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Immunoproteasome inhibition is a promising strategy for the treatment of hematological malignancies, autoimmune diseases, and inflammatory diseases. The design of non-covalent inhibitors of the immunoproteasome β1i/β5i catalytic subunits could be a novel approach to avoid the drawbacks of the known covalent inhibitors, such as toxicity due to off-target binding. In this work, we report the biological evaluation of thirty-four compounds selected from a commercially available collection. These hit compounds are the outcomes of a virtual screening strategy including a dynamic pharmacophore modeling approach onto the β1i subunit and a pharmacophore/docking approach onto the β5i subunit. The computational studies were first followed by in vitro enzymatic assays at 100 μM. Only compounds capable of inhibiting the enzymatic activity by more than 50% were characterized in detail using Tian continuous assays, determining the dissociation constant (Ki) of the non-covalent complex where Ki is also the measure of the binding affinity. Seven out of thirty-four hits showed to inhibit β1i and/or β5i subunit. Compound 3 is the most active on the β1i subunit with Ki = 11.84 ± 1.63 µM, and compound 17 showed Ki = 12.50 ± 0.77 µM on the β5i subunit. Compound 2 showed inhibitory activity on both subunits (Ki = 12.53 ± 0.18 and Ki = 31.95 ± 0.81 on the β1i subunit and β5i subunit, respectively). The induced fit docking analysis revealed interactions with Thr1 and Phe31 of β1i subunit and that represent new key residues as reported in our previous work. Onto β5i subunit, it interacts with the key residues Thr1, Thr21, and Tyr169. This last hit compound identified represents an interesting starting point for further optimization of β1i/β5i dual inhibitors of the immunoproteasome.

Cystic Fibrosis (CF) is an autosomal recessive genetic disease caused by mutations in the CFTR gene, coding for the CFTR chloride channel. About 10% of the CFTR gene mutations are “stop” mutations that generate a premature termination codon (PTC), thus synthesizing a truncated CFTR protein. A way to bypass PTC relies on ribosome readthrough, which is the ribosome’s capacity to skip a PTC, thus generating a full-length protein. “TRIDs” are molecules exerting ribosome readthrough; for some, the mechanism of action is still under debate. We investigate a possible mechanism of action (MOA) by which our recently synthesized TRIDs, namely NV848, NV914, and NV930, could exert their readthrough activity by in silico analysis and in vitro studies. Our results suggest a likely inhibition of FTSJ1, a tryptophan tRNA-specific 2′-O-methyltransferase.

Cyclin Dependent Kinases-2 (CDK2) are members of serine/threonine protein kinases family. They play an important role in the regulation events of the eukaryotic cell division cycle, especially during the G1 to S phase transition. Experimental evidence indicate that excessive expression of CDK2s should cause abnormal cell cycle regulation. Therefore, since a long time, CDK2s have been considered potential therapeutic targets for cancer therapy. In this work, onehundred and forty-nine complexes of inhibitors bound in the CDK2-ATP pocket were submitted to short MD simulations (10ns) and free energy calculation. Comparison with experimental data (Ki, Kd and pIC50) revealed that short simulations are exhaustive to examine the crucial ligand-protein interactions within the complexes. Information collected on MD simulations of protein-ligand complexes has been used to perform a molecular modelling approach that incorporates flexibility into structure-based pharmacophore modelling (Common Hits Approach, CHA). The high number of pharmacophore models resulting from the MD simulation was thus reduced to a few representative groups of pharmacophore models. The performance of the models has been assessed by using the ROC curves analysis. This definitive set of validated pharmacophore models could be used to screen in-house and/or commercial datasets for detection of new CDK-2 inhibitors. We provide the models to all the researchers involved in this field.

