Novel l-prolyl-l-leucylglycinamide (PLG) tripeptidomimetics based on a 2-azanorbornane scaffold as positive allosteric modulators of the D2R.

An efficient and straightforward orthogonal methodology was successfully developed to achieve constrained l-prolyl-l-leucylglycinamide (PLG) analogues starting from two proline mimetics based on a 2-azanorbornane scaffold. A preliminary dopamine D2 receptor radiolabeled binding assay with [3H]-N-propylnorapomorphine shows that enantiopurity of PLG peptidomimetics based on 2-azanorbornane is a requirement to achieve statistically significant positive modulators of the D2 receptor. This is the first documented active peptidomimetic of PLG whose bioactivity is not correlated with the C-terminal carboxamide pharmacophore and which cannot adopt the hypothesized type II ß-turn conformation.

Prediction of multi-target networks of neuroprotective compounds with entropy indices and synthesis, assay, and theoretical study of new asymmetric 1,2-rasagiline carbamates.

In a multi-target complex network, the links (L(ij)) represent the interactions between the drug (d(i)) and the target (t(j)), characterized by different experimental measures (K(i), K(m), IC50, etc.) obtained in pharmacological assays under diverse boundary conditions (c(j)). In this work, we handle Shannon entropy measures for developing a model encompassing a multi-target network of neuroprotective/neurotoxic compounds reported in the CHEMBL database. The model predicts correctly >8300 experimental outcomes with Accuracy, Specificity, and Sensitivity above 80%-90% on training and external validation series. Indeed, the model can calculate different outcomes for >30 experimental measures in >400 different experimental protocolsin relation with >150 molecular and cellular targets on 11 different organisms (including human). Hereafter, we reported by the first time the synthesis, characterization, and experimental assays of a new series of chiral 1,2-rasagiline carbamate derivatives not reported in previous works. The experimental tests included: (1) assay in absence of neurotoxic agents; (2) in the presence of glutamate; and (3) in the presence of H2O2. Lastly, we used the new Assessing Links with Moving Averages (ALMA)-entropy model to predict possible outcomes for the new compounds in a high number of pharmacological tests not carried out experimentally.

Copper-catalyzed Huisgen 1,3-dipolar cycloaddition under oxidative conditions: polymer-assisted assembly of 4-acyl-1-substituted-1,2,3-triazoles.

We herein document the first example of a reliable copper-catalyzed Huisgen 1,3-dipolar cycloaddition under oxidative conditions. The combined use of two polymer-supported reagents (polystyrene-1,5,7-triazabicyclo[4,4,0]dec-5-ene/Cu and polystyrene-2-iodoxybenzamide) overcomes the thermodynamic instability of copper(I) species toward oxidation, enabling the reliable Cu-catalyzed Huisgen 1,3-dipolar cycloadditions in the presence of an oxidant agent. This polymer-assisted pathway, not feasible under conventional homogeneous conditions, provides a direct assembly of 4-acyl-1-substituted-1,2,3-triazoles, contributing to expand the reliability and scope of Cu(I)-catalyzed alkyne-azide cycloaddition.

TOPS-MODE model of multiplexing neuroprotective effects of drugs and experimental-theoretic study of new 1,3-rasagiline derivatives potentially useful in neurodegenerative diseases.

