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A set of twenty-five thioxanthene-9-one and xanthene-9-one derivatives, that were previously shown to inhibit cholinesterases (ChEs) and amyloid β (Aβ40) aggregation, were evaluated for the inhibition of tau protein aggregation. All compounds exhibited a good activity, and eight of them (5–8, 10, 14, 15 and 20) shared comparable low micromolar inhibitory potency versus Aβ40 aggregation and human acetylcholinesterase (AChE), while inhibiting human butyrylcholinesterase (BChE) even at submicromolar concentration. Compound 20 showed outstanding biological data, inhibiting tau protein and Aβ40 aggregation with IC50 = 1.8 and 1.3 μM, respectively. Moreover, at 0.1–10 μM it also exhibited neuroprotective activity against tau toxicity induced by okadoic acid in human neuroblastoma SH-SY5Y cells, that was comparable to that of estradiol and PD38. In preliminary toxicity studies, these interesting results for compound 20 are somewhat conflicting with a narrow safety window. However, compound 10, although endowed with a little lower potency for tau and Aβ aggregation inhibition additionally demonstrated good inhibition of ChEs and rather low cytotoxicity. Compound 4 is also worth of note for its high potency as hBChE inhibitor (IC50 = 7 nM) and for the three order of magnitude selectivity versus hAChE. Molecular modelling studies were performed to explain the different behavior of compounds 4 and 20 towards hBChE. The observed balance of the inhibitory potencies versus the relevant targets indicates the thioxanthene-9-one derivatives as potential MTDLs for AD therapy, provided that the safety window will be improved by further structural variations, currently under investigation.

[Image: see text] In the face of the clinical challenge posed by non-small cell lung cancer (NSCLC), the present need for new therapeutic approaches is genuine. Up to now, no proof existed that 17β-hydroxysteroid dehydrogenase type 1 (17β-HSD1) is a viable target for treating this disease. Synthesis of a rationally designed library of 2,5-disubstituted furan derivatives followed by biological screening led to the discovery of 17β-HSD1 inhibitor 1, capable of fully inhibiting human NSCLC Calu-1 cell proliferation. Its pharmacological profile renders it eligible for further in vivo studies. The very high selectivity of 1 over 17β-HSD2 was investigated, revealing a rational approach for the design of selective inhibitors. 17β-HSD1 and 1 hold promise in fighting NSCLC.

Introduction: The 1,3-dipolar cycloaddition reactions of nitrile oxides formed in situ (in the presence of NCS and Et3N) from the oximes of (purin-9-yl)acetaldehyde or (coumarinyloxy)acetaldehyde with allyloxycoumarins or 9-allylpurines, respectively resulted in 3,5-disubstituted isoxazolines. The similar reactions of propargyloxycoumarins or 9-propargylpurines led to 3,5-disubstituted isoxazoles by treatment with PIDA and catalytic amount of TFA. Methods: The new compounds were tested in vitro as antioxidant agents and inhibitors of soybean lipoxygenase LO, AChE and MAO-B. Results: The majority of the compounds showed significant hydroxyl radical scavenging activity. Compounds 4k and 4n presented LO inhibitory activity. Conclusion: Compound 13e presents an antioxidant significant profile combining anti-LO, anti-AChE and anti-MAO-B activities.

The quinoline motif fused with other heterocyclic systems plays an important role in the field of anticancer drug development. An extensive series of tetracyclic quinolino[3,4-b]quinoxalines N-5 or C-6 substituted with basic side chain and a limited number of tricyclic pyridazino[4,3-c]quinolines N-6 substituted were designed, synthesized and evaluated for topoisomerase IIα (Topo IIα) inhibitory activity, ability to bind and stabilize G-quadruplex structures and cytotoxic properties against two human cancer cell lines (HeLa and MCF-7). Almost all of the tested agents showed a high activity as Topo IIα inhibitors and G-quadruplex stabilizers. Among all the derivatives studied, the quinolino[3,4-b]quinoxalines 11 and 23, N-5 and C-6 substituted respectively, stand out as the most promising compounds. Derivative 11 resulted a selective binder to selected G-quadruplex sequences, while derivative 23 displayed the most interesting Topo IIα inhibitory activity (IC50 = 5.14 μM); both showed high cytotoxic activity (IC50 HeLa = 2.04 μM and 2.32 μM, respectively).

