Design, synthesis and experimental validation of novel potential chemopreventive agents using random forest and support vector machine binary classifiers

Compared to the current knowledge on cancer chemotherapeutic agents, only limited information is available on the ability of organic compounds, such as drugs and/or natural products, to prevent or delay the onset of cancer. In order to evaluate chemical chemopreventive potentials and design novel chemopreventive agents with low to no toxicity, we developed predictive computational models for chemopreventive agents in this study. First, we curated a database containing over 400 organic compounds with known chemoprevention activities. Based on this database, various random forest and support vector machine binary classifiers were developed. All of the resulting models were validated by cross validation procedures. Then, the validated models were applied to virtually screen a chemical library containing around 23,000 natural products and derivatives. We selected a list of 148 novel chemopreventive compounds based on the consensus prediction of all validated models. We further analyzed the predicted active compounds by their ease of organic synthesis. Finally, 18 compounds were synthesized and experimentally validated for their chemopreventive activity. The experimental validation results paralleled the cross validation results, demonstrating the utility of the developed models. The predictive models developed in this study can be applied to virtually screen other chemical libraries to identify novel lead compounds for the chemo-prevention of cancers

The design, synthesis and evaluation of Nrf2-Keap1 PPI inhibitors: a modular, virtual screening-led approach

Nrf2 (nuclear factor erythroid 2-related factor 2) is a cap’n’collar bZIP transcription factor and is the main activator of the transcription of over 100 genes that play roles in responses to oxidative stress and detoxifying xenobiotics. The main control of Nrf2 levels is exercised by Keap1 (Kelchlike ECH-associated protein 1) which facilitates the ubiquitination of Nrf2 and therefore its degradation. Keap1 is oxidation-sensitive and upon exposure to oxidants, it changes its conformation and binds Nrf2 tightly. Consequently, de novo-synthesised Nrf2 can accumulate. Following its discovery, Nrf2 received most attention in relation to cancer. Over the time, however, its implication in other pathologies have been more and more acknowledged, namely in inflammation and most importantly in neurodegenerative diseases. Especially Parkinson’s disease (PD), which is the second most common neurodegenerative disease, caused by the progressive loss of dopaminergic neurons in the substantia nigra, has been linked to oxidative stress. The role Nrf2 plays has been demonstrated in animal models of α-synuclein aggregation or chemically induced parkinsonism, where an increase in Nrf2 expression provided neuroprotection and a slowing of disease progression. Therefore, the inhibition of Keap1- mediated Nrf2 degradation presents a promising strategy for the mechanistic study and the therapy of PD. Several structures showing high potency towards Keap1 inhibition have been described, with activities in the nanomolar range. However, these compounds are large, or hydrophilic and charged. In order to develop new scaffolds, extensive virtual screening assays have been conducted which resulted in hits with promising molecular scaffolds. At the same time, chemical modifications on a known triazole structure have been performed in order to elucidate structure-activity relationships. In this thesis, the molecular modelling lead, as well the synthetic approach to both project components are described. Finally, the results of a competitive fluorescence polarisation (FP) assay for the second set of compounds are presented

Essential oil phytocomplex activity, a review with a focus on multivariate analysis for a network pharmacology-informed phytogenomic approach

Thanks to omic disciplines and a systems biology approach, the study of essential oils and phytocomplexes has been lately rolling on a faster track. While metabolomic fingerprinting can provide an effective strategy to characterize essential oil contents, network pharmacology is revealing itself as an adequate, holistic platform to study the collective effects of herbal products and their multi-component and multi-target mediated mechanisms. Multivariate analysis can be applied to analyze the effects of essential oils, possibly overcoming the reductionist limits of bioactivity-guided fractionation and purification of single components. Thanks to the fast evolution of bioinformatics and database availability, disease-target networks relevant to a growing number of phytocomplexes are being developed. With the same potential actionability of pharmacogenomic data, phytogenomics could be performed based on relevant disease-target networks to inform and personalize phytocomplex therapeutic application

Multi-Targeting Bioactive Compounds Extracted from Essential Oils as Kinase Inhibitors

