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Multielement analysis and chemometric methods were proposed to discriminate the Sorrento lemon (PGI) juices according to geographical origin. In 2018 and 2019, 169 fruits from three farms in PGI area and two in not-PGI area were collected and analysed for essential and not-essential elements by ICP-MS. The PCA of multielement fingerprinting grouped lemon juices from PGI farms revealing a strong differentiation at small geographical scale. The S-LDA discriminated lemon juices for Mo, Ba, Rb, Mg, Co, Ca, Fe, Sr on the two production years, giving 97.7% correct classification, 98.5% accuracy and 93.8% external validation. The good correlation lemon juice vs cultivation soil and the soil discrimination by not-essential elements suggested the use of these elements as reliable indicators of lemon juice provenances. Despite lowering the number of variables, constituted by not-essential elements Ba, Rb, Ti, Co, the use of S-QDA discriminated the lemons juices with 87.5% accuracy and 83.9% validation.

Background: The emergence of psychoactive designer drugs has significantly increased over the last few years. Customs officials are responsible for the control of products entering the European Union (EU) market. This control applies to chemicals in general, pharmaceutical products and medicines. Numerous products imported from non-EU countries, often declared as ‘bath salts’ or ‘fertilizers’, contain new psychoactive substance (NPS). Review: These are not necessarily controlled under international law, but may be subject to monitoring in agreement with EU legislation. This situation imposes substantial challenges, for example, for the maintenance of spectral libraries used for their detection by designated laboratories. The chemical identification of new substances, with the use of powerful instrumentation, and the time needed for detailed analysis and interpretation of the results, demands considerable commitment. The EU Joint Research Centre endeavors to provide scientific support to EU Customs laboratories to facilitate rapid identification and characterisation of seized samples. In addition to analysing known NPS, several new chemical entities have also been identified. Frequently, these belong to NPS classes already notified to the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) by the European Early-Warning System (EWS). Conclusion: The aim of this paper is to discuss the implementation of workflow mechanisms that are in place in order to facilitate the monitoring, communication and management of analytical data. The rapid dissemination of this information between control authorities strives to help protect EU citizens against the health risks posed by harmful substances.

Diseases of infection, of neurodegeneration (such as Alzheimer’s and Parkinson’s diseases), and of malignancy (cancers) have complex and varied causative factors. Modern drug discovery has the power to identify potential modulators for multiple targets from millions of compounds. Computational approaches allow the determination of the association of each compound with its target before chemical synthesis and biological testing is done. These approaches depend on the prior identification of clinically and biologically validated targets. This Perspective will focus on the molecular and computational approaches that underpin drug design by medicinal chemists to promote understanding and collaboration with clinical scientists.

Support was kindly provided by the EU COST Action CM1103. DA, KN, and JV kindly acknowledge national project number 172033 and OI1612039 supported by the Ministry of the Republic of Serbia. TDj and KY kindly acknowledge "Training in Neurodegeneration, Therapeutics, Intervention and Neurorepair" project number 608381 funded by Marie Skłodowska-Curie action, funding scheme: FP7-MC-ITN The diverse cerebral mechanisms implicated in CNS (Central Nervous System) diseases together with the heterogeneous and overlapping nature of phenotypes indicated that multitarget strategies may be appropriate for the improved treatment of complex brain diseases. Understanding how the neurotransmitter systems interact is also important in optimizing therapeutic strategies. Pharmacological intervention on one target will often influence another one, such as the well-established serotonin-dopamine interaction or the dopamine-glutamate interaction. It is now accepted that drug action can involve plural targets and that polypharmacological interaction with multiple targets, to address disease in more subtle and effective ways, is a key concept for development of novel drug candidates against complex CNS diseases. A multi-target therapeutic strategy for Alzheimer`s disease resulted in the development of very effective Multi-Target Designed Ligands (MTDL) that act on both the cholinergic and monoaminergic systems, and also retard the progression of neurodegeneration by inhibiting amyloid aggregation. Many compounds already in databases have been investigated as ligands for multiple targets in drug-discovery programs. A probabilistic method, the Parzen-Rosenblatt Window approach, was used to build a “predictor” model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. Based on all these findings, it is concluded that multipotent ligands targeting AChE/MAO-A/MAO-B and also D1-R/D2-R/5-HT2A-R/H3-R are promising novel drug candidates with improved efficacy and beneficial neuroleptic and procognitive activities in treatment of Alzheimer’s and related neurodegenerative diseases. Structural information for drug targets permits docking and virtual screening and exploration of the molecular determinants of binding, hence facilitating the design of multi-targeted drugs. The crystal structures and models of enzymes of the monoaminergic and cholinergic systems have been used to investigate the structural origins of target selectivity and to identify molecular determinants, in order to direct the development of novel multifunctional ligands. Publisher PDF

