Phenazine 5,10-dioxide analogues as drugs against acute myeloid leukaemia. -Preclinical documentation for lead selection

Postponed access: the file will be accessible after 2021-05-22Background: Acute Myeloid Leukaemia (AML) is a form of cancer that is associated with low survival rates, and where the current treatment is impaired by low tolerance and severe side-effects. Thus, novel treatments are needed to increase the life-expectancy of AMLpatients. The phenazine 5,10-dioxide compound, iodinin, has shown promising cytotoxic effects against AML cell lines in previous research. Iodinin itself has low solubility in aqueous media, and it was necessary to develop analogues with improved drug properties, which can be tested in animal models for toxicity and efficacy. Methods: The cytotoxicity of the analogues IM 5, IM 20, IM 56 and IM 69 was investigated by performing viability assays on OCI-AML-3 and MOLM-13 AML cell lines and comparing the results to previously obtained results for the normal cell lines rat kidney epithelial (NRK) and cardiac myeloblast (H9c2). The generation of reactive oxygen species (ROS), by a fluorescent reporter (DCF), was also investigated for MOLM-13 and H9c2 cells. Furthermore, key factors in ROS signalling were investigated by western blot. The physiochemical properties were studied by a screening assay for membrane permeability and in silicoprediction of properties important for permeability and biodistribution and linked to the biological activity of the analogues. Results: The analogue IM 56 showed increased cytotoxicity towards AML cell lines compared to the parent compound IM 5. It was also less toxic towards normal cell lines compared to the most frequently used AML drug, the anthracycline Daunorubicin. The difference in biological activities of the analogues is supported by their difference in membrane permeability. The analogues increase the generation of ROS in MOLM-13 cells. Except for the analogue IM 20, no such increase could be detected in H9c2 cells. Conclusion: The analogue IM 56 was chosen for further drug development, due to its enhanced effect against AML cell lines relative to normal cell lines. It increases cell death in MOLM-13 cells, most likely due to generation of ROS. IM 56 is thus a promising candidate for in vivo pre-clinical studies.Masteroppgåve i FarmasiFARM399/05HMATF-FAR

Reading method of the chemical formula for the support technology of visual disabilities using computational chemistry.

富山大学・富生命博甲第84号・上條治夫・2016/03/23富山大学201

Identification of New Inhibitors with Potential Antitumor Activity from Polypeptide Structures via Hierarchical Virtual Screening

We gratefully acknowledge the support provided by the Graduate Program in Pharmaceutical Innovation—Federal University of Amapá, Laboratory of Modeling and Computational Chemistry—Federal University of Amapá (UNIFAP-Macapá-Brazil), Computational Laboratory of Pharmaceutical Chemistry—University of Sao Paulo (USP-Ribeirão Preto-Brazil) and Department of Pharmaceutical and Organic Chemistry—Institute of Biosanitary Research ibs.GRANADA—University of Granada (UGR-Granada-Spain) for computational and financial support.Leukemias are neoplasms that affect hematopoietic cells, which are developed by genetic alterations (mutations) that lead to the loss of proliferation control mechanisms (maturation and/or cell death). The α4β1 integrin receptor is a therapeutic target for inflammation, autoimmune diseases and lymphoid tumors. This study was carried out to search through the antagonists-based virtual screening for α4β1 receptor. Initially, seventeen (17) structures were selected (based on the inhibitory activity values, IC50) and the structure with the best value was chosen as the pivot. The pharmacophoric pattern was determined from the online PharmaGist server and resulted in a model of score value equal to 97.940 with 15 pharmacophoric characteristics that were statistically evaluated via Pearson correlations, principal component analysis (PCA) and hierarchical clustering analysis (HCA). A refined model generated four pharmacophoric hypotheses totaling 1.478 structures set of Zinc_database. After, the pharmacokinetic, toxicological and biological activity predictions were realized comparing with pivot structure that resulted in five (ZINC72088291, ZINC68842860, ZINC14365931, ZINC09588345 and ZINC91247798) structures with optimal in silico predictions. Therefore, future studies are needed to confirm antitumor potential activity of molecules selected this work with in vitro and in vivo assays

Welche Strukturformeln sollte der Mediziner bzw. Zahnmediziner für die Physikumsprüfung beherrschen?