Background: Indicaxanthin, a betaxanthin belonging to the betalain class of compounds, has been recently demonstrated to exert significant antiproliferative effects inducing apoptosis of human melanoma cells through the inhibition of NF-κB as the predominant pathway. Specifically, Indicaxanthin inhibited IκBα degradation in A375 cells. In resting cells, NF-κB is arrested in the cytoplasm by binding to its inhibitor protein IκBα. Upon stimulation, IκBα is phosphorylated by the IKK complex, and degraded by the proteasome, liberating free NF-κB into the nucleus to initiate target gene transcription. Inhibition of the IKK complex leads to the arrest of the NF-κB pathway.Methods: To acquire details at the molecular level of Indicaxanthin’s inhibitory activity against hIKKβ, molecular modeling and simulation techniques including induced-fit docking (IFD), binding pose metadynamics (BPMD), molecular dynamics simulations, and MM-GBSA (molecular mechanics-generalized Born surface area continuum solvation) have been performed.Results: The computational calculations performed on the active and inactive form, and the allosteric binding site of hIKKβ, revealed that Indicaxanthin inhibits prevalently the active form of the hIKKβ. MM-GBSA computations provide further evidence of Indicaxanthin’s stability inside the active binding pocket with a binding free energy of −22.2 ± 4.3 kcal/mol with respect to the inactive binding pocket with a binding free energy of −20.7 ± 4.7 kcal/mol. BPMD and MD simulation revealed that Indicaxanthin is likely not an allosteric inhibitor of hIKKβ.Conclusion: As a whole, these in silico pieces of evidence show that Indicaxanthin can inhibit the active form of the hIKKβ adding novel mechanistic insights on its recently discovered ability to impair NF-κB signaling in melanoma A375 cells. Moreover, our results suggest the phytochemical as a new lead compound for novel, more potent IKKβ inhibitors to be employed in the treatment of cancer and inflammation-related conditions.

Background: G-quadruplex (G4) forming sequences are recurrent in telomeres and promoter regions of several protooncogenes. In normal cells, the transient arrangements of DNA in G-tetrads may regulate replication, transcription, and translation processes. Tumors are characterized by uncontrolled cell growth and tissue invasiveness and some of them are possibly mediated by gene expression involving G-quadruplexes. The stabilization of G-quadruplex sequences with small molecules is considered a promising strategy in anticancer targeted therapy. Methods: Molecular virtual screening allowed us identifying novel symmetric bifunctionalized naphtho[1,2-b:8,7-b’]dithiophene ligands as interesting candidates targeting h-Telo and c-MYC G-quadruplexes. A set of unexplored naphtho-dithiophene derivatives has been synthesized and biologically tested through in vitro antiproliferative assays and spectroscopic experiments in solution. Results: The analysis of biological and spectroscopic data highlighted noteworthy cytotoxic effects on HeLa cancer cell line (GI50 in the low μM range), but weak interactions with G-quadruplex c-MYC promoter. Conclusions: The new series of naphtho[1,2-b:8,7-b’]dithiophene derivatives, bearing the pharmacophoric assumptions necessary to stabilize G-quadruplexes, have been designed and successfully synthesized. The interesting antiproliferative results supported by computer aided rational approaches suggest that these studies are a significant starting point for a lead optimization process and the isolation of a more efficacious set of G-quadruplexes stabilizers.

The selective inhibition of immunoproteasome is a valuable strategy to treat autoimmune, inflammatory diseases, and hematologic malignancies. Recently, a new series of amide derivatives as non-covalent inhibitors of the β1i subunit with Ki values in the low/submicromolar ranges have been identified. Here, we investigated the binding mechanism of the most potent and selective inhibitor, N-benzyl-2-(2-oxopyridin-1(2H)-yl)propanamide (1), to elucidate the steps from the ligand entrance into the binding pocket to the ligand-induced conformational changes. We carried out a total of 400 ns of MD-binding analyses, followed by 200 ns of plain MD. The trajectories clustering allowed identifying three representative poses evidencing new key interactions with Phe31 and Lys33 together in a flipped orientation of a representative pose. Further, Binding Pose MetaDynamics (BPMD) studies were performed to evaluate the binding stability, comparing 1 with four other inhibitors of the β1i subunit: N-benzyl-2-(2-oxopyridin-1(2H)-yl)acetamide (2), N-cyclohexyl-3-(2-oxopyridin-1(2H)-yl)propenamide (3), N-butyl-3-(2-oxopyridin-1(2H)-yl)propanamide (4), and (S)-2-(2-oxopyridin-1(2H)-yl)-N,4-diphenylbutanamide (5). The obtained results in terms of free binding energy were consistent with the experimental values of inhibition, confirming 1 as a lead compound of this series. The adopted methods provided a full dynamic description of the binding events, and the information obtained could be exploited for the rational design of new and more active inhibitors.