Aiming at modulating two key enzymatic targets for Alzheimers disease (AD), i.e., acetylcholinesterase (AChE) and monoamine oxidase B (MAO B), a series of multitarget ligands was properly designed by linking the 3,4-dimethylcoumarin scaffold to 1,3- and 1,4-substituted piperidine moieties, thus modulating the basicity to improve the hydrophilic/lipophilic balance. After in vitro enzymatic inhibition assays, multipotent inhibitors showing potencies in the nanomolar and in the low micromolar range for hMAO B and eeAChE, respectively, were prioritized and evaluated in human SH-SY5Y cell-based models for their cytotoxicity and neuroprotective effect against oxidative toxins (H2O2, rotenone, and oligomycin-A). The present study led to the identification of a promising multitarget hit compound (5b) exhibiting high hMAO B inhibitory activity (IC50 = 30 nM) and good MAO B/A selectivity (selectivity index, SI = 94) along with a micromolar eeAChE inhibition (IC50 = 1.03 mu M). Moreover, 5b behaves as a water-soluble, brain-permeant neuroprotective agent against oxidative insults without interacting with P-gp efflux system.

Computational methods have advanced toxicology towards the development of target-specific models based on a clear cause-effect rationale. However, the predictive potential of these models presents strengths and weaknesses. On the good side, in silico models are valuable cheap alternatives to in vitro and in vivo experiments. On the other, the unconscious use of in silico methods can mislead end-users with elusive results. The focus of this review is on the basic scientific and regulatory recommendations in the derivation and application of computational models. Attention is paid to examine the interplay between computational toxicology and drug discovery and development. Avoiding the easy temptation of an overoptimistic future, we report our view on what can, or cannot, realistically be done. Indeed, studies of safety/toxicity represent a key element of chemical prioritization programs carried out by chemical industries, and primarily by pharmaceutical companies.

Quantitative Structure-Activity Relationships are widely acknowledged predictive methods employed, for years, in organic and medicinal chemistry. More recently, they have assumed a central role also in the context of the explorative toxicology for the protection of environment and human health. However, their real-life application has not been always enthusiastically welcomed, being often retrospectively used and, thus, of limited importance for prospective goals. The need of making more trustable predictions has thus addressed studies on the so-called Applicability Domain, which represents the chemical space from which a model is derived and where a prediction is considered to be reliable. In the present study, the authors survey a number of approaches used to build the Applicability Domain. In particular, they will focus on strategies based on: a) physico-chemical, b) structural and c) response domains. Moreover, some examples integrating different strategies will be also discussed to meet the needs of both model developers and downstream users.

Inhibition data on rat monoamine oxidase B isoform of a large number of 7-metahalobenzyloxy-2H-chromen-2-one derivatives (67 compounds) carrying at position 4 a variety of substituents differing in steric, electrostatic, lipophilic and H-bonding properties, were modeled by Gaussian field-based 3D-QSAR and docking simulations carried out on rat MAO-B homology model. The computational study combining two different approaches provided easily interpretable binding modes, highlighting the dominant role of the steric effects at position 4, and guided the design of new, potent and selective MAO-B inhibitors. The 4-hydroxyethyl-, 4-chloroethyl-, 4-carboxamidoethyl-coumarin derivatives 70, 71, and 76, respectively, were endowed with high MAO-B inhibitory potency (pIC50 = 8.13, 7.89 and 7.82, respectively) and good selectivity over MAO-A (pIC50 = 5.33, 3% inhibition at 10 μM, and pIC50 = 5.37, respectively). New compounds with moderate to low MAO-B inhibitory activity were also designed and prepared to challenge the predictive power of our docking-based 3D-QSAR model. The good match between predicted and experimental pIC50 values for all the newly designed compounds confirmed the robustness of our model (r(2) = 0.856, RMSE = 0.421) and its transparent rationale in unveiling the main molecular determinants for high potency towards MAO-B.