Essential oils (EOs) are popular in aromatherapy, a branch of alternative medicine that claims their curative effects. Moreover, several studies reported EOs as potential anti-cancer agents by inducing apoptosis in different cancer cell models. In this study, we have considered EOs as a potential resource of new kinase inhibitors with a polypharmacological profile. On the other hand, computational methods offer the possibility to predict the theoretical activity profile of ligands, discovering dangerous off-targets and/or synergistic effects due to the potential multi-target action. With this aim, we performed a Structure-Based Virtual Screening (SBVS) against X-ray models of several protein kinases selected from the Protein Data Bank (PDB) by using a chemoinformatics database of EOs. By evaluating theoretical binding affinity, 13 molecules were detected among EOs as new potential kinase inhibitors with a multi-target profile. The two compounds with higher percentages in the EOs were studied more in depth by means Induced Fit Docking (IFD) protocol, in order to better predict their binding modes taking into account also structural changes in the receptor. Finally, given its good binding affinity towards five different kinases, cinnamyl cinnamate was biologically tested on different cell lines with the aim to verify the antiproliferative activity. Thus, this work represents a starting point for the optimization of the most promising EOs structure as kinase inhibitors with multi-target feature

Synthesis and biological evaluation of fluorinated 1,5-diarylpyrrole-3-alkoxyethyl ether derivatives as selective COX-2 inhibitors endowed with anti-inflammatory activity

A series of substituted 1,5-diarylpyrrole-3-alkoxyethyl ethers were previously synthesized and the potential anti-inflammatory and antinociceptive activities of these compounds were evaluated in vivo. The compounds displayed a very good activity against both carrageenan-induced hyperalgesia and oedema in the rat paw test. Therefore, in a very preliminary test, compounds (8a,b) showed antiproliferative activity in the HaCaT (aneuploid immortal keratinocyte from adult human skin) cell models. On these basis, our research continued with the synthesis of fluorinated derivatives (8c,d, 9b-d, and 10b-d) with the aim of improving the pharmacokinetic profile of the previous active compounds. Substitution of a hydrogen atom by a fluorine atom may change the conformational preferences of the molecules due to stereoelectronic effects and also fluorine atom may be able to exert the metabolic obstruction reducing the "first-pass effect". Compound 10b exhibited a prominent in vivo anti-inflammatory and antinociceptive activities, in addition its antiproliferative power in an in vitro model of human skin cancer is herein described

GRID and docking analyses reveal a molecular basis for flavonoid inhibition of src-family kinase activity

Flavonoids reduce cardiovascular disease risk through anti-inflammatory, anti-coagulant and anti-platelet actions. One key flavonoid inhibitory mechanism is blocking kinase activity that drives these processes. Flavonoids attenuate activities of kinases including phosphoinositide-3-kinase (PI3K), Fyn, Lyn, Src, Syk, PKC, PIM1/2, ERK, JNK, and PKA. X-ray crystallographic analyses of kinase-flavonoid complexes show that flavonoid ring systems and their hydroxyl substitutions are important structural features for their binding to kinases. A clearer understanding of structural interactions of flavonoids with kinases is necessary to allow construction of more potent and selective counterparts. We examined flavonoid (quercetin, apigenin and catechin) interactions with Src-family kinases (Lyn, Fyn and Hck) applying the Sybyl docking algorithm and GRID. A homology model (Lyn) was used in our analyses to demonstrate that high quality predicted kinase structures are suitable for flavonoid computational studies. Our docking results revealed potential hydrogen bond contacts between flavonoid hydroxyls and kinase catalytic site residues. Identification of plausible contacts indicated that quercetin formed the most energetically stable interactions, apigenin lacked hydroxyl groups necessary for important contacts, and the non-planar structure of catechin could not support predicted hydrogen bonding patterns. GRID analysis using a hydroxyl functional group supported docking results. Based on these findings, we predicted that quercetin would inhibit activities of Src-family kinases with greater potency than apigenin and catechin. We validated this prediction using in vitro kinase assays. We conclude that our study can be used as a basis to construct virtual flavonoid interaction libraries to guide drug discovery using these compounds as molecular templates

Validation of digital microscopy in the histopathological diagnoses of oral diseases