The interest on computational techniques for the discovery of neuroprotective drugs has increased due to recent fail of important clinical trials. In fact, there is a huge amount of data accumulated in public databases like CHEMBL with respect to structurally heterogeneous series of drugs, multiple assays, drug targets, and model organisms. However, there are no reports of multi-target or multiplexing Quantitative Structure-Property Relationships (mt-QSAR/mx-QSAR) models of these multiplexing assay outcomes reported in CHEMBL for neurotoxicity/neuroprotective effects of drugs. Accordingly, in this paper we develop the first mx-QSAR model for multiplexing assays of neurotoxicity/neuroprotective effects of drugs. We used the method TOPS-MODE to calculate the structural parameters of drugs. The best model found correctly classified 4393 out of 4915 total cases in both training and validation. This is representative of overall train and validation Accuracy, Sensitivity, and Specificity values near to 90%, 98%, and 80%, respectively. This dataset includes multiplexing assay endpoints of 2217 compounds. Every one compound was assayed in at least one out of 338 assays, which involved 148 molecular or cellular targets and 35 standard type measures in 11 model organisms (including human). The second aim of this work is the exemplification of the use of the new mx-QSAR model with a practical case of study. To this end, we obtained again by organic synthesis and reported, by the first time, experimental assays of the new 1,3-rasagiline derivatives 3 different tests: assay (1) in absence of neurotoxic agents, (2) in the presence of glutamate, and (3) in the presence of H2O2. The higher neuroprotective effects found for each one of these assays were for the stereoisomers of compound 7: compound 7b with protection=23.4% in assay (1) and protection=15.2% in assay (2); and for compound 7a with protection=46.2% in assay (3). Interestingly, almost all compounds show protection values >10% in assay (3) but not in the other 2 assays. After that, we used the mx-QSAR model to predict the more probable response of the new compounds in 559 unique pharmacological tests not carried out experimentally. The results obtained are very significant because they complement the pharmacological studies of these promising rasagiline derivatives. This work paves the way for further developments in the multi-target/multiplexing screening of large libraries of compounds potentially useful in the treatment of neurodegenerative diseases.

MIND-BEST: Web server for drugs and target discovery; design, synthesis, and assay of MAO-B inhibitors and theoretical-experimental study of G3PDH protein from Trichomonas gallinae.

Many drugs with very different affinity to a large number of receptors are described. Thus, in this work, we selected drug-target pairs (DTPs/nDTPs) of drugs with high affinity/nonaffinity for different targets. Quantitative structure-activity relationship (QSAR) models become a very useful tool in this context because they substantially reduce time and resource-consuming experiments. Unfortunately, most QSAR models predict activity against only one protein target and/or they have not been implemented on a public Web server yet, freely available online to the scientific community. To solve this problem, we developed a multitarget QSAR (mt-QSAR) classifier combining the MARCH-INSIDE software for the calculation of the structural parameters of drug and target with the linear discriminant analysis (LDA) method in order to seek the best model. The accuracy of the best LDA model was 94.4% (3,859/4,086 cases) for training and 94.9% (1,909/2,012 cases) for the external validation series. In addition, we implemented the model into the Web portal Bio-AIMS as an online server entitled MARCH-INSIDE Nested Drug-Bank Exploration & Screening Tool (MIND-BEST), located at http://miaja.tic.udc.es/Bio-AIMS/MIND-BEST.php . This online tool is based on PHP/HTML/Python and MARCH-INSIDE routines. Finally, we illustrated two practical uses of this server with two different experiments. In experiment 1, we report for the first time a MIND-BEST prediction, synthesis, characterization, and MAO-A and MAO-B pharmacological assay of eight rasagiline derivatives, promising for anti-Parkinson drug design. In experiment 2, we report sampling, parasite culture, sample preparation, 2-DE, MALDI-TOF and -TOF/TOF MS, MASCOT search, 3D structure modeling with LOMETS, and MIND-BEST prediction for different peptides as new protein of the found in the proteome of the bird parasite Trichomonas gallinae, which is promising for antiparasite drug targets discovery.

Synthesis, Pharmacological, and Biological Evaluation of 2-Furoyl-Based MIF-1 Peptidomimetics and the Development of a General-Purpose Model for Allosteric Modulators (ALLOPTML).