Studierende der Medizin und Zahnmedizin stehen bei der Vorbereitung auf das Physikum vor der Frage, ob und welche chemischen Strukturformeln für das Prü-fungsfach Biochemie/Molekularbiologie zu lernen sind. Dazu gibt der Gegenstands-katalog der Institution für das schriftliche Examen (IMPP) nur sehr vage Angaben. Auch die Hochschullehrer vor Ort legen sich meist nicht fest. Außerdem haben die Studierenden den subjektiven Eindruck, dass die Meinungen ihrer Dozenten stark voneinander abweichen. Hilfe kommt auch nicht von den sonst zuverlässigen Lehr-büchern, die meist von Formeln überquellen, aber es unterlassen, Angaben dazu zu machen, welche Formeln prüfungsrelevant und deshalb zu lernen sind. Auch im Internet als einer zusätzlichen Informationsquelle mit wachsender Bedeutung in der Lehre finden sich keine Hinweise zur Beantwortung der Frage. Das Ziel der Dissertation war es deshalb, eine begründete Antwort auf die Frage zu geben, welche chemischen Strukturformeln zu lernen sind. Dazu war die geschilderte Situation zu analysieren und mit Daten zu unterlegen, die auf einer systematischen Befragung deutscher Hochschullehrer der Biochemie und Molekularbiologie beruht. Ausgehend von einem Formelkatalog, den Prof. Koolman (Physiologisch-Chemisches Institut der Universität Marburg) seinen Studierenden empfiehlt, wurde eine Umfrage bei 98 Hochschullehrern biochemisch/molekularbiologischer Institute an 36 Hochschulen durchgeführt, die Mediziner ausbilden. Von den angeschrieben Hochschullehrern antworteten 26. Die Antworten spiegelten die große Heterogenität in der Auffassung wieder, was ein Studierender an Formeln zu lernen habe. Es gibt gegenwärtig also keinen Konsens unter den Prüfern, welche Strukturformeln ein Studierender zu lernen hat. Da der versandte Formelkatalog sich in etwa in der Mitte des Antwortspektrums befand, wurde im nächsten Schritt der Dissertation eine multimediale Lehreinheit entwickelt, die den Lernstoff (chemische Strukturformeln für Mediziner und Zahn-mediziner) aufbereitet. Dabei wurden einschlägige didaktische Empfehlungen für das eLearning berücksichtigt. Die Lehreinheit wurde für die Lernplattform k-MED ge-schrieben, um ihr einen möglichst breiten Einsatz an vielen Hochschulen zu sichern. In einem zweiten Anlauf wurden erneut diejenigen Hochschullehrer angeschrieben, die bereits auf die erste Anfrage geantwortet hatten. Ihnen wurde die Lerneinheit und ein detaillierter Fragebogen vorgelegt. Die Einschätzung der eLerneinheit war über-wiegend zustimmend. Allerdings ist die Rücklaufquote zu gering, um das Ergebnis als statistisch signifikant anzusehen. Es lässt sich folgern, dass die Ausgangsfrage zwar den Studierenden, nicht aber den Lehrenden auf den Nägeln brennt. Die Frage nach den zu lernenden Formeln hat mit der vorgelegten eLerneinheit eine Antwort erfahren. Ob diese Antwort damit die Bedürfnisse der Studierenden nach einer verlässlichen Vorgabe erfüllt, wird eine zukünftige Befragung der Nutzer he-rausfinden müssen. Langfristig wäre es wünschenswert, wenn sich die Dozenten der Biochemie und Molekularbiologie – etwa auf der Ebene ihres Verbandes (Gesell-schaft deutscher Biochemiker und Molekularbiologen, GBM) – auf einen Katalog chemischer Formeln einigen könnten, der den Prüfungen zugrunde liegt

Discovery and Optimization of Pyrrolopyrimidine Derivatives as Selective Disruptors of the Perinucleolar Compartment, a Marker of Tumor Progression toward Metastasis

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Medicinal Chemistry, Copyright © 2022 American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acs.jmedchem.2c00204.The perinucleolar compartment (PNC) is a dynamic subnuclear body found at the periphery of the nucleolus. The PNC is enriched with RNA transcripts and RNA-binding proteins, reflecting different states of genome organization. PNC prevalence positively correlates with cancer progression and metastatic capacity, making it a useful marker for metastatic cancer progression. A high-throughput, high-content assay was developed to identify novel small molecules that selectively reduce PNC prevalence in cancer cells. We identified and further optimized a pyrrolopyrimidine series able to reduce PNC prevalence in PC3M cancer cells at submicromolar concentrations without affecting cell viability. Structure–activity relationship exploration of the structural elements necessary for activity resulted in the discovery of several potent compounds. Analysis of in vitro drug-like properties led to the discovery of the bioavailable analogue, metarrestin, which has shown potent antimetastatic activity with improved survival in rodent models and is currently being evaluated in a first-in-human phase 1 clinical trial

