Six-membered cyclic ureas as HIV-1 protease inhibitors: a QSAR study based on CODESSA PRO approach. Quantitative structure-activity relationships

Polydentate N,O-Ligands Possessing Unsymmetrical Urea Fragments Attached to a p-Cresol Scaffold

In this study, three series of polydentate N,O-ligands possessing unsymmetrical urea fragments attached to a p-cresol scaffold are obtained, namely mono- and bi-substituted open-chain aromatics, synthesised using a common experiment, as well as fused aryloxazinones. Separate protocols for the preparation of each series are developed. It is found that in the case of open-chain compounds, the reaction output is strongly dependent on both bis-amine and carbamoyl chloride substituents, while oxazinones can be effectively obtained via a common protocol. The products are characterized via 1D and 2D NMR spectra in solution and using single-crystal XRD. A preliminary study on the coordination abilities of the products performed via ITC shows that there are no substantial interactions in the pH range of 5.0-8.5 in general.

Bioassay-Guided Alkaloids Isolation from Camellia sinensis and Colchicum luteum: In Silico and In Vitro Evaluations for Protease Inhibition

Bioassay-guided isolation from Camellia sinensis (Theaceae) and Colchicum luteum (Liliaceae) utilizing an in vitro model of protease assay revealed colchicine (1) and caffeine (2) from chloroform fractions, respectively. Their structures were validated using spectral techniques. The purified compounds were further optimized with Gaussian software utilizing the B3LYP functional and 6-31G(d,p) basis set. The result files were utilized to determine several global reactivity characteristics to explain the diverse behavior of the compounds. Colchicine (1) showed a higher inhibition of protease activity (63.7 ± 0.5 %age with IC50 = 0.83 ± 0.07 mM), compared with caffeine (2) (39.2 ± 1.3 %age). In order to determine the type of inhibition, compound 1 was further studied, and, based on Lineweaver–Burk/Dixon plots and their secondary replots, it was depicted that compound 1 was a non-competitive inhibitor of this enzyme, with a Ki value of 0.690 ± 0.09 mM. To elucidate the theoretical features of protease inhibition, molecular docking studies were performed against serine protease (PDB #1S0Q), which demonstrated that compound 1 had a strong interaction with the different amino acid residues located on the active site of this understudied enzyme, with a high docking score of 16.2 kcal/mol.

Valorisation of plastic waste via metal-catalysed depolymerisation

Metal-catalysed depolymerisation of plastics to reusable building blocks, including monomers, oligomers or added-value chemicals, is an attractive tool for the recycling and valorisation of these materials. The present manuscript shortly reviews the most significant contributions that appeared in the field within the period January 2010–January 2020 describing selective depolymerisation methods of plastics. Achievements are broken down according to the plastic material, namely polyolefins, polyesters, polycarbonates and polyamides. The focus is on recent advancements targeting sustainable and environmentally friendly processes. Biocatalytic or unselective processes, acid–base treatments as well as the production of fuels are not discussed, nor are the methods for the further upgrade of the depolymerisation products.

Pd Nanoparticles and Mixture of CO2/CO/O2 Applied in the Carbonylation of Aniline

CO2 is a compound of high stability which proves useful in some organic syntheses as a solvent or component decreasing explosivity of gases. It is also a good carbonylating agent for aliphatic amines although not for aromatic ones, the latter being carbonylated with phosgene or, as in our previous works, with CO/O2 in the presence of Pd(II) complexes. In this work we have used the mixture of CO/O2 and CO2 for carbonylation of aniline to N,N’-diphenylurea. After optimization of the reaction conditions (56% of CO2 in CO2/CO mixture) we studied the activity of three kinds of pre-catalysts: (a) Pd(II) complexes, (b) Pdblack, and (c) palladium nanoparticles (PdNPs) in the presence of derivatives of pyridine (XnPy). The highest conversion of aniline (with selectivity towards N,N-diphenylurea ca. 90%) was observed for PdNPs. The results show that catalytic cycle involves Pd(0) stabilized by pyridine ligand as active species. Basing on this observation, we put the hypothesis that application of PdNPs instead of Pd(II) complex can efficiently reduce the reaction time.

A novel one-pot method for the stereoselective synthesis of tetrahydropyrimidinones in a low melting mixture

A direct and metal free one-pot method has been developed for the stereoselective synthesis of tetrahydropyrimidinone derivatives from a vinyl arene and formaldehyde using a tartaric acid-dimethylurea (TA : DMU) melt as a green reaction medium. The substrate scope of this method is very general and the tetrahydropyrimidinone (THPM) derivatives are synthesized in good yields with a high degree of diastereoselectivity. In this reaction, the melt plays a triple role as the solvent, catalyst and reagent.