Orientador: Alan Roger dos Santos SilvaDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Odontologia de PiracicabaResumo: A microscopia digital (MD) expandiu-se nos últimos anos em ambientes educacionais e profissionais para interconsulta, telepatologia, armazenamento e relatórios anatomopatológicos, colocando sistemas whole slide imaging (WSI) na posição privilegiada de dispositivos inovadores para interpretação de diagnósticos primários, aplicação previamente concebida com receio. Esta é uma consequência direta da falta de regulamentação desses dispositivos. É necessário reunir evidências sobre o desempenho da MD, para estabelecer se esta tecnologia pode ser usada para fornecer diagnóstico primário com segurança. O primeiro capítulo apresentado no presente estudo teve como objetivo fornecer informações sobre o desempenho de sistemas WSI, avaliando concordância intra-observador como melhor evidência. Uma busca eletrônica nas bases Scopus, MEDLINE/PubMed e Embase foi conduzida. As características metodológicas, a concordância entre a microscopia convencional (MC) e a MD e as razões para a ocorrência de diagnósticos discordantes foram analisadas. Um total de 13 artigos foram incluídos. As concordâncias intra-observadores variaram de 90% a 98,3% (intervalo de confiança de ? = 0,8-0,98). A dificuldade do caso foi o principal motivo de discordância (46,15%), seguido por dificuldades na identificação de microrganismos (15,38%). 58,84% enfatizam que o desempenho do método digital não está relacionado com a ocorrência de discordâncias. Apenas 25% das discordâncias tinham diagnósticos preferenciais por WSI. 15,38% dos estudos incluídos apresentaram alto risco de viés devido à seleção da amostra e 15,38% devido à ausência de especificação de um limiar de positividade. Todos os estudos foram classificados como baixa risco em relação à aplicabilidade. Esta revisão sistemática demonstrou uma alta concordância entre os diagnósticos por WSI e CLM. É possível confirmar que essa tecnologia pode ser usada para fornecer diagnóstico primário em várias especialidades da patologia humana. O segundo capítulo apresentado neste estudo teve como objetivo validar um sistema WSI para fins de diagnóstico de doenças bucais, utilizando a variabilidade intraobservador como a principal forma de análise. Setenta (n = 70) lâminas de vidro coradas em H&E de biópsias orais foram escaneadas pelo Aperio Digital Pathology System (Aperio Technologies Inc., Vista, CA, EUA) em uma magnificação de 20x. Dois patologistas experientes analisaram cegamente todos os casos com MLC e, após 3 meses de washout, com WSI. Informações clínicas foram fornecidas em ambas as análises. A concordância intraobservador entre os métodos foi de 97% para ambos os patologistas. Entre os casos discordantes, a maioria dos diagnósticos preferidos foi por MLC. Ambos os patologistas tiveram as mesmas discordâncias em diferentes casos. A dificuldade de alguns casos, que possibilitou interpretações controversas, e a pouca quantidade de tecido para análise foram consideradas razões principais de desacordo em detrimento dos métodos de diagnóstico. O valor de tempo (mediana) foi maior apenas com MLC para um patologista e, a melhoria do tempo com WSI está relacionada com o melhor fluxo de trabalho provido pelo sistema WSI. Os valores máximos de tempo ocorreram em casos discordantes e em outros casos considerados difíceis. Este estudo fornece evidências originais de um alto desempenho do sistema WSI para fins de diagnóstico na prática clínica, patologia de rotina e diagnóstico primário no campo da patologia oralAbstract: Digital microscopy (DM) has expanded recently in professional settings for interconsultations, telepathology, storage and routine reporting, what puts whole-slide imaging (WSI) systems in the privileged position of innovative devices for interpretation of primary diagnoses, application previously conceived with fear. This is a direct consequence of the lack of regulation of these devices. It is necessary to assemble evidence regarding the performance of the DM, in order to establish whether this technology can be used to provide primary diagnosis. The first chapter presented in this study aimed to provide information regarding the performance of whole slide imaging (WSI) devices, evaluating intraobserver agreement as the best evidence to elucidate whether digital microscopy (DM) is reliable for primary diagnostic purposes. Scopus, MEDLINE/PubMed and Embase were searched electronically. The methodological characteristics, the intraobserver agreement between conventional light microscopy (CLM) and WSI and the reasons for discordant diagnoses were analysed. Thirteen articles were included. The intraobserver agreements showed an excellent concordance, with values ranging from 90% to 98,3%, (? coef?cient range 0.8¿0.98). Challenging cases were the main reasons for disagreements (46.15%) followed by difficulties in the identification of microorganisms (15.38%). 58,84% emphasize that the performance of the digital method is not related to the occurrence of disagreements. Only 25% of discordant cases had preferred WSI diagnosis. 15.38% presented high risk of bias due to unclear sample selection, and 15.38% due to the absence of specification of a threshold. Regarding to applicability, all studies were classified as a low concern. This systematic review showed a high concordance between diagnoses achieved by using WSI and CLM. These studies were also optimally designed to validate WSI for general clinical use and, most importantly, it is possible to confirm that this technology can be used to provide primary diagnosis in several specialties of human pathology.Second chapter of this study intended to validate a WSI system for diagnostic purposes of oral diseases, using the intraobserver variability as the primary form of analysis. Seventy (n = 70) H&E-stained glass slides of oral biopsies were scanned by the Aperio Digital Pathology System (Aperio Technologies Inc., Vista, CA, USA) at a magnification of 20x. Two experienced pathologists blindly analysed all cases with CLM and, after 3 months washout, with WSI. Clinical information was provided in both analyses. The intraobserver agreement between CLM and WSI system diagnoses was 97% for both pathologists. Among discordances, the majority of preferred diagnoses were by CLM. Both pathologists had the same discordances in different cases. Difficult cases, which allowed controversial interpretations, and the lack of tissue for analyses, were considered main reasons for disagreement rather than the diagnostic methods. Median time was higher only in CLM for one pathologist and the improvement of time in WSI was related to better workflow of WSI. Time outliers occurred in discordant cases and other difficult cases. This study provides original evidence for the high-performance of WSI for diagnostic purposes in clinical practice, routine pathology and primary diagnosis in the field of oral pathologyMestradoEstomatologiaMestra em Estomatopatologia33003033009P4CAPE