Over the latest years phytochemical consumption has been associated to a decreased risk of both the onset and the development of a number of pathological conditions. In this context indicaxanthin, a betalain pigment from Opuntia ficus-indica fruit, has been the object of sound research. Explored, at first, for its mere antioxidant potential, Indicaxanthin is now regarded as a redox-active compound able to exert significant poly-pharmacological effects against several targets in a number of experimental conditions both in vivo and in vitro. This paper aims to provide an overview on the therapeutical effects of indicaxanthin, ranging from the anti-inflammatory to the neuro-modulatory and anti-tumoral ones and favored by its high bioavailability. Moreover, biochemical and molecular modelling investigations are aimed to identify the pharmacological targets the compound is able to interact with and to address the challenging development in the future research.

E’ noto in letteratura che Ataluren (acido 5-(fluorofenil)-1,2,4-ossadiazolil-benzoico) sia in grado di sopprimere le mutazioni non senso favorendo il readthrough dei codoni di stop prematuri, anche se il suo meccanismo di azione non risulta ancora chiaro. La probabile interazione tra Ataluren e CTFR-mRNA è stata precedentemente studiata mediante dinamica molecolare. In questo studio1, abbiamo esteso il modeling del probabile meccanismo di azione di Ataluren mediante approcci computazionali completementari, quali Induced Fit Docking (IFD), Quantum Polarized Ligand Docking (QPLD), metodi MM-GBSA e mutagenesi computazionale. Oltre a considerare il CTFR-mRNA, sono stati presi in considerazione altri target implicati nel processo di traduzione, quali la subunità 16S dell’rRNA batterico e la subunità 18S dell’rRNA eucariotico, che sono target comprovati di molti aminoglicosidi noti per la loro capacità di sopprimere l’attività di correzione svolta normalmente dal ribosoma; il fattore di rilascio eucariotico eRF1, per valutare la potenziale influenza di Ataluren sulla fine del processo di traduzione. Inoltre, è stato effettuato un confronto tra Ataluren, un suo nuovo promettente analogo NV2445 (acido 4-(5-(o-tolil)-1,3,4-ossadiazol-2-il)benzoico)2 e una serie di antibiotici aminoglicosidici. I risultati hanno confermato che mRNA è il più probabile target per Ataluren e i suoi derivati. I calcoli di energia libera di legame effettuati in seguito alla mutagenesi computazionale, hanno mostrato che il legame tra Ataluren e il codone di stop prematuro è fortemente influenzato dalla presenza di nucleotidi ausiliari nell’intorno genico.

To date, SARS-CoV-2 infectious disease, named COVID-19 by the World Health Organization (WHO) in February 2020, has caused millions of infections and hundreds of thousands of deaths. Despite the scientific community efforts, there are currently no approved therapies for treating this coronavirus infection. The process of new drug development is expensive and time-consuming, so that drug repurposing may be the ideal solution to fight the pandemic. In this paper, we selected the proteins encoded by SARS-CoV-2 and using homology modeling we identified the high-quality model of proteins. A structure-based pharmacophore modeling study was performed to identify the pharmacophore features for each target. The pharmacophore models were then used to perform a virtual screening against the DrugBank library (investigational, approved and experimental drugs). Potential inhibitors were identified for each target using XP docking and induced fit docking. MM-GBSA was also performed to better prioritize potential inhibitors. This study will provide new important comprehension of the crucial binding hot spots usable for further studies on COVID-19. Our results can be used to guide supervised virtual screening of large commercially available libraries.