The eternal battle to combat global warming: (thio)urea as a CO2 wet scrubbing agent

(Thio)Urea scaffolds are best known for their importance as intermediates in organic synthesis. In this work, a mechanistic study of the reaction between urea (U), (2-hydroxyethyl)urea (U-EtOH) and thiourea (tU)/NaH in DMSO with CO2 was carried out. While both U/tU reacted with CO2via a 1 : 2 mechanism through the formation of the keto (thio)carbamide-carboxylate adducts (k-U/tU-CO2- Na+), U-EtOH gave mixed CO2-adducts composed of organic carbonate and carbamide-carboxylate moieties (Na+-CO2-U-Et-OCO2- Na+). Moreover, we recorded for the first time, a new type of bond, namely sodium carbamimidothiocarbonate (e-tU-SCO2- Na+), upon bubbling CO2 in the DMSO solution of tU due to the persistence of the enol form (e-tU) and the better nucleophilicity of sulfur over nitrogen focal points. The reaction mechanisms were proven by 1D and 2D nuclear magnetic resonance (NMR) and ex situ attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopies. The stability of these bonds was studied following the changes in 1H-NMR as a function of temperature, which indicated the reversibility of these reactions. Furthermore, the proposed mechanisms were explored theoretically via density functional theory (DFT) calculations by analyzing the energetics of the anticipated products.

Synthesis of ferrocene-containing six-membered cyclic ureas via α-ferrocenyl carbocations

A convenient method for the synthesis of ferrocene-containing six membered cyclic ureas was developed.

Model for vaccine design by prediction of B-epitopes of IEDB given perturbations in peptide sequence, in vivo process, experimental techniques, and source or host organisms

Perturbation methods add variation terms to a known experimental solution of one problem to approach a solution for a related problem without known exact solution. One problem of this type in immunology is the prediction of the possible action of epitope of one peptide after a perturbation or variation in the structure of a known peptide and/or other boundary conditions (host organism, biological process, and experimental assay). However, to the best of our knowledge, there are no reports of general-purpose perturbation models to solve this problem. In a recent work, we introduced a new quantitative structure-property relationship theory for the study of perturbations in complex biomolecular systems. In this work, we developed the first model able to classify more than 200,000 cases of perturbations with accuracy, sensitivity, and specificity >90% both in training and validation series. The perturbations include structural changes in >50000 peptides determined in experimental assays with boundary conditions involving >500 source organisms, >50 host organisms, >10 biological process, and >30 experimental techniques. The model may be useful for the prediction of new epitopes or the optimization of known peptides towards computational vaccine design.

S. Cordeiro MN, Yañez M, González-Díaz H, García-Mera X. Model for high-throughput screening of multitarget drugs in chemical neurosciences: synthesis, assay, and theoretic study of rasagiline carbamates

The disappointing results obtained in recent clinical trials renew the interest in experimental/computational techniques for the discovery of neuroprotective drugs. In this context, multitarget or multiplexing QSAR models (mt-QSAR/mx-QSAR) may help to predict neurotoxicity/neuroprotective effects of drugs in multiple assays, on drug targets, and in model organisms. In this work, we study a data set downloaded from CHEMBL; each data point (>8000) contains the values of one out of 37 possible measures of activity, 493 assays, 169 molecular or cellular targets, and 11 different organisms (including human) for a given compound. In this work, we introduce the first mx-QSAR model for neurotoxicity/neuroprotective effects of drugs based on the MARCH-INSIDE (MI) method. First, we used MI to calculate the stochastic spectral moments (structural descriptors) of all compounds. Next, we found a model that classified correctly 2955 out of 3548 total cases in the training and validation series with Accuracy, Sensitivity, and Specificity values>80%. The model also showed excellent results in Computational-Chemistry simulations of High-Throughput Screening (CCHTS) experiments, with accuracy=90.6% for 4671 positive cases. Next, we reported the synthesis, characterization, and experimental assays of new rasagiline derivatives. We carried out three different experimental tests: assay (1) in the absence of neurotoxic agents, assay (2) in the presence of glutamate, and assay (3) in the presence of H2O2. Compounds 11 with 27.4%, 8 with 11.6%, and 9 with 15.4% showed the highest neuroprotective effects in assays (1), (2), and (3), respectively. After that, we used the mx-QSAR model to carry out a CCHTS of the new compounds in >400 unique pharmacological tests not carried out experimentally. Consequently, this model may become a promising auxiliary tool for the discovery of new drugs for the treatment of neurodegenerative diseases.

Synthesis of uriedo and thiouriedo derivatives of peptide conjugated heterocycles - A new class of promising antimicrobials

Forty five new derivatives of ureas and thioureas were synthesized by the reaction of peptide conjugated heterocycles with isocyanates and isothiocyanates respectively. All the compounds have been characterized by IR, (1)H NMR, mass and elemental analysis. The compounds were evaluated for their ability to inhibit the growth of a panel of microorganisms and all the synthesized compounds displayed an excellent antimicrobial activity. From structure-activity relationship studies, it was apparent that thioureas infact is slightly more active than ureas. Also, substituents on the phenyl ring of the title compounds play a key role in the activity. Further, compound 40 is nearly twenty times more potent than the standard used. These results present a platform for the further studies in this line.