DNA intercalating agents are a consolidated therapeutic option in the treatment of tumor diseases. Starting from previous findings in the antiproliferative efficacy of a series of indeno[1,2-c]cinnoline-11-one derivatives, we performed a suitable decoration of this scaffold by means of a simple and straightforward chemistry, aiming to a) enlarge the planar core to a pentacyclic benzo[h]indeno[1,2-c]cinnoline-13-one and b) introduce a basic head tethered through a simple polymethylene chain. In fluorescence melting and fluorescence intercalator displacement assays, these new compounds displayed fair to very good intercalating properties on different nucleic acid strands, with preference for G-quadruplex sequences. Inhibition of human topoisomerase IIα and antiproliferative assays on HeLa and MCF7 tumor cell lines outlined a multitarget antiproliferative profile for tetracyclic 6 and pentacyclic derivative 20, both bearing a N,N-dimethylamine as the protonatable moiety. Particularly, compound 6 displayed a very potent inhibition of tumor cell proliferation, while 20 returned the highest thermal stabilization in melting experiments. In summary, these results outlined a potential of such highly planar scaffolds for nucleic acid binding and antiproliferative effects.

In Alzheimer's disease (AD), multiple factors account for the accumulation of neurocellular changes, which may begin several years before symptoms appear. The most important pathogenic brain changes that are contributing to the development of AD are the formation of the cytotoxic β-amyloid aggregates and of the neurofibrillary tangles, which originate from amyloid-β peptides and hyperphosphorylated tau protein, respectively. New therapeutic agents that target both major pathogenic mechanisms may be particularly efficient. In this study, we introduce bis(hydroxyphenyl)-substituted thiophenes as a novel class of selective, dual inhibitors of the tau kinase Dyrk1A and of the amyloid-β aggregation.

Repeated dose toxicity is of the utmost importance to characterize the toxicological profile of a chemical after repeated administration. Its evaluation refers to the Lowest-Observed-(Adverse)-Effect-Level (LO(A)EL) explicitly requested in several regulatory contexts, such as REACH and EC Regulation 1223/2009 on cosmetic products. So far in vivo tests have been the sole viable option to assess repeated dose toxicity. We report a customized k-nearest neighbors (k-NN) approach for predicting sub-chronic oral toxicity in rats. A training set of 254 chemicals was used to derive models whose robustness was challenged through leave-one-out cross-validation. Their predictive power was evaluated on an external dataset comprising 179 chemicals. Despite the intrinsically heterogeneous nature of the data, our models give promising results, with q2 >= 0.632 and external r2 >= 0.543. The confidence in prediction was ensured by implementing restrictive user-adjustable rules, excluding suspicious chemicals irrespective of the goodness in their prediction. Comparison with the very few LO(A)EL predictive models in the literature indicates that the results of the present analysis can be valuable in prioritizing the safety assessment of chemicals and thus making safe decisions and justifying waiving animal tests according to current regulations concerning chemical safety.

The CORAL (CORrelation And Logic) software can be used to build up the quantitative structure–property/activity relationships (QSPR/QSAR) with optimal descriptors calculated with the simplified molecular input line entry system. We used the CORAL to build up QSAR for toxicity of psychotropic drugs (phenothiazines, antidepressants, and anxiolitics). The acute toxicity data of drugs to mouse (oral LD50, mg/kg) were taken in the literature. These values were converted into pLD50, i.e., negative decimal logarithm of the LD50 expressed in mmol/kg. The statistical quality of the models for “invisible” validation set (compounds which are not involved in building up model) is quite good.

It has long been considered that the most significant risks for breast cancer are gender and age but, as many other tumors, this cancer has also been undeniably linked to gene mutations. The vast majority of breast cancers in postmenopausal women are estrogen-responsive, a hormone which is biosynthesized from blood-circulating androgens through an aromatization reaction, catalyzed by aromatase (AR). One strategy, therefore, to combat breast cancer, has been to find compounds that can inhibit the activity of aromatase to reduce estrogen levels.The authors provide a broad and updated overview of the general structure-activity relationships and on the latest ligand- and structure-based approaches applied to the discovery of potent, selective and safer breast cancer drugs. Specifically the authors review the most consolidated techniques, based on structure-activity relationships, pharmacophore mapping, rigid and flexible molecular docking, as well as sophisticated and reliable protocols simulating critical biological events.The recently solved X-ray structures of aromatase represent solid milestones to breathe new life into the search of newer chemotypes with reduced risks of cross-reactivity toward other CYPs and safer pharmacological profiles. We anticipate that great benefits will arrive from the wealth of information obtained by integrating genomics, site-directed mutagenesis experiments with protein modeling. Furthermore, we welcome the advent of GPU technology that, in conjunction with dedicated algorithms, grants scientists an unprecedented point of view on physiologically relevant phenomena, occurring on the µs time scale, such as ligand binding/unbinding.