Automatic Analysis and Validation of the Chemical Literature

ThesisMethods to automatically extract and validate data from the chemical literature in legacy formats to machine-understandable forms are examined. The work focuses of three types of data: analytical data reported in articles, computational chemistry output files and crystallographic information files (CIFs). It is shown that machines are capable of reading and extracting analytical data from the current legacy formats with high recall and precision. Regular expressions cannot identify chemical names with high precision or recall but non-deterministic methods perform significantly better. The lack of machine-understandable connection tables in the literature has been identified as the major issue preventing molecule-based data-driven science being performed in the area. The extraction of data from computational chemistry output files using parser-like approaches is shown to be not generally possible although such methods work well for input files. A hierarchical regular expression based approach can parse > 99:9% of the output files correctly although significant human input is required to prepare the templates. CIFs may be parsed with extremely high recall and precision, contain connection tables and the data is of high quality. The comparison of bond lengths calculated by two computational chemistry programs show good agreement in general but structures containing specific moieties cause discrepancies. An initial protocol for the high-throughput geometry optimisation of molecules extracted from the CIFs is presented and the refinement of this protocol is discussed. Differences in bond length between calculated and experimentally determined values from the CIFs of less than 0.03 Angstrom are shown to be expected by random error. The final protocol is used to find high-quality structures from crystallography which can be reused for further science.Unilever Centre for Molecular Science Informatic

Crystal isostructurality and X-ray diffraction studies of cyclodextrin inclusion compounds

Includes bibliographical references.The first part of this dissertation is an update on the isostructurality method of PXRD analysis (lsoPXRD), the last update having been published in 2001 The scope of the isostructurality part of this dissertation includes organic inclusion complexes of all three natural cyclodextrins (a-

Antimicrobial activity of a library of thioxanthones and their potential as efflux pump inhibitors

The overexpression of efflux pumps is one of the causes of multidrug resistance, which leads to the inefficacy of drugs. This plays a pivotal role in antimicrobial resistance, and the most notable pumps are the AcrAB-TolC system (AcrB belongs to the resistance-nodulation-division family) and the NorA, from the major facilitator superfamily. In bacteria, these structures can also favor virulence and adaptation mechanisms, such as quorum-sensing and the formation of biofilm. In this study, the design and synthesis of a library of thioxanthones as potential efflux pump inhib-itors are described. The thioxanthone derivatives were investigated for their antibacterial activity and inhibition of efflux pumps, biofilm formation, and quorum-sensing. The compounds were also studied for their potential to interact with P-glycoprotein (P-gp, ABCB1), an efflux pump present in mammalian cells, and for their cytotoxicity in both mouse fibroblasts and human Caco-2 cells. The results concerning the real-time ethidium bromide accumulation may suggest a potential bacterial efflux pump inhibition, which has not yet been reported for thioxanthones. Moreover, in vitro studies in human cells demonstrated a lack of cytotoxicity for concentrations up to 20 µM in Caco-2 cells, with some derivatives also showing potential for P-gp modulation.This research was supported by national funds through FCT (Foundation for Science and Technology) within the scope of UIDB/04423/2020, UIDP/04423/2020 (Group of Natural Products and Medicinal Chemistry-CIIMAR), and under the project PTDC/SAU-PUB/28736/2017 (reference POCI-01–0145-FEDER-028736), co-financed by COMPETE 2020, Portugal 2020 and the European Union through the ERDF and by FCT through national funds and structured program of R&D&I ATLANTIDA (NORTE-01-0145-FEDER-000040), supported by NORTE2020, through ERDF, and CHIRALBIO ACTIVE-PI-3RL-IINFACTS-2019

MIA-QSAR modeling of inhibitors actylcholinesterase

Orientador: Roberto Rittner NetoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Ciências MédicasResumo: O presente trabalho trata de um estudo sobre compostos que se comportam como inibidores da acetilcolinesterase, uma importante enzima do processo de cognição. A acetilcolinesterase atua na hidrólise da acetilcolina, responsável pela comunicação entre os neurônios. Uma das modalidades para o design racional de fármacos é a estimativa de propriedades biológicas de novas moléculas utilizando métodos computacionais. Análise quantitativa entre estrutura química e atividade biológica (QSAR) é uma dessas técnicas. No presente trabalho, análise multivariada de imagens aplicada em QSAR (MIA-QSAR) foi utilizada para se construírem modelos QSAR preditivos para uma série congênere de carbamatos com atividade anticolinesterásica. Os bons resultados estatísticos da modelagem credenciaram o modelo MIA-QSAR construído a predizer a atividade biológica de alguns novos derivados, potencialmente úteis para o tratamento do Mal de AlzheimerAbstract: The present work describes the study of some compounds which act as acetylcholinesterase inhibitors a very important enzyme in the cognitive process. zAcetylcholinesterase is responsible by the hydrolysis of acetylcholine, which accounts for the communication among the neurons. One of the approaches for the rational pharmaceuticals design is the estimation of the biological properties of new molecules using computational methods. The quantitative analysis between chemical structure and biological activity (QSAR) is one of these techniques. In the present work, the multivariate analysis of images applied in QSAR (MIA-QSAR) was employed for building predictable QSAR models for a congenial series of carbamates which exhibit anticholinesterase activity. The significant statistical results from this treatment enabled the MIA-QSAR model thus obtained to reliably predict the biological activity of some new derivatives, as potentially useful for the Alzheimer Disease treatmentMestradoCiencias BiomedicasMestra em Ciências Médica