Cheminformatic Approach for Deconvolution of Active Compounds in a Complex Mixture - phytoserms in Licorice

ABSTRACT After the validation of our in silico models by using the previous knowledge in this area the alerting phytochemicals from two Glycyrrhiza species (G. glabra and G. uralensis) were clustered. Exhaustive computational mining of licorice metabolome against selected endocrinal and metabolic targets led to the discovery of a unique class of compounds which belong to the dihydrostilbenoids (DHS) class appended with prenyl groups at various positions. To the best of our knowledge this interesting group of compounds has not been studied for their estrogenic activities or PXR activation. In addition some of the bis-prenylated DHS have been reported to be present only in G. uralensis. Another aspect of the current project was to predict the phase I primary metabolites of compounds found in both species of Glycyrrhiza and assess them with computational tools to predict their binding potential against both isoforms of hERs or drug metabolizing enzymes such as (CYP) inhibition models. Our investigations revealed estrogenic character for most of the predicted metabolites and have confirmed earlier reports of potential CYP3A4 and CYP1A2 inhibition. Compilation of such data is essential to gain a better understanding of the efficacy/safety of licorice extracts used in various botanical formularies. This approach with the involved cheminformatic tools has proven effective to yield rich information to support our understanding of traditional practices. It also can expand the role of botanical drugs for introducing new chemical entities (NCEs) and/or uncovering their liabilities at early stages. In this work we endeavored to comprehend the mechanism associated with the efficacy and safety of components reported in the licorice plant. We utilized smart screening techniques such as cheminformatics tools to reveal the high number of secondary metabolites produced by licorice which are capable of interfering with the human Estrogen Receptors (hERs) and/or PXR or other vital cytochrome P450 enzymes. The genus Glycyrrhiza encompasses several species exhibiting complex structural diversity of secondary metabolites and hence biological activities. The intricate nature of botanical remedies such as licorice rendered them obsolete for scientific research or medical industry. Understanding and finding the mechanisms of efficacy or safety for a plant-based therapy is very challenging yet it remains crucial and warranted. The licorice plant is known to have Selective Estrogen Receptor Modulatory effects (SERMs) with a spectrum of estrogenic and anti-estrogenic activities attributed to women’s health. On the contrary licorice extract was shown to induce pregnane xenobiotic receptor (PXR) which may manifest as a potential route for deleterious effects such as herb-drug interaction (HDI). While many studies attributed these divergent activities to a few classes of compounds such as liquiritigenin (a weak estrogenic SERM) or glycyrrhizin (weak PXR agonist) no attempt was made to characterize the complete set of compounds responsible for these divergent activities. A plethora of licorice components is undermined which might have the potential to be developed into novel phytoSERMS or to trigger undesirable adverse effects by altering drug metabolizing enzymes and thus pharmacokinetics. Thus we have ventured to synthesize a set of constitutional isomers of stilbenoids and DHS (archetypal of those found in licorice) with different prenylation patterns. Sixteen constitutional isomers of stilbenoids (M2-M10) and DHS (M12-M18) were successfully synthesized of which six of them (M8 M9 M14 M15 M17 and M18) were synthesized for the first time to be further tested and validated with cell-based methods for their estrogenic activities. We have unveiled a novel class of compounds which possess a strong PXR activation. These results which were in accord with the in silico prediction were observed for multiple synthesized prenylated stilbenoid and DHS by the luciferase reporter gene assay at µM concentrations. Moreover this activation was further validated by the six-fold increase in mRNA expression of Cytochrome P450 3A4 (CYP3A4) where three representative compounds (M7 M10 and M15) exceeded the activation fold of the positive control