Matrix metalloproteinases (MMPs) are attractive biological targets that play a key role in many physiopathological processes such as degradation of extracellular matrix proteins, release and cleavage of cell-surface receptors, tumour progression, homeostatic regulation and innate immunity. A series of 5-hydroxy, 5-substituted pyrimidine-2,4,6-triones were rationally designed, prepared and tested as inhibitors of gelatinases MMP-2 and MMP-9 and collagenase MMP-8. On one side, the presence of the 5-hydroxyl group, that represents an typical feature of this class of compounds, ensured an attractive pharmacokinetic profile while on the other suitably substituted biaryl molecular fragments, attached to position 5 through a ketomethylene linker, guaranteed favourable interaction in the deep region of the S(1)' enzymatic subsite. This rational design led to the discovery of highly potent MMP inhibitors. In particular, biphenyl derivatives bearing at the para position COCH(3) and OCF(3) substituents permitted to inhibit gelatinases MMP-2 and MMP-9, with IC(50) values as low as 30 nM and 21 nM, respectively, whereas the introduction at the same position of the bulkier SO(2)CH(3) group afforded a potent collagenase MMP-8 inhibitor with an IC(50) value equal to 66 nM. Molecular docking simulations allowed us to elucidate key interactions driving the binding of the top active compounds towards their preferred MMP target.

A series of 3,4-dihydroquinazoline derivatives consisting of the selected compounds from our chemical library on the diversity basis and the new synthetic compounds were in vitro tested for their inhibitory activities for both acetylcholinesterase (AChE, from electric eel) and butyrylcholinesterase (BChE, from equine serum) enzymes. It was discovered that most of the compounds displayed weak AChE and strong BuChE inhibitory activities. In particular, compound 8b and 8d were the most active compounds in the series against BChE with IC50 values of 45nM and 62nM, as well as 146- and 161-fold higher affinity to BChE, respectively. To understand the excellent activity of these compounds, molecular docking simulations were performed to get better insights into the mechanism of binding of 3,4-dihydroquinazoline derivatives. As expected, compound 8b and 8d bind to both catalytic anionic site (CAS) and peripheral site (PS) of BChE with better interaction energy values than AChE, in agreement with our experimental data. Furthermore, the non-competitive/mixed-type inhibitions of both compounds further confirmed their dual binding nature in kinetic studies.

This is the peer reviewed version of the following article: Domínguez, J., Fernández-Nieto, F., Brea, J., Catto, M., Paleo, M., & Porto, S. et al. (2016). 8-Aminomethyl-7-hydroxy-4-methylcoumarins as Multitarget Leads for Alzheimer's Disease. Chemistryselect, 1(11), 2742-2749, which has been published in final form at https://doi.org/10.1002/slct.201600735. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions This work is part of our ongoing research in the discovery of multitarget therapeutic agents for Alzheimer's disease (AD). A literature screening, based on our recently proposed pharmacophore, led to the identification of 8‐aminomethyl‐7‐hydroxy‐4‐methyl coumarins as potential multitarget leads for AD. The results of a computer‐assisted protocol developed by us to validate multitarget hits for AD indicated that our coumarin candidates were viable leads only for AChE inhibition as later validated by biological assays. The results of BChE binding and propidium displacement assays indicate that our first generation compounds bind to the PAS site in AChE. We designed new generations of coumarin derivatives with a longer substituent at position 8 aimed at leads with more efficient interaction at the catalytic anionic site (CAS). Inhibition data and docking simulations indicated that an anilino‐capping group reached the CAS region of AChE and determined also a higher inhibitory potency towards BChE. The best compound obtained, with a N‐benzylpiperidine fragment, displayed sub‐micromolar affinity for AChE, affinity for BChE, and precluded Aβ‐amyloid aggregation with a potency similar to that of 9,10‐anthraquinone, making it a multitarget lead viable for further improvement Financial support from the Ministerio de Economia y Competitividad of Spain (Project CTQ2014‐55208‐P) and the Xunta de Galicia (10CSA209063PR and GRC2014/029) is gratefully acknowledged. The Italian authors thank the University of Bari for partial financial support (Fondi di Ateneo 2014–2015) SI