This work describes the synthesis and pharmacological evaluation of 2-furoyl-based Melanostatin (MIF-1) peptidomimetics as dopamine D2 modulating agents. Eight novel peptidomimetics were tested for their ability to enhance the maximal effect of tritiated N-propylapomorphine ([3H]-NPA) at D2 receptors (D2R). In this series, 2-furoyl-l-leucylglycinamide (6a) produced a statistically significant increase in the maximal [3H]-NPA response at 10 pM (11 ± 1%), comparable to the effect of MIF-1 (18 ± 9%) at the same concentration. This result supports previous evidence that the replacement of proline residue by heteroaromatic scaffolds are tolerated at the allosteric binding site of MIF-1. Biological assays performed for peptidomimetic 6a using cortex neurons from 19-day-old Wistar-Kyoto rat embryos suggest that 6a displays no neurotoxicity up to 100 µM. Overall, the pharmacological and toxicological profile and the structural simplicity of 6a makes this peptidomimetic a potential lead compound for further development and optimization, paving the way for the development of novel modulating agents of D2R suitable for the treatment of CNS-related diseases. Additionally, the pharmacological and biological data herein reported, along with >20 000 outcomes of preclinical assays, was used to seek a general model to predict the allosteric modulatory potential of molecular candidates for a myriad of target receptors, organisms, cell lines, and biological activity parameters based on perturbation theory (PT) ideas and machine learning (ML) techniques, abbreviated as ALLOPTML. By doing so, ALLOPTML shows high specificity Sp = 89.2/89.4%, sensitivity Sn = 71.3/72.2%, and accuracy Ac = 86.1%/86.4% in training/validation series, respectively. To the best of our knowledge, ALLOPTML is the first general-purpose chemoinformatic tool using a PTML-based model for the multioutput and multicondition prediction of allosteric compounds, which is expected to save both time and resources during the early drug discovery of allosteric modulators.

3,4-Dihydropyrimidin-2(1H)-ones as Antagonists of the Human A2B Adenosine Receptor: Optimization, Structure-Activity Relationship Studies, and Enantiospecific Recognition.

We present and thoroughly characterize a large collection of 3,4-dihydropyrimidin-2(1H)-ones as A2BAR antagonists, an emerging strategy in cancer (immuno) therapy. Most compounds selectively bind A2BAR, with a number of potent and selective antagonists further confirmed by functional cyclic adenosine monophosphate experiments. The series was analyzed with one of the most exhaustive free energy perturbation studies on a GPCR, obtaining an accurate model of the structure-activity relationship of this chemotype. The stereospecific binding modeled for this scaffold was confirmed by resolving the two most potent ligands [(±)-47, and (±)-38 Ki = 10.20 and 23.6 nM, respectively] into their two enantiomers, isolating the affinity on the corresponding (S)-eutomers (Ki = 6.30 and 11.10 nM, respectively). The assessment of the effect in representative cytochromes (CYP3A4 and CYP2D6) demonstrated insignificant inhibitory activity, while in vitro experiments in three prostate cancer cells demonstrated that this pair of compounds exhibits a pronounced antimetastatic effect.

Synthesis and pharmacological evaluation of novel 1,3,8- and 1,3,7,8-substituted xanthines as adenosine receptor antagonists.

A number of novel xanthines bearing a variety of substituents at positions 1, 3, 7 and 8 were prepared and evaluated for their binding affinity to the human adenosine receptor A(1), A(2A), A(2B) and A(3) subtypes. Several of the 1,3,8- and 1,3,7,8-substituted xanthines showed moderate-to-high affinity at human A(2B) and A(1) receptors, with the most active compound (14q) having a pK(i) of 7.57 nM for hA(2B) receptors and a selectivity over hA(2A) receptors of 8.1-fold and hA(1) receptors of 3.7-fold.

Nitrogen-Walk Approach to Explore Bioisosteric Replacements in a Series of Potent A2B Adenosine Receptor Antagonists.

A systematic exploration of bioisosteric replacements for furan and thiophene cores in a series of potent A2BAR antagonists has been carried out using the nitrogen-walk approach. A collection of 42 novel alkyl 4-substituted-2-methyl-1,4-dihydrobenzo[4,5]imidazo[1,2-a]pyrimidine-3-carboxylates, which contain 18 different pentagonal heterocyclic frameworks at position 4, was synthesized and evaluated. This study enabled the identification of new ligands that combine remarkable affinity (Ki < 30 nM) and exquisite selectivity. The structure-activity relationship (SAR) trends identified were substantiated by a molecular modeling study, based on a receptor-driven docking model and including a systematic free energy perturbation (FEP) study. Preliminary evaluation of the CYP3A4 and CYP2D6 inhibitory activity in optimized ligands evidenced weak and negligible activity, respectively. The stereospecific interaction between hA2BAR and the eutomer of the most attractive novel antagonist (S)-18g (Ki = 3.66 nM) was validated.