Correlation between cell line chemosensitivity and protein expression pattern as new approach for the design of targeted anticancer small molecules

BACKGROUND AND RATIONALE: Over the past few decades, several databases with a significant amount of biological data related to cancer cells and anticancer agents (e.g.: National Cancer Institute database, NCI; Cancer Cell Line Encyclopedia, CCLE; Genomic and Drug Sensitivity in Cancer portal, GDSC) have been developed. The huge amount of heterogeneous biological data extractable from these databanks (among all, drug response and protein expression) provides a real foundation for predictive cancer chemogenomics, which aims to investigate the relationships between genomic traits and the response of cancer cells to drug treatment with the aim to identify novel therapeutic molecules and targets. In very recent times many computational and statistical approaches have been proposed to integrate and correlate these heterogeneous biological data sequences (protein expression – drug response), with the aim to assign the putative mechanism of action of anticancer small molecules with unknown biological target/s. The main limitation of all these computational methods is the need for experimental drug response data (after screening data). From this point of view, the possibility to predict in silico the antiproliferative activity of new/untested small molecules against specific cell lines, could enable correlations to be found between the predicted drug response and protein expression of the desired target from the very earliest stages of research. Such an innovative approach could allow to select the compounds with molecular mechanisms that are more likely to be connected with the target of interest preliminary to the in vitro assays, which would be a critical aid in the design of new targeted anticancer agents. RESULTS: In the present study, we aimed to develop a new innovative computational protocol based on the correlation of drug activity and protein expression data to support the discovery of new targeted anticancer agents. Compared with the approaches reported in the literature, the main novelty of the proposed protocol was represented by the use of predicted antiproliferative activity data, instead of experimental ones. To this aim, in the first phase of the research the new in silico Antiproliferative Activity Predictor (AAP) tool able to predict the anticancer activity (expressed as GI50) of new/untested small molecules against the NCI-60 panel was developed. The ligand-based tool, which took the advantages of the consolidated expertise of the research group in the manipulation of molecular descriptors, was adequately validated and the reliability of the prediction was further confirmed by the analysis of an in-house database and subsequent evaluation of a set of molecules selected by the NCI for the one-dose/five-doses antiproliferative assays. In the second part of the study, a new computational method to correlate drug activity data and protein expression pattern data was proposed and evaluated by analysing several case studies of targeted drugs tested by NCI, confirming the reliability of the proposed method for the biological data analysis. In the last part of the project the proposed correlation approach was applied to design new small molecules as selective inhibitors of Cdc25 phosphatase, a well-known protein involved in carcinogenic processes. By means of this innovative approach, integrated with other classical ligand/structures-based techniques, it was possible to screen a large database of molecular structures, and to select the ones with optimal relationship with the focused target. In vitro antiproliferative and enzymatic inhibition assays of the selected compounds led to the identification of new structurally heterogeneous inhibitors of Cdc25 proteins and confirmed the results of the in silico analysis. CONCLUSIONS: Collectively, the obtained results showed that the correlation between protein expression pattern and chemosensitivity is an innovative, alternative, and effective method to identify new modulators for the selected targets. In contrast to traditional in silico methods, the proposed protocol allows for the selection of molecular structures with heterogeneous scaffolds, which are not strictly related to the binding sites and with chemical-physical features that may be more suitable for all the pathways involved in the overall mechanism. The biological assays further corroborate the robustness and the reliability of this new approach and encourage its application in the anticancer targeted drug discovery field