Hantzsch-Type Dihydropyridin es and Biginelli-Type Tetra- hydropyrimidines: A Review of their Chemotherapeutic Activities

Years after the first report on 1,4-dihydropyridines (1,4-DHPs) and 1,2,3,4-tetrahydropyrimidines (1,2,3,4-THPMs) appeared, they are revisited as plausible therapeutic agents. This is mainly due to the convenient methods that exist for their synthesis and the diverse pharmacologic properties that these scaffolds present. 1,4-Dihydropyridines and 1,2,3,4-tetrahydropyrimidines are usually regarded as analogous in several aspects. They are both prepared in multi-component reactions using very similar starting materials and synthesis protocols. This leads to common structural features between 1,4-DHPs and 1,2,3,4-THPMs, as well several related biological effects. For example, they share many pharmacological features such as analgesic, anti-tumor, antioxidant, anti-inflammatory, antitubercular, antibacterial, cardiovascular and adrenoceptor blocking activities. Numerous reviews have been devoted to the chemistry and cardiovascular effects of these compounds. However, the lack of a comprehensive literature overview on the chemotherapeutic ability of these scaffolds is behind the present attempt to provide a detailed survey of 1,4-DHPs and 1,2,3,4-THPMs and their structural features as chemotherapeutic agents

Fighting the disagreement in Explainable Machine Learning with consensus

Machine learning (ML) models are often valued by the accuracy of their predictions. However, in some areas of science, the inner workings of models are as relevant as their accuracy. To understand how ML models work internally, the use of interpretability algorithms is the preferred option. Unfortunately, despite the diversity of algorithms available, they often disagree in explaining a model, leading to contradictory explanations. To cope with this issue, consensus functions can be applied once the models have been explained. Nevertheless, the problem is not completely solved because the final result will depend on the selected consensus function and other factors. In this paper, six consensus functions have been evaluated for the explanation of five ML models. The models were previously trained on four synthetic datasets whose internal rules were known in advance. The models were then explained with model-agnostic local and global interpretability algorithms. Finally, consensus was calculated with six different functions, including one developed by the authors. The results demonstrated that the proposed function is fairer than the others and provides more consistent and accurate explanations.Comment: 21 pages, 7 figure

1-(2-Chlorobenzyloxy)-3-[1,2,3]triazol-1-yl-propan-2-ol Derivatives: Synthesis, Characterization, and DFT-Based Descriptors Analysis

A novel series of 1-(2-chlorobenzyloxy)-3-[1,2,3]triazol-1-yl-propan-2-ol derivatives was designed and synthesized using copper catalyzed alkyne-azide cycloaddition in the key step. Theoretical investigation of molecular and electronic properties by means of global and local reactivity indexes of the synthetized compounds was carried out, using DFT (Density Functional Theory) at PBEPBE/6-31++G∗∗ levelCONACY

Evaluation of the anti-diabetic activity of some common herbs and spices : providing new insights with inverse virtual screening