1,3-dialkyl-8-N-substituted benzyloxycarbonylamino-9-deazaxanthines as potent adenosine receptor ligands: Design, synthesis, structure-affinity and structure-selectivity relationships.

A number of 1,3-dialkyl-9-deazaxanthines (9-dAXs), bearing a variety of N-substituted benzyloxycarbonylamino substituents at position 8, were prepared and evaluated for their binding affinity to the recombinant human adenosine receptors (hARs), chiefly to the hA(2B) and hA(2A) AR subtypes. Several ligands endowed with excellent binding affinity to the hA(2B) receptors, but low selectivity versus hA(2A) and hA(1) were identified. Among these, 1,3-dimethyl-N-3'-thienyl carbamate 15 resulted as the most potent ligand at hA(2B) (K(i)=0.8 nM), with a low selectivity versus hA(2A) (hA(2A)/hA(2B)=12.6) and hA(1) (hA(1)/hA(2B)=12.5) and a higher selectivity versus hA(3) (hA(3)/hA(2B)=454). When tested in functional assays in vitro, compound 15 exhibited high antagonist activities and efficacies versus both the A(2A) and A(2B) receptor subtypes, with pA(2) values close to the corresponding pK(i)s. A comparative analysis of structure-affinity and structure-selectivity relationships of the similar analogues 8-N-substituted benzyloxycarbonylamino- and 8-N-substituted phenoxyacetamido-9-dAXs suggested that their binding modes at the hA(2B) and hA(2A) ARs may strongly differ. Computational studies help to clarify this striking difference arising from a simple, albeit crucial, structural change, from CH(2)OCON to OCH(2)CON, in the para-position of the 8-phenyl ring.

Synthesis and pharmacological evaluation of novel 1- and 8-substituted-3-furfuryl xanthines as adenosine receptor antagonists.

The synthesis of an important set of 3-furfurylxanthine derivatives is described. Binding affinities were determined for rat A(1) and human A(2A), A(2B) and A(3) receptors. Several of the 3-furfuryl-7-methylxanthine derivatives showed moderate-to-high affinity at human A(2B) receptors, the most active compound (10d) having a K(i) of 7.4 nM for hA(2B) receptors, with selectivities over rA(1) and hA(2A) receptors up to 14-fold and 11-fold, respectively. Affinities for hA(3) receptors were very low for all members of the set.

Synthesis of novel 1-alkyl-8-substituted-3-(3-methoxypropyl) xanthines as putative A(2B) receptor antagonists.

In order to identify a high-affinity, selective antagonist for the A(2B) subtype adenosine receptor, more than 40 1,8-disubstituted-3-(3-methoxypropyl) xanthines were prepared and evaluated for their binding affinity at recombinant human adenosine receptors, mainly of the A(2A) and A(2B) subtypes. Some of the 1-ethyl-3-(3-methoxypropyl)-8-aryl substituted derivatives 15(a-m) showed moderate-to-high affinity at human A(2B) receptors, with compound 15d showing A(2B) selectivity over the other A receptors assayed (A(1), A(2A), A(3)) of 34-fold or over.

Trifluorinated Pyrimidine-Based A2B Antagonists: Optimization and Evidence of Stereospecific Recognition.