[Image: see text] Translational readthrough-inducing drugs (TRIDs) rescue the functional full-length protein expression in genetic diseases, such as cystic fibrosis, caused by premature termination codons (PTCs). Small molecules have been developed as TRIDs to trick the ribosomal machinery during recognition of the PTC. Herein we report a computational study to identify new TRID scaffolds. A pharmacophore approach was carried out on compounds that showed readthrough activity. The pharmacophore model applied to screen different libraries containing more than 87000 compounds identified four hit-compounds presenting scaffolds with diversity from the oxadiazole lead. These compounds have been synthesized and tested using the Fluc reporter harboring the UGA PTC. Moreover, the cytotoxic effect and the expression of the CFTR protein were evaluated. These compounds, a benzimidazole derivative (NV2899), a benzoxazole derivative (NV2913), a thiazole derivative (NV2909), and a benzene-1,3-disulfonate derivative (NV2907), were shown to be potential new lead compounds as TRIDs, boosting further efforts to address the optimization of the chemical scaffolds.

We compared the performance of molecular dynamics (MD)-derived pharmacophore modeling approaches, Common Hit Approach (CHA), and the Molecular dYnamics SHAred PharmacophorE (MYSHAPE) approach, with semi-flexible constrained/unconstrained docking. The aim of this work is to enrich the hit-list of a virtual screening on CDK-2 known inhibitors as a case study. Cyclin-dependent kinases (CDKs) deregulation is associated with cancer growth. CDKs are an attractive target for anticancer agents. MD-derived pharmacophore models have been obtained with LigandScout 4.2.1. Docking analysis has been performed through Glide 7.6. The results highlighted the MYSHAPE approach has a better performance when multiple target-ligand complexes are available (ROC5% = 0.99). Moreover, the use of short molecular dynamics simulations improves the performance of the screening (ROC5% = 0.98–0.99) with respect to docking (ROC5% = 0.89–0.94). Outcomes of this work indicate that these approaches are highly suitable for prospective screening by a non-expert, and could be useful for the identification of novel CDK-2 inhibitors.

Indicaxanthin is a bioactive and bioavailable betalain pigment extracted from Opuntia ficus indica fruits. Indicaxanthin has pharmacokinetics proprieties, rarely found in other phytochemicals, and it has been demonstrated that it provides a broad-spectrum of pharmaceutical activity, exerting antiproliferative, anti-inflammatory and neuromodulator effects. The discovery of the Indicaxanthin physiological targets plays an important role in understanding the biochemical mechanism. In this study, combined reverse pharmacophore mapping, reverse docking, and text-based database search identified Inositol Trisphosphate 3-Kinase (ITP3K-A), Glutamate carboxypeptidase II (GCPII), Leukotriene-A4 hydrolase (LTA4H), Phosphoserine phosphatase (HPSP), Phosphodiesterase 4D (PDE4D), AMPA receptor (GluA3 and GluA2 subunits) and Kainate receptor (GluK1 isoform) as potential targets for Indicaxanthin. These targets are implicated in neuromodulation, and inflammatory regulation, normally expressed mostly in the CNS, and expressed (or overexpressed) in cancer tissues (i.e. breast, thyroid and prostate cancer cells). Moreover, this study provides qualitative and quantitative information about dynamic interactions of Indicaxanthin at the binding site of target proteins, through molecular dynamics simulations and MM-GBSA.