Culinary herbs and spices are widely used as a traditional medicine in the treatment of diabetes and its complications, and there are several scientific studies in the literature supporting the use of these medicinal plants. However, there is often a lack of knowledge on the bioactive compounds of these herbs and spices and their mechanisms of action. The aim of this study was to use inverse virtual screening to provide insights into the bioactive compounds of common herbs and spices, and their potential molecular mechanisms of action in the treatment of diabetes. In this study, a library of over 2300 compounds derived from 30 common herbs and spices were screened in silico with the DIA-DB web server against 18 known diabetes drug targets. Over 900 compounds from the herbs and spices library were observed to have potential anti-diabetic activity and liquorice, hops, fennel, rosemary, and fenugreek were observed to be particularly enriched with potential anti-diabetic compounds. A large percentage of the compounds were observed to be potential polypharmacological agents regulating three or more anti-diabetic drug targets and included compounds such as achillin B from yarrow, asparasaponin I from fenugreek, bisdemethoxycurcumin from turmeric, carlinoside from lemongrass, cinnamtannin B1 from cinnamon, crocin from sa ron and glabridin from liquorice. The major targets identified for the herbs and spices compounds were dipeptidyl peptidase-4 (DPP4), intestinal maltase-glucoamylase (MGAM), liver receptor homolog-1 (NR5A2), pancreatic alpha-amylase (AM2A), peroxisome proliferator-activated receptor alpha (PPARA), protein tyrosine phosphatase non-receptor type 9 (PTPN9), and retinol binding protein-4 (RBP4) with over 250 compounds observed to be potential inhibitors of these particular protein targets. Only bay leaves, liquorice and thyme were found to contain compounds that could potentially regulate all 18 protein targets followed by black pepper, cumin, dill, hops and marjoram with 17 protein targets. In most cases more than one compound within a given plant could potentially regulate a particular protein target. It was observed that through this multi-compound-multi target regulation of these specific protein targets that the major anti-diabetic e ects of reduced hyperglycemia and hyperlipidemia of the herbs and spices could be explained. The results of this study, taken together with the known scientific literature, indicated that the anti-diabetic potential of common culinary herbs and spices was the result of the collective action of more than one bioactive compound regulating and restoring several dysregulated and interconnected diabetic biological processes.The National Research Foundation of South Africa, the Spanish Ministry of Economy and Competitiveness (CTQ2017-87974-R) and by the Fundación Séneca del Centro de Coordinación de la Investigación de la Región de Murcia under Project 20988/PI/18.http://www.mdpi.com/journal/moleculesam2020BiochemistryGeneticsMicrobiology and Plant Patholog

Novel anti-invasive properties of a Fascin1 inhibitor on colorectal cancer cells

Tumor invasion and metastasis involve processes in which actin cytoskeleton rearrangement induced by Fascin1 plays a crucial role. Indeed, Fascin1 has been found overexpressed in tumors with worse prognosis. Migrastatin and its analogues target Fascin1 and inhibit its activity. However, there is need for novel and smaller Fascin1 inhibitors. The aim of this study was to assess the effect of compound G2 in colorectal cancer cell lines and compare it to migrastatin in in vitro and in vivo assays. Molecular modeling, actin-bundling, cell viability, inmunofluorescence, migration, and invasion assays were carried out in order to test anti-migratory and anti-invasive properties of compound G2. In addition, the in vivo effect of compound G2 was evaluated in a zebrafish model of invasion. HCT-116 cells exhibited the highest Fascin1 expression from eight tested colorectal cancer cell lines. Compound G2 showed important inhibitory effects on actin bundling, filopodia formation, migration, and invasion in different cell lines. Moreover, compound G2 treatment resulted in significant reduction of invasion of DLD-1 overexpressing Fascin1 and HCT-116 in zebrafish larvae xenografts; this effect being less evident in Fascin1 known-down HCT-116 cells. This study proves, for the first time, the in vitro and in vivo anti-tumoral activity of compound G2 on colorectal cancer cells and guides to design improved compound G2-based Fascin1 inhibitors. Key messages center dot Fascin is crucial for tumor invasion and metastasis and is overexpressed in bad prognostic tumors. center dot Several adverse tumors overexpress Fascin1 and lack targeted therapy. center dot Anti-fascin G2 is for the first time evaluated in colorectal carcinoma and compared with migrastatin. center dot Filopodia formation, migration activity, and invasion in vitro and in vivo assays were performed. center dot G2 blocks actin structures, migration, and invasion of colorectal cancer cells as fascin-dependent.Peer reviewe