We report the identification of two subsets of fluorinated nonxanthine A2B adenosine receptor antagonists. The novel derivatives explore the effect of fluorination at different positions of two pyrimidine-based scaffolds. The most interesting ligands combine excellent hA2B affinity (Ki < 15 nM) and remarkable subtype selectivity. The results of functional cAMP experiments confirmed the antagonistic behavior of representative ligands. The compounds were designed on the basis of previous molecular models of the stereoselective binding of the parent scaffolds to the hA2B receptor, and we herein provide refinement of such models with the fluorinated compounds, which allows the explanation of the spurious effects of the fluorination at the different positions explored. These models are importantly confirmed by a synergistic study combining chiral HPLC, circular dichroism, diastereoselective synthesis, molecular modeling, and X-ray crystallography, providing experimental evidence toward the stereospecific interaction between optimized trifluorinated stereoisomers and the hA2B receptor.

Perturbation Theory/Machine Learning Model of ChEMBL Data for Dopamine Targets: Docking, Synthesis, and Assay of New l-Prolyl-l-leucyl-glycinamide Peptidomimetics.

Predicting drug-protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning (ML) models for one specific protein. Unfortunately, these models fail to account for large and complex big data sets of preclinical assays reported in public databases. This includes multiple conditions of assays, such as different experimental parameters, biological assays, target proteins, cell lines, organism of the target, or organism of assay. On the other hand, perturbation theory (PT) models allow us to predict the properties of a query compound or molecular system in experimental assays with multiple boundary conditions based on a previously known case of reference. In this work, we report the first PTML (PT + ML) study of a large ChEMBL data set of preclinical assays of compounds targeting dopamine pathway proteins. The best PTML model found predicts 50000 cases with accuracy of 70-91% in training and external validation series. We also compared the linear PTML model with alternative PTML models trained with multiple nonlinear methods (artificial neural network (ANN), Random Forest, Deep Learning, etc.). Some of the nonlinear methods outperform the linear model but at the cost of a notable increment of the complexity of the model. We illustrated the practical use of the new model with a proof-of-concept theoretical-experimental study. We reported for the first time the organic synthesis, chemical characterization, and pharmacological assay of a new series of l-prolyl-l-leucyl-glycinamide (PLG) peptidomimetic compounds. In addition, we performed a molecular docking study for some of these compounds with the software Vina AutoDock. The work ends with a PTML model predictive study of the outcomes of the new compounds in a large number of assays. Therefore, this study offers a new computational methodology for predicting the outcome for any compound in new assays. This PTML method focuses on the prediction with a simple linear model of multiple pharmacological parameters (IC50, EC50, Ki, etc.) for compounds in assays involving different cell lines used, organisms of the protein target, or organism of assay for proteins in the dopamine pathway.

Effect of Nitrogen Atom Substitution in A3 Adenosine Receptor Binding: N-(4,6-Diarylpyridin-2-yl)acetamides as Potent and Selective Antagonists.

We report the first family of 2-acetamidopyridines as potent and selective A3 adenosine receptor (AR) antagonists. The computer-assisted design was focused on the bioisosteric replacement of the N1 atom by a CH group in a previous series of diarylpyrimidines. Some of the generated 2-acetamidopyridines elicit an antagonistic effect with excellent affinity (Ki < 10 nM) and outstanding selectivity profiles, providing an alternative and simpler chemical scaffold to the parent series of diarylpyrimidines. In addition, using molecular dynamics and free energy perturbation simulations, we elucidate the effect of the second nitrogen of the parent diarylpyrimidines, which is revealed as a stabilizer of a water network in the binding site. The discovery of 2,6-diaryl-2-acetamidopyridines represents a step forward in the search of chemically simple, potent, and selective antagonists for the hA3AR, and exemplifies the benefits of a joint theoretical-experimental approach to identify novel hA3AR antagonists through succinct and efficient synthetic methodologies.

Multi-Target Mining of Alzheimer Disease Proteome with Hansch's QSBR-Perturbation Theory and Experimental-Theoretic Study of New Thiophene Isosters of Rasagiline.