Quantitative structure-activity relationship models with receptor-dependent descriptors for predicting peroxisome proliferator-activated receptor activities of thiazolidinedione and oxazolidinedione derivatives

A quantitative structure-activity relationship study has been carried out, in which the relationship between the peroxisome proliferator-activated receptor alpha and the peroxisome proliferator-activated receptor gamma agonistic activities of thiazolidinedione and oxazolidinedione derivatives and quantitative descriptors, V(site) calculated in a receptor-dependent manner is modeled. These descriptors quantify the volume occupied by the optimized ligands in regions that are either common or specific to the superimposed binding sites of the targets under consideration. The quantitative structure-activity relationship models were built by forward stepwise linear regression modeling for a training set of 27 compounds and validated for a test set of seven compounds, resulting in a squared correlation coefficient value of 0.90 for peroxisome proliferator-activated receptor alpha and of 0.89 for peroxisome proliferator-activated receptor gamma. The leave-one-out cross-validation and test set predictability squared correlation coefficient values for these models were 0.85 and 0.62 for peroxisome proliferator-activated receptor alpha and 0.89 and 0.50 for peroxisome proliferator-activated receptor gamma respectively. A dual peroxisome proliferator-activated receptor model has also been developed, and it indicates the structural features required for the design of ligands with dual peroxisome proliferator-activated receptor activity. These quantitative structure-activity relationship models show the importance of the descriptors here introduced in the prediction and interpretation of the compounds affinity and selectivity.

QSAR modeling of anti-invasive activity of organic compounds using structural descriptors

The anti-invasive activity of 139 compounds was correlated by an artificial neural network approach with descriptors calculated solely from the molecular structures using CODESSA Pro. The best multilinear regression method implemented in CODESSA Pro was used for a pre-selection of descriptors. The resulting nonlinear (artificial neural network) QSAR model predicted the exact class for 66 (71%) of the training set of 93 compounds and 32 (70%) of validation set of 46 compounds. The standard deviation ratios for the both training and validation sets are less than unity, indicating a satisfactory predictive capability for classification of the nature of the anti-invasive activity data. The proposed model can be used for the prediction of the anti-invasive activity of novel classes of compounds enabling a virtual screening of large databases of anticancer drugs.

Modeling of activity of cyclic urea HIV-1 protease inhibitors using regularized-artificial neural networks

Artificial neural networks (ANNs) were used to model both inhibition of HIV-1 protease (K(i)) and inhibition of HIV replication (IC90) for 55 cyclic urea derivatives using constitutional and 2D descriptors. As a preliminary step, linear dependences were established by multiple linear regression (MLR) approaches, selecting the relevant descriptors by genetic algorithm (GA) feature selection. For ANN models non-linear GA feature selection was also applied. Non-linear modeling of K(i) overcame the results of the linear one using four properties, keeping in mind standard Pearson R correlation coefficients (0.931 vs. 0.862) and leave one out (LOO) cross-validation analysis (Q(LOO)2 = 0.703 vs. 0.510). On the other hand, IC90 modeling was insoluble by a linear approach: no predictive model was achieved; however, a non-linear relation was encountered according to statistic results (R = 0.891; Q(LOO)2 = 0.568). The best non-linear models suggested the influence of the presence of nitrogen atoms and the molecular volume distribution in the inhibitor structures on the HIV-1 protease inhibition as well as that the inhibition of HIV replication was dependent on the occurrence of five-member rings. Finally, inhibitors were well distributed regarding its activity levels in a Kohonen self-organizing map built using the input variables of the best non-linear models.

Synthesis, cytotoxicity, and DNA-topoisomerase inhibitory activity of new asymmetric ureas and thioureas

A new series of N-3,3-diphenylpropyl-N-(p-X-benzyl)-N'-phenylureas (5a-g) and thioureas (6a-g) were synthesized by the reaction of secondary amines and phenyl isocyanate or isothiocyanate. The cytotoxic effects of the urea and thiourea derivatives were evaluated by MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay against Ehrlich carcinoma and K562 human leukemia cells. Moreover, the activity of compounds in the inhibition of DNA topoisomerases I and II-alpha was tested. The results indicated that the compounds presented important and promising antiproliferative action.

Topological models for the prediction of HIV-protease inhibitory activity of tetrahydropyrimidin-2-ones

Relationship between the topological indices and HIV-protease inhibitory activity of tetrahydropyrimidine-2-ones has been investigated. Three topological indices, Wiener's index--a distance based topological descriptor, Zagreb group parameter--an adjacency based topological descriptor and eccentric connectivity index--an adjacency-cum-distance based topological descriptor were used for the present investigations. A dataset comprising of 80 substituted tetrahydropyrimidine-2-one analogues was selected for the present studies. The values of the Wiener's index, Zagreb group parameter and eccentric connectivity index for each of the 80 compounds comprising the dataset were computed using an in-house computer program. The dataset was divided randomly into training and test sets. Resultant data was analyzed and suitable models were developed after identifying the active ranges in the training set. Subsequently, a biological activity was assigned to each of the compound involved in the test set using these models, which was then compared with the reported HIV-protease inhibitory activity. Accuracy of prediction using these models was found to vary from a minimum of approximately 86% to a maximum of approximately 88%.