Rationale The study of self-assembly process of surfactant molecules in gas phase is of actually interest for several theoretical and technological reasons related to their possible exploitation as drug carriers, protein shields and cleaning agents in gas phase. Methods Stability and fragmentation patterns of singly and multiply charged (either positively or negatively) aggregates of the surfactant (1R,2S)-dodecyl(2-hydroxy-1-methyl-2-phenylethyl) dimethyl ammonium bromide (DMEB) in gas phase have been studied by ion mobility mass spectrometry and tandem mass spectrometry. Molecular dynamics (MD) simulations of positively and negatively singly and multiply charged DMEB aggregates have been performed to get structural and energetics information. Finally, in order to get some clues on the DMEB growth mechanism, quantum mechanics calculations were carried out. Results It has been evidenced that positively and negatively singly charged aggregates at low collision energy decompose preferentially by loss of only one DMEB molecule. Increasing the collision energy, the loss of neutrals becomes increasingly abundant. Multiply charged DMEB aggregates are unstable and decompose forming singly charged monomers or dimers. MD simulations show reverse micelle like structures with polar heads somewhat segregated into the aggregate interior. Finally a good correlation between experimental and calculated collisional cross section was found. Conclusions The fragmentation pathways of DMEB charged species evidenced for singly charged aggregates features similar to that of other detergents aggregates, but multiply charged aggregates showed a system specific behavior. QM calculations on the optimized structures (21+, 31+, 11- and 21-) indicate that the most determinant interactions are due to an OH---Br hydrogen bonding that are also involved in the link between monomeric DMEB units. The MD models gave CCS values in good agreement with experimental ones, evidenced a less strict reverse micelle like structure and a quite spread bromine anion distribution.

Molecular dynamics (MD) simulations can be used, prior to virtual screening, to add flexibility to proteins and study them in a dynamic way. Furthermore, the use of multiple crystal structures of the same protein containing different co-crystallized ligands can help elucidate the role of the ligand on a protein's active conformation, and then explore the most common interactions between small molecules and the receptor. In this work, we evaluated the contribution of the combined use of MD on crystal structures containing the same protein but different ligands to examine the crucial ligand-protein interactions within the complexes. The study was carried out on peroxisome proliferator-activated receptor α (PPARα). Findings derived from the dynamic analysis of interactions were then used as features for pharmacophore generation and constraints for generating the docking grid for use in virtual screening. We found that information derived from short multiple MD simulations using different molecules within the binding pocket of the target can improve the early enrichment of active ligands in the virtual screening process for this receptor. In the end we adopted a consensus scoring based on docking score and pharmacophore alignment to rank our dataset. Our results showed an improvement in virtual screening performance in early recognition when screening was performed with the Molecular dYnamics SHAred PharmacophorE (MYSHAPE) approach.

Not always lead compound and/or derivatives are suitable for the specific biological target for which they are designed but, in some cases, discarded compounds proved to be good binders for other biological targets; therefore, drug repurposing constitute a valid alternative to avoid waste of human and financial resources. Our virtual lock-and-key methods, VLKA and Conf-VLKA, furnish a strong support to predict the efficacy of a designed drug a priori its biological evaluation, or the correct biological target for a set of the selected compounds, allowing thus the repurposing of known and unknown, active and inactive compounds.

Not always lead compound and/or derivatives are suitable for the specific biological target for which they are designed but, in some cases, discarded compounds proved to be good binders for other biological targets; therefore, drug repurposing constitute a valid alternative to avoid waste of human and financial resources. Our virtual lock-and-key methods, VLKA and Conf-VLKA, furnish a strong support to predict the efficacy of a designed drug a priori its biological evaluation, or the correct biological target for a set of the selected compounds, allowing thus the repurposing of known and unknown, active and inactive compounds.

The skin is the main barrier between the internal body environment and the external one. The characteristics of this barrier and its properties are able to modify and affect drug delivery and chemical toxicity parameters. Therefore, it is not surprising that permeability of many different compounds has been measured through several in vitro and in vivo techniques. Moreover, many different in silico approaches have been used to identify the correlation between the structure of the permeants and their permeability, to reproduce the skin behavior, and to predict the ability of specific chemicals to permeate this barrier. A significant number of issues, like interlaboratory variability, experimental conditions, data set building rationales, and skin site of origin and hydration, still prevent us from obtaining a definitive predictive skin permeability model. This review wants to show the main advances and the principal approaches in computational methods used to predict this property, to enlighten the main issues that have arisen, and to address the challenges to develop in future research.