Hansch's model is a classic approach to Quantitative Structure-Binding Relationships (QSBR) problems in Pharmacology and Medicinal Chemistry. Hansch QSAR equations are used as input parameters of electronic structure and lipophilicity. In this work, we perform a review on Hansch's analysis. We also developed a new type of PT-QSBR Hansch's model based on Perturbation Theory (PT) and QSBR approach for a large number of drugs reported in CheMBL. The targets are proteins expressed by the Hippocampus region of the brain of Alzheimer Disease (AD) patients. The model predicted correctly 49312 out of 53783 negative perturbations (Specificity = 91.7%) and 16197 out of 21245 positive perturbations (Sensitivity = 76.2%) in training series. The model also predicted correctly 49312/53783 (91.7%) and 16197/21245 (76.2%) negative or positive perturbations in external validation series. We applied our model in theoretical-experimental studies of organic synthesis, pharmacological assay, and prediction of unmeasured results for a series of compounds similar to Rasagiline (compound of reference) with potential neuroprotection effect.

Brain-inspired cheminformatics of drug-target brain interactome, synthesis, and assay of TVP1022 derivatives.

The use of Cheminformatics tools is gaining importance in the field of translational research from Medicinal Chemistry to Neuropharmacology. In particular, we need it for the analysis of chemical information on large datasets of bioactive compounds. These compounds form large multi-target complex networks (drug-target interactome network) resulting in a very challenging data analysis problem. Artificial Neural Network (ANN) algorithms may help us predict the interactions of drugs and targets in CNS interactome. In this work, we trained different ANN models able to predict a large number of drug-target interactions. These models predict a dataset of thousands of interactions of central nervous system (CNS) drugs characterized by > 30 different experimental measures in >400 different experimental protocols for >150 molecular and cellular targets present in 11 different organisms (including human). The model was able to classify cases of non-interacting vs. interacting drug-target pairs with satisfactory performance. A second aim focus on two main directions: the synthesis and assay of new derivatives of TVP1022 (S-analogues of rasagiline) and the comparison with other rasagiline derivatives recently reported. Finally, we used the best of our models to predict drug-target interactions for the best new synthesized compound against a large number of CNS protein targets.

Synthesis by microwave-assisted 1,3-dipolar cycloaddition of 1,2,3-triazole 1'-homo-3'-isoazanucleosides and evaluation of their anticancer activity.

Racemic 1'-homo-3'-isoazanucleosides have been obtained by microwave-assisted 1,3-dipolar cycloaddition of 3,5-disubstituted proline derivative (±)-2 with different alkynes. The compounds obtained were evaluated for their cytotoxic activities in vitro against human breast carcinoma cell lines (MCF-7), human ovary carcinoma cell lines (A2780) and human lung carcinoma cell lines (NCI-H460).

Pyrazin-2(1H)-ones as a novel class of selective A3 adenosine receptor antagonists.

BACKGROUND: A3AR antagonists are promising drug candidates as neuroprotective agents as well as for the treatment of inflammation or glaucoma. The most widely known A3AR antagonists are derived from polyheteroaromatic scaffolds, which usually show poor pharmacokinetic properties. Accordingly, the identification of structurally simple A3AR antagonists by the exploration of novel diversity spaces is a challenging goal. RESULTS: A convergent and efficient Ugi-based multicomponent approach enabled the discovery of pyrazin-2(1H)-ones as a novel class of A3AR antagonists. A combined experimental/computational strategy accelerated the establishment of the most salient features of the structure-activity and structure-selectivity relationships in this series. CONCLUSION: The optimization process provided pyrazin-2(1H)-ones with improved affinity and a plausible hypothesis regarding their binding modes was proposed.

Synthesis, antiviral and cytostatic activities, of carbocyclic nucleosides incorporating a modified cyclopentane ring. IV. Adenosine and uridine analogues.

Eight new carbocyclic nucleosides were prepared by mounting a purine (compounds 8-10), 8-azapurine (12 and 13) or pyrimidine (15, 16 and 17b) on the amino group of (1S,3R)-3-aminomethyl-2,2,3-trimethylcyclopentylmethanol (6). All the compounds were evaluated as antiviral and antitumor agents in a variety of assay systems. Only compound 8 showed any cytostatic activity against the tumor cell lines examined.