Numerous studies suggest that common genetic and epigenetic factors such as p53, histone deacetylase (HDAC), brain-derived neurotrophic factor (BDNF), the (Ataxia Telangiectasia mutated) ATM gene, cyclin-dependent kinase 5 (CDK5), glycogen synthase kinase 3 (GSK3) and altered expression of microRNA (miRNA) play a crucial role in cancer and neurodegeneration. As there is growing evidence that epigenetic aberrations in cancer and neurological diseases lead to complex pathophysiological changes, the simultaneous targeting of epigenetic and other related pathways by dual-target inhibitors may contribute to the discovery of more effective and personalized therapeutic options. Computer-Aided Drug Design (CADD) provides comprehensive bioinformatic, chemoinformatic, and chemometric approaches for the design of novel chemotypes of epigenetic dual-target inhibitors, enabling efficient discovery of new drug candidates for innovative treatments of these multifactorial diseases. The detailed anticancer mechanisms by which the epigenetic dual-target inhibitors alter metastatic and tumorigenic properties, influence the tumor microenvironment, or regulate the immune response are also presented and discussed in the review. To improve our understanding of the pathogenesis of cancer and neurodegeneration, this review discusses novel therapeutic agents targeting different molecular mechanisms involved in these multifactorial diseases.

Considering the escalating global prevalence and the huge therapeutic demand for the treatment of hypertension, there is a persistent need to identify novel target sites for vasodilator action. This study aimed to investigate the role of TRPA1 channels in carvacrol-induced vasodilation and to design novel compounds based on carvacrol structure with improved activities. In an isolated tissue bath experiment, it was shown that 1 µM of the selective TRPA1 antagonist A967079 significantly (p < 0.001) reduced vasodilation induced by 3 mM of carvacrol. A reliable 3D-QSAR model with good statistical parameters was created (R2 = 0.83; Q2 = 0.59 and Rpred2 = 0.84) using 29 TRPA1 agonists. Obtained results from this model were used for the design of novel TRPA1 activators, and to predict their activity against TRPA1. Predicted pEC50 activities of these molecules range between 4.996 to 5.235 compared to experimental pEC50 of 4.77 for carvacrol. Molecular docking studies showed that designed molecules interact with similar amino acid residues of the TRPA1 channel as carvacrol, with eight compounds showing lower binding energies. In conclusion, carvacrol-induced vasodilation is partly mediated by the activation of TRPA1 channels. Combining different in silico approaches pointed out that the molecule D27 (2-[2-(hydroxymethyl)-4-methylphenyl]acetamide) is the best candidate for further synthesis and experimental evaluation in in vitro conditions.

Objective. The aim of this study was to investigate students’ knowledge, attitudes and hesitancy regarding COVID-19 vaccination. Methods. A cross-sectional questionnaire-based survey was conducted among a total of 1282 medical students and 509 non-medical students at four public universities in Bosnia and Herzegovina: Tuzla, Sarajevo, Banja Luka, and Mostar. Results. A significantly higher rate of vaccination was observed in the group of medical students as well as a higher level of knowledge about vaccination in general and vaccines against the COVID-19 disease. Students who received the COVID-19 vaccine had a higher level of knowledge about vaccination in general and COVID-19 vaccines in particular compared to the non-vaccinated students in the medical and non-medical groups, respectively. Furthermore, vaccinated students, regardless of the course they are taking, showed generally stronger positive attitudes compared to non-vaccinated students, regarding the safety and effectiveness of the COVID-19 vaccine. Both groups of students believe that the rapid development of the vaccine is contributing to refusal or hesitancy to receive a vaccine against COVID-19. Social media/networks were the main sources of information about the COVID-19 vaccine. We did not find any contribution of social media to the reduced level of COVID-19 vaccine coverage. Conclusion. Education of students about the benefits of the COVID-19 vaccine will lead to its better acceptance as well as the development of more positive attitudes towards vaccination in general, especially having in mind that students are the future population of parents, who will make decisions about vaccinating their children.

Using the Design of Experiments methodology (Response-Surface Methodology and Derringer's Desirability Function), a simple, fast and robust RP-HPLC method was developed for the analysis of enrofloxacin (EFC), its impurity A (fluoroquinolonic acid, FQ) and impurity B (ciprofloxacin, CPX). Gradient elution of samples was performed on a Zorbax Eclipse XDB C18 column (150 × 4.6 mm, 3.5 μm) with a mobile phase consisting of 32 mM phosphate buffer pH 3.5 – methanol (0 min-19.6% methanol; 15.5 min-19.6% methanol; 29.5 min-80% methanol; 30 min-19.6% methanol; 35 min-19.6% methanol), delivered at a flow rate of 1.5 mL min−1, wavelength of detection 278 nm (for EFX and CFX) and 265 nm for FQ. A good linear response was achieved in the range 15–35 μg mL−1 (EFX) and LOQ-150% for impurities (CFX and FQ). Other validation parameters were also tested: precision, accuracy, sensitivity and robustness. The developed method was shown to be simple, practical and suitable for the analysis of EFC and its impurities (CPX, FQ) in veterinary drugs.

Background/Aim: Therapy of diabetes mellitus type 2 includes drugs that act as inhibitors of dipeptidyl peptidase 4 (DPP-4) enzyme. Several DPP-4 inhibitors are marketed today and although they have favourable safety profile and tolerability, they show moderate activity in controlling glycaemia. The 3D quantitative structure-activity relationship (3D-QSAR) methodology was employed in order to find pharmacophore responsible for good DPP-4 inhibitory activity and designed new compounds with enhanced activity. Methods: For 3D-QSAR model development, 48 compounds structurally related to sitagliptin were collected from ChEMBL database. Structures of all compounds were optimised in order to find the best 3D conformations prior to QSAR modelling. To establish correlation between structure and biological activity Partial Least Squares (PLS) regression method integrated in Pentacle software was used. Results: Parameters of internal and external validation (R2 = 0.80, Q2 = 0.64 and R2 pred = 0.610) confirmed reliability of developed QSAR model. Analysis of obtained structural descriptors enabled identification of key structural characteristics that influenced DPP-4 inhibitory activity. Based on that information, new compounds were designed, of which 35 compounds had a better predicted activity, compared to sitagliptin. Conclusion: This QSAR model can be used for DPP-4 inhibitory activity prediction of structurally related compounds and resulting pharmacophore contains information useful for optimisation and design of new DPP-4 inhibitors. Finally, authors propose designed compounds for further synthesis, in vitro and in vivo testing, as new potential DPP-4 inhibitors.

Rational drug design implies usage of molecular modeling techniques such as pharmacophore modeling, molecular dynamics, virtual screening, and molecular docking to explain the activity of biomolecules, define molecular determinants for interaction with the drug target, and design more efficient drug candidates. Kinases play an essential role in cell function and therefore are extensively studied targets in drug design and discovery. Kinase inhibitors are clinically very important and widely used antineoplastic drugs. In this review, computational methods used in rational drug design of kinase inhibitors are discussed and compared, considering some representative case studies.