Predictive toxicology is a new emerging multifaceted research field aimed at protecting human health and environment from risks posed by chemicals. Such issue is of extreme public relevance and requires a multidisciplinary approach where the experience in medicinal chemistry is of utmost importance. Herein, we will survey some basic recommendations to gather good data and then will review three recent case studies to show how strategies of ligand- and structure-based molecular design, widely applied in medicinal chemistry, can be adapted to meet the more restrictive scientific and regulatory goals of predictive toxicology. In particular, we will report: Docking-based classification models to predict the estrogenic potentials of chemicals. Predicting the bioconcentration factor using biokinetics descriptors. Modeling oral sub-chronic toxicity using a customized k-nearest neighbors (k-NN) approach.

The need for developing real disease-modifying drugs against neurodegenerative syndromes, particularly Alzheimer’s disease (AD), shifted research towards reliable drug discovery strategies to unveil clinical candidates with higher therapeutic efficacy than single-targeting drugs. By following the multi-target approach, we designed and synthesized a novel class of dual acetylcholinesterase (AChE)-monoamine oxidase B (MAO-B) inhibitors through the decoration of the 2H-chromen-2-one skeleton. Compounds bearing a propargylamine moiety at position 3 displayed the highest in vitro inhibitory activities against MAO-B. Within this series, derivative 3h emerged as the most interesting hit compound, being a moderate AChE inhibitor (IC50 = 8.99 µM) and a potent and selective MAO-B inhibitor (IC50 = 2.8 nM). Preliminary studies in human neuroblastoma SH-SY5Y cell lines demonstrated its low cytotoxicity and disclosed a promising neuroprotective effect at low doses (0.1 µM) under oxidative stress conditions promoted by two mitochondrial toxins (oligomycin-A and rotenone). In a Madin-Darby canine kidney (MDCK)II-MDR1 cell-based transport study, Compound 3h was able to permeate the BBB-mimicking monolayer and did not result in a glycoprotein-p (P-gp) substrate, showing an efflux ratio = 0.96, close to that of diazepam SI

Predictive toxicology is a new emerging multifaceted research field aimed at protecting human health and environment from risks posed by chemicals. Such issue is of extreme public relevance and requires a multidisciplinary approach where the experience in medicinal chemistry is of utmost importance. Herein, we will survey some basic recommendations to gather good data and then will review three recent case studies to show how strategies of ligand- and structure-based molecular design, widely applied in medicinal chemistry, can be adapted to meet the more restrictive scientific and regulatory goals of predictive toxicology. In particular, we will report: Docking-based classification models to predict the estrogenic potentials of chemicals. Predicting the bioconcentration factor using biokinetics descriptors. Modeling oral sub-chronic toxicity using a customized k-nearest neighbors (k-NN) approach.

Since Hansch's extra thermodynamic multi-parameter approach, originally coined as Linear Free Energy Relationship, great efforts in medicinal chemistry have been made to properly estimate the binding free energy. Despite the often small amount, its value is however very critical in determining a successful binding. As a result, its correct estimation may provide a guide for a prospective rational drug design. The calculation of the absolute binding free energies is however a very challenging task as it requires a rigorous treatment of a number of physical terms that are both very time demanding and to some extent not immediately interpretable. In view of this, the introduction of some numerical approximations has permitted to develop the so called Linear Interaction Energy method that, at present, constitutes the best compromise among accuracy, speed of computation and easy interpretation. The initially developed Linear Interaction Energy method was subsequently revisited and several important improvements have been made. Significant examples are the Extended Linear Response, the surface generalized Born LIE, the molecular mechanics generalized Born surface area, the linear interaction energy in continuum electrostatics as well as its quantum mechanics variant. Principles and selected applications of these methods will be herein reviewed.