Seminář byl přínosný tím, že poskytl příležitost na mezinárodní úrovni prodiskutovat a vyměnit zkušenosti a trendy s předními odborníky na poli poskytování a rozvoje specializovaných akademických služeb.

Polymorphic transformations are known to occur as a result of many factors, one of the most prominent being recrystallisation from different solutions. Though other factors have been known to induce polymorphic change, these can include environmental factors and mechanical/physical stress. During many manufacturing processes mechanical stress such as milling or compression can induce polymorphic transformation, as well as environmental effects during storage such as changes in temperature or humidity. In this body of work the solid state transformations of two model polymorphic drugs, sulfamerazine and sulfathiazole, were studied. For this accurate analytical methods were developed for comprehensive polymorphic analysis. Previous studies have shown the effects of mechanical stress on the solid state chemistry of sulfamerazine. It has already been shown that compression during tabletting can cause transformation from sulfamerazine form I (FI) to form II (FII), that cryo-milling can generate amorphous content, and milling at room temperature can transform FI to FII. In this work, methods to prepare bulk FII from FI were reviewed. Both forms I & II of sulfamerazine were monitored during milling at room temperature and low temperatures, achieving the first complete transformation to sulfamerazine's amorphous phase (FA). FA produced from cryo-milling both FI and FII at different time intervals were compared to determine the optimal method to prepare (FA) for multivariate analysis. This optimal method resulted in the most stable amorphous phase, while taking the least amount of time to prepare. FI, FII and FA were used to prepare binary and ternary mixtures for chemometric models using XRPD, NIR and IR spectroscopy. This gave a novel means to analysis and monitors the solid state transformations of sulfamerazine observed during the room temperature milling and cryo-milling of FI and FII. The shelf-life of FA was also monitored when stored under vacuum at 4oC and room temperature using these calibration models. For the work with sulfathiazole, low content analysis of different solid sates was used to determine the limitations of a number of analytical techniques such as XRPD, NIR and IR spectroscopy. The analytical method that produced the most accurate calibrations was used in other studies. For the first time the amorphous phase of sulfathiazole was prepared via cryo-milling forms I and III. These produced purer samples of the amorphous phase when compared to samples prepared by the melt quench method. With a successful method to prepare pure samples of the amorphous phase, novel ternary studies containing the amorphous phase of sulfathiazole, and form I and form III were used to create ternary regression models from two different data sets, which were then compared. One ternary study was designed to focus on low content analysis, while the other was designed to focus on whole content analysis. The ternary system that gave the best results was then used to monitor the solid state transformations of forms I and III to the amorphous phase during cryo-milling.

Molecular descriptors capture diverse structural information of molecules and are a prerequisite for ligand-based similarity searching. In this study, we introduce topological matrix-based descriptors to virtual screening for hit discovery. We evaluated the usefulness of matrix-based descriptors in a retrospective setting and compared them with topological pharmacophore descriptors. Special attention was given to the influence of data pre-processing and the applied similarity metric on the virtual screening performance. Overall, the MB descriptors showed a competitive and complementary performance to other descriptors. A prospective screen of a commercial compound library led to the discovery of a novel natural-product-derived cyclooxygenase-2 inhibitor predicted to interact differently with the target protein compared to the query compound ibuprofen. The results of our study motivate the use of matrix-based descriptors for molecular similarity-based virtual screening and scaffold hopping.