase), were dried to films. DVS data were essential to predict physical stability at different humidities. A predictive thermodynamic model was developed based on drug-polymer hydrogen-bonding interactions, using the Hoffman equation, to estimate the drug-PVP ratio needed to obtain stable MTDDS and to evaluate the impact of humidity on their physical stability. This new approach considers the impact of polymorphism on drug solubility by using easily accessible experimental data (Tm and DVS) and avoids uncertainties associated with the solubility parameter approach. In conclusion, a good fit of predicted and experimental data was observed.

Drug crystallization in transdermal drug delivery systems is a critical quality defect. The impact of drug load and hydration on the physical stability of polar (acrylic) drug-in-adhesive (DIA) films was investigated with the objective to identify predictive formulation parameters with respect to drug solubility and long-term stability. Medicated acrylic films were prepared over a range of drug concentrations below and above saturation solubility and were characterized by Fourier transform infrared spectroscopy, differential scanning calorimetry, polarized microscopy, and dynamic vapor sorption (DVS) analysis. Physical stability of medicated films was monitored over 4 months under different storage conditions and was dependent on solubility parameters, Gibbs free energy for drug phase transition from the amorphous to the crystalline state, and relative humidity. DVS data, for assessing H-bonding capacity experimentally, were essential to predict physical stability at different humidities and were used together with Gibbs free energy change and the Hoffman equation to develop a new predictive thermodynamic model to estimate drug solubility and stability in DIA films taking into account relative humidity.

Acrylates have been widely used in the synthesis of pharmaceutical polymers. The quantitation of residual acrylate monomers is vital as they are strong irritants and allergens, but after polymerization, are relatively inert, causing no irritation and allergies. Poly(ethylene oxide) (PEO) hydrogels were prepared using pentaerythritol tetra-acrylate (PETRA) as UV crosslinking agent. A simple, accurate, and robust quantitation method was developed based on gas chromatographic techniques (GC), which is suitable for routine analysis of residual PETRA monomers in these hydrogels. Unreacted PETRA was initially identified using gas chromatography–mass spectrometry (GC–MS). The quantitation of analyte was performed and validated using gas chromatography equipped with a flame ionization detector (GC–FID). A linear relationship was obtained over the range of 0.0002%–0.0450% (m/m) with a correlation coefficient (r2) greater than 0.99. The recovery (>90%), intra-day precision (%RSD <0.67), inter-day precision (%RSD <2.5%), and robustness (%RSD <1.62%) of the method were within the acceptable values. The limit of detection (LOD) and limit of quantitation (LOQ) were 0.0001% (m/m) and 0.0002% (m/m), respectively. This assay provides a simple and quick way of screening for residual acrylate monomer in hydrogels.

Complex networks are a graph theoretic method that can model genetic mutations, in particular single nucleotide polymorphisms (snps) which are genetic variations that only occur at single position in a DNA sequence. These can potentially cause the amino acids to be changed and may affect protein function and thus structural stability which can contribute to developing diseases. We show how snps can be represented by complex graph structures, the connectivity patterns if represented by graphs can be related to human diseases, where the proteins are the nodes (vertices) and the interactions between them are represented by links (edges). Disruptions caused by mutations can be explained as loss of connectivity such as the deletion of nodes or edges in the network (hence the term edgetics). Furthermore, diseases appear to be interlinked with hub genes causing multiple problems and this has led to the concept of the human disease network or diseasome. Edgetics is a relatively new concept which is proving effective for modelling the relationships between genes, diseases and drugs which were previously considered intractable problems.

Novel polyethylene oxide (PEO) hydrogel films were synthesized via UV crosslinking with varying concentrations of pentaerythritol tetra-acrylate (PETRA) as crosslinking agent. The aim was to study the effects of the crosslinking agent on the material properties of hydrogel films intended for dermatological applications. Fabricated film samples were characterized using swelling studies, scanning electron microscopy, tensile testing and rheometry. Films showed rapid swelling and high elasticity. The increase of PETRA concentration resulted in significant increase in the gel fraction and crosslinking density (ρc), while causing a significant decrease in the equilibrium water content (EWC), average molecular weight between crosslinks (\({\overline{M}}_{c}\)), and mesh size (ζ) of films. From the scanning electron microscopy, cross-linked PEO hydrogel network appeared as cross-linked mesh-like structure with interconnected micropores. Rheological studies showed PEO films required a minimum of 2.5% w/w PETRA to form stable viscoelastic solid gels. Preliminary studies concluded that a minimum of 2.5% w/w PETRA is required to yield films with desirable properties for skin application.