Aquaporins (AQPs) play a physiological role in several organs and tissues, and their alteration is associated with disorders of water regulation. The identification of molecular interactions, which are crucial in determining the rate of water flux through the channel, is of pivotal role for the discovery of molecules able to target those interactions and therefore to be used for pathologies ascribable to an altered AQP-dependent water balance. In the present study, a mutational screening of human aquaporin-4 (AQP4) gene was performed on subjects with variable degrees of hearing loss. One heterozygous missense mutation was identified in a Spanish sporadic case, leading to an Asp/Glu amino acid substitution at position 184 (D184E). A BLAST analysis revealed that the amino acid D184 is conserved across species, consistently with a crucial role in the structure/function of AQP4 water channels. The mutation induces a significant reduction in water permeability as measured by the Xenopus laevis oocytes swelling assay and by the use of mammalian cells by total internal reflection microscopy. By Western blot, immunofluorescence and 2D Blue Native/SDS-PAGE we show that the reduction in water permeability is not ascribable to a reduced expression of AQP4 mutant protein or to its incorrect plasma membrane targeting and aggregation into orthogonal arrays of particles. Molecular dynamics simulation provided a molecular explanation of the mechanism whereby the mutation induces a loss of function of the channel. Substituting glutamate for aspartate affects the mobility of the D loop, which acquires a higher propensity to equilibrate in a “closed conformation”, thus affecting the rate of water flux. We speculate that this mutation, combined with other genetic defects or concurrently with certain environmental stimuli, could confer a higher susceptibility to deafness.

Drug discovery and development is a typical multi-objective problem and its successes or failures depend on the simultaneous control of numerous, often conflicting, molecular and pharmacological properties. Multi-objective optimization strategies represent a new approach to capture the occurrence of varying optimal solutions based on trade-offs among the objectives taken into account. In view of this, multi-objective optimization aims to discover a set of satisfactory compromises that may in turn be used to find the global optimal solution by optimizing numerous dependent properties simultaneously.The authors review the potential of multi-objective strategies in a number of fields including: drug library design; substructure mining; the derivation of quantitative structure-activity relationship models; ranking of docking poses. The authors also discuss the potential of multi-objective strategies in controlling competing properties for absorption, distribution, metabolism and elimination/toxicity optimization.It is very clear to those who work in drug discovery and development that the success of rational drug design is largely dependent on the control of a number of, often conflicting, objectives. Therefore, multi-objective optimization methods, which have recently been introduced to the field of molecular discovery, represent the ultimate frontier in chemoinformatics. The widespread use of these multi-objective techniques has provided new opportunities in medicinal chemistry as seen through its use in a number of applications for chemoinformatics both within academia and the pharmaceutical industry.

Scaffold hopping of known active compounds is becoming a successful strategy for the development of new molecular series. [1, 2] This strategy is based on the assumption that the same biological activity can be exerted by newly designed compounds that maintain some essential features of the template but are structurally different otherwise. [3] Playing a central role in modern medicinal chemistry, scaffold hopping is based on the concept of molecular similarity and thus involves the use of techniques such as shape matching, pharmacophore and similarity searching, fragment and bioisosteric replacement. [4] At present, many examples of successful scaffold hopping are known. A milestone in this field has been the identification of GABA-receptor antagonists based on the 1,4-benzodiazepine molecular scaffold. After its discovery in the Fifties, many attempts were undertaken to improve both pharmacokinetic and pharmacodynamic profiles of benzodiazepines initially by exploring various substituents and later by scaffold hopping to identify completely new core structures. Compounds with a novel scaffold different from that of benzodiazepines are Zopiclone, Zolpidem and Zaleplon. [5] Among other drugs dis

The design, synthesis, and biological evaluation of a series of new aromatase (AR, CYP19) inhibitors bearing an imidazole ring linked to a 7-substituted coumarin scaffold at position 4 (or 3) are reported. Many compounds exhibited an aromatase inhibitory potency in the nanomolar range along with a high selectivity over 17-α-hydroxylase/C17-20 lyase (CYP17). The most potent AR inhibitor was the 7-(3,4-difluorophenoxy)-4-imidazolylmethyl coumarin 24 endowed with an IC(50) = 47 nM. Docking simulations on a selected number of coumarin derivatives allowed the identification of the most important interactions driving the binding and clearly indicated the allowed and disallowed regions for appropriate structural modifications of coumarins and closely related heterocyclic molecular scaffolds.