DIA-DB : a database and web server for the prediction of diabetes drugs

The DIA-DB is a web server for the prediction of diabetes drugs that uses two different and complementary approaches: (a) comparison by shape similarity against a curated database of approved antidiabetic drugs and experimental small molecules and (b) inverse virtual screening of the input molecules chosen by the users against a set of therapeutic protein targets identified as key elements in diabetes. As a proof of concept DIA-DB was successfully applied in an integral workflow for the identification of the antidiabetic chemical profile in a complex crude plant extract. To this end, we conducted the extraction and LC-MS based chemical profile analysis of Sclerocarya birrea and subsequently utilized this data as input for our server. The server is open to all users, registration is not necessary, and a detailed report with the results of the prediction is sent to the user by email once calculations are completed. This is a novel public domain database and web server specific for diabetes drugs and can be accessed online through http://bio-hpc.eu/software/dia-db/.http://pubs.acs.org/journal/jcics1/about.htmlhj2021BiochemistryGeneticsMicrobiology and Plant Patholog

Automatic Selection of Molecular Descriptors using Random Forest: Application to Drug Discovery

The optimal selection of chemical features (molecular descriptors) is an essential pre-processing step for the efficient application of computational intelligence techniques in virtual screening for identification of bioactive molecules in drug discovery. The selection of molecular descriptors has key influence in the accuracy of affinity prediction. In order to improve this prediction, we examined a Random Forest (RF)-based approach to automatically select molecular descriptors of training data for ligands of kinases, nuclear hormone receptors, and other enzymes. The reduction of features to use during prediction dramatically reduces the computing time over existing approaches and consequently permits the exploration of much larger sets of experimental data. To test the validity of the method, we compared the results of our approach with the ones obtained using manual feature selection in our previous study (Perez-Sanchez et al., 2014). The main novelty of this work in the field of drug discovery is the use of RF in two different ways: feature ranking and dimensionality reduction, and classification using the automatically selected feature subset. Our RF-based method out-performs classification results provided by Support Vector Machine (SVM) and Neural Networks (NN) approaches

New role of the antidepressant imipramine as a Fascin1 inhibitor in colorectal cancer cells

Colorectal cancer: Antitumor antidepressant The antidepressant drug imipramine can block the activity of a protein that contributes to the progression of certain aggressive tumors. Serrated adenocarcinoma (SAC) is a form of colorectal cancer with a poor prognosis. A key factor in SAC development is the overexpression of the protein fascin1, which promotes the formation of structures that help cancer cells move around, thereby leading to metastasis. Pablo Conesa-Zamora at Santa Lucia University Hospital in Cartagena, Horacio Perez-Sanchez at the Universidad Catolica de Murcia in Guadalupe, Spain, and coworkers demonstrated that imipramine shows promise in binding to fascin1 and blocking its activity. The team analyzed over 9500 compounds as potential fascin1 blockers, identifying imipramine as a possible option. In tests on human tissues and in vivo studies using zebrafish, the drug reduced cancer invasion and metastasis. Serrated adenocarcinoma (SAC) is more invasive, has worse outcomes than conventional colorectal carcinoma (CRC), and is characterized by frequent resistance to anti-epidermal growth factor receptor (EGFR) and overexpression of fascin1, a key protein in actin bundling that plays a causative role in tumor invasion and is overexpressed in different cancer types with poor prognosis. In silico screening of 9591 compounds, including 2037 approved by the Food and Drug Administration (FDA), was performed, and selected compounds were analyzed for their fascin1 binding affinity by differential scanning fluorescence. The results were compared with migrastatin as a typical fascin1 inhibitor. In silico screening and differential scanning fluorescence yielded the FDA-approved antidepressant imipramine as the most evident potential fascin1 blocker. Biophysical and different in vitro actin-bundling assays confirm this activity. Subsequent assays investigating lamellipodia formation and migration and invasion of colorectal cancer cells in vitro using 3D human tissue demonstrated anti-fascin1 and anti-invasive activities of imipramine. Furthermore, expression profiling suggests the activity of imipramine on the actin cytoskeleton. Moreover, in vivo studies using a zebrafish invasion model showed that imipramine is tolerated, its anti-invasive and antimetastatic activities are dose-dependent, and it is associated with both constitutive and induced fascin1 expression. This is the first study that demonstrates an antitumoral role of imipramine as a fascin1 inhibitor and constitutes a foundation for a molecular targeted therapy for SAC and other fascin1-overexpressing tumors.Peer reviewe