A series of novel acrylic acid derivatives bearing at the 3 position thienyl, furfuryl and 3,5-ditert-butyl-4-hydroxyphenyl substituents have been designed, synthesized and tested as potential dual lipoxygenase/cyclooxygenase-1 (LOX/COX-1) inhibitors and as antioxidant and anti-inflammatory agents. Some compounds have shown moderate antioxidant and COX-1 inhibitory activities, very good anti-inflammatory activity and an inhibition of soybean lipoxygenase (LOX) higher than caffeic acid. In particular, compound 4I disclosed a moderate in vitro LOX inhibition with an IC(50) = 100 μM whereas compounds 1I and 2II exhibited the best, albeit poor, activity as COX-1 inhibition (75% inhibition at 100 μM). Good radical scavenging properties were shown by compounds 4I, 3I and 1II. Docking simulations performed on LOX inhibitor 4I and COX-1 inhibitor 1I indicated that hydrophobic key interactions may govern the enzyme-inhibitor binding.

A series of isatin-3-arylhydrazones were synthesized and evaluated in vitro as inhibitors of Aβ(1-40) aggregation using a thioflavin T fluorescence method. An exploration of the effects on Aβ(1-40) aggregation of a number of diverse substituents at phenylhydrazone group and 5,6- positions of the indolinone nucleus led us to single out some new anti-aggregating compounds with IC(50) values in the low micromolar range. The most active compounds carry methoxy- or hydroxy- substituents in the indolinone 5,6-positions and lipophilic groups such as iPr and Cl at 4'- and 3'-position, respectively, of the phenylhydrazone moiety. Two derivatives are noteworthy, namely 18 (IC(50) = 0.4 μM) and 42 (IC(50) = 1.1 μM). The in vitro effects of the highly active, water soluble, compound 42 on the temporal evolution of Aβ(1-40) fibrils formation were further investigated by circular dichroism spectroscopy, transmission electron microscopy and dynamic light scattering studies, which clearly showed that this compound delayed and lowered the amyloid fibril formation.

A large series of substituted coumarins linked through an appropriate spacer to 3-hydroxy-N,N-dimethylanilino or 3-hydroxy-N,N,N-trialkylbenzaminium moieties were synthesized and evaluated as acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitors. The highest AChE inhibitory potency in the 3-hydroxy-N,N-dimethylanilino series was observed with a 6,7-dimethoxy-3-substituted coumarin derivative, which, along with an outstanding affinity (IC(50)=0.236 nM) exhibits excellent AChE/BChE selectivity (SI>300 000). Most of the synthesized 3-hydroxy-N,N,N-trialkylbenzaminium salts display an AChE affinity in the sub-nanomolar to picomolar range along with excellent AChE/BChE selectivities (SI values up to 138 333). The combined use of docking and molecular dynamics simulations permitted us to shed light on the observed structure-affinity and structure-selectivity relationships, to detect two possible alternative binding modes, and to assess the critical role of pi-pi stacking interactions in the AChE peripheral binding site.

A small molecular library of 40 pyrimidine, pyrazole, and isoxazole derivatives, bearing structural features for a promising binding of therapeutically interesting enzymes, was designed and prepared. An efficient and straightforward solid phase synthesis was envisaged and carried out on a Rink amide resin. The assistance of microwave heating in any step reduced the reaction time, increased the reaction yields, and allowed an easy work-up and purification of the targeted compounds.

Many naturally occurring substances, traditionally used in popular medicines around the world, contain the coumarin moiety. Coumarin represents a privileged scaffold for medicinal chemists, because of its peculiar physicochemical features, and the versatile and easy synthetic transformation into a large variety of functionalized coumarins. As a consequence, a huge number of coumarin derivatives have been designed, synthesized, and tested to address many pharmacological targets in a selective way, e.g., selective enzyme inhibitors, and more recently, a number of selected targets (multitarget ligands) involved in multifactorial diseases, such as Alzheimer’s and Parkinson’s diseases. In this review an overview of the most recent synthetic pathways leading to mono- and polyfunctionalized coumarins will be presented, along with the main biological pathways of their biosynthesis and metabolic transformations. The many existing and recent reviews in the field prompted us to make some drastic selections, and therefore, the review is focused on monoamine oxidase, cholinesterase, and aromatase inhibitors, and on multitarget coumarins acting on selected targets of neurodegenerative diseases.

A series of 27 benzamidine inhibitors covering a wide range of biological activity and chemical diversity was analysed to derive a Linear Interaction Energy in Continuum Electrostatics (LIECE) model for analysing the thrombin inhibitory activity. The main interactions occurring at the thrombin binding site and the preferred binding conformations of inhibitors were explicitly biased by including into the LIECE model 10 compounds extracted from X-ray solved thrombin-inhibitor complexes available from the Protein Data Bank (PDB). Supported by a robust statistics (r(2) = 0.698; q(2) = 0.662), the LIECE model was successful in predicting the inhibitory activity for about 76% of compounds (r (ext) (2)or = 0.600) from a larger external test set encompassing 88 known thrombin inhibitors and, more importantly, in retrieving, at high sensitivity and with better performance than docking and shape-based methods, active compounds from a thrombin combinatorial library of 10240 mimetic chemical products. The herein proposed LIECE model has the potential for successfully driving the design of novel thrombin inhibitors with benzamidine and/or benzamidine-like chemical structure.

In an effort to discover novel selective monoamine oxidase (MAO) B inhibitors with favorable physicochemical and pharmacokinetic profiles, 7-[(m-halogeno)benzyloxy]coumarins bearing properly selected polar substituents at position 4 were designed, synthesized, and evaluated as MAO inhibitors. Several compounds with MAO-B inhibitory activity in the nanomolar range and excellent MAO-B selectivity (selectivity index SI > 400) were identified. Structure-affinity relationships and docking simulations provided valuable insights into the enzyme-inhibitor binding interactions at position 4, which has been poorly explored. Furthermore, computational and experimental studies led to the identification and biopharmacological characterization of 7-[(3-chlorobenzyl)oxy]-4-[(methylamino)methyl]-2H-chromen-2-one methanesulfonate 22b (NW-1772) as an in vitro and in vivo potent and selective MAO-B inhibitor, with rapid blood-brain barrier penetration, short-acting and reversible inhibitory activity, slight inhibition of selected cytochrome P450s, and low in vitro toxicity. On the basis of this preliminary preclinical profile, inhibitor 22b might be viewed as a promising clinical candidate for the treatment of neurodegenerative diseases.

A multiobjective optimization algorithm was proposed for the automated integration of structure- and ligand-based molecular design. Driven by a genetic algorithm, the herein proposed approach enabled the detection of a number of trade-off QSAR models accounting simultaneously for two independent objectives. The first was biased toward best regressions among docking scores and biological affinities; the second minimized the atom displacements from a properly established crystal-based binding topology. Based on the concept of dominance, 3D QSAR equivalent models profiled the Pareto frontier and were, thus, designated as nondominated solutions of the search space. K-means clustering was, then, operated to select a representative subset of the available trade-off models. These were effectively subjected to GRID/GOLPE analyses for quantitatively featuring molecular determinants of ligand binding affinity. More specifically, it was demonstrated that a) diverse binding conformations occurred on the basis of the ligand ability to profitably contact different part of protein binding site; b) enzyme selectivity was better approached and interpreted by combining diverse equivalent models; and c) trade-off models were successful and even better than docking virtual screening, in retrieving at high sensitivity active hits from a large pool of chemically similar decoys. The approach was tested on a large series, very well-known to QSAR practitioners, of 3-amidinophenylalanine inhibitors of thrombin and trypsin, two serine proteases having rather different biological actions despite a high sequence similarity.

A new method was implemented in the in-house program @lic& to rationally combine structure- and ligand-based design through nondeterministic rescoring of docking poses for the automated generation of structural alignments of a series of benzamidine compounds acting as protease inhibitors. Such alignments enable 3D-QSAR models to explain enzyme selectivity and to retrieve with high sensitivity active hits from a pool of 260 structurally-related benzamidine derivatives.

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.