Ataluren was reported to suppress nonsense mutations by promoting the readthrough of premature stop codons, although its mechanism of action (MOA) is still debated. The likely interaction of Ataluren with CFTR-mRNA has been previously studied by molecular dynamics. In this work we extended the modeling of Ataluren's MOA by complementary computational approaches such as induced fit docking (IFD), quantum polarized ligand docking (QPLD), MM-GBSA free-energy calculations, and computational mutagenesis. In addition to CFTR-mRNA, this study considered other model targets implicated in the translation process, such as eukaryotic rRNA 18S, prokaryotic rRNA 16S, and eukaryotic Release Factor 1 (eRF1), and we performed a comparison with a new promising Ataluren analogue (NV2445) and with a series of aminoglycosides, known to suppress the normal proofreading function of the ribosome. Results confirmed mRNA as the most likely candidate target for Ataluren and its analogue, and binding energies calculated after computational mutagenesis highlighted how Ataluren's interaction with the premature stop codon could be affected by ancillary nucleotides in the genetic context.

[Image: see text] Ataluren was reported to suppress nonsense mutations by promoting the readthrough of premature stop codons, although its mechanism of action (MOA) is still debated. The likely interaction of Ataluren with CFTR-mRNA has been previously studied by molecular dynamics. In this work we extended the modeling of Ataluren’s MOA by complementary computational approaches such as induced fit docking (IFD), quantum polarized ligand docking (QPLD), MM-GBSA free-energy calculations, and computational mutagenesis. In addition to CFTR-mRNA, this study considered other model targets implicated in the translation process, such as eukaryotic rRNA 18S, prokaryotic rRNA 16S, and eukaryotic Release Factor 1 (eRF1), and we performed a comparison with a new promising Ataluren analogue (NV2445) and with a series of aminoglycosides, known to suppress the normal proofreading function of the ribosome. Results confirmed mRNA as the most likely candidate target for Ataluren and its analogue, and binding energies calculated after computational mutagenesis highlighted how Ataluren’s interaction with the premature stop codon could be affected by ancillary nucleotides in the genetic context.

Background:Telomerase, a reverse transcriptase, maintains telomere and chromosomes integrity of dividing cells, while it is inactivated in most somatic cells. In tumor cells, telomerase is highly activated, and works in order to maintain the length of telomeres causing immortality, hence it could be considered as a potential marker to tumorigenesis.A series of 1,3,4-oxadiazole derivatives showed significant broad-spectrum anticancer activity against different cell lines, and demonstrated telomerase inhibition.Methods:This series of 24 N-benzylidene-2-((5-(pyridine-4-yl)-1,3,4-oxadiazol-2yl)thio)acetohydrazide derivatives as telomerase inhibitors has been considered to carry out QSAR studies. The endpoint to build QSAR models is determined by the IC50 values for telomerase inhibition, i.e., the concentration (μM) of inhibitor that produces 50% inhibition. These values were converted to pIC50 (- log IC50) values. We used the most common and transparent method, where models are described by clearly expressed mathematical equations: Multiple Linear Regression (MLR) by Ordinary Least Squares (OLS).Results:Validated models with high correlation coefficients were developed. The Multiple Linear Regression (MLR) models, by Ordinary Least Squares (OLS), showed good robustness and predictive capability, according to the Multi-Criteria Decision Making (MCDM = 0.8352), a technique that simultaneously enhances the performances of a certain number of criteria. The descriptors selected for the models, such as electrotopological state (E-state) descriptors, and extended topochemical atom (ETA) descriptors, showed the relevant chemical information contributing to the activity of these compounds.Conclusion:The results obtained in this study make sure about the identification of potential hits as prospective telomerase inhibitors.

The duplex and G-quadruplex DNA-binding of six nickel(II) and zinc(II) complexes of three salphen-like ligands (salphen = N,N?-bis-salicylidene-1,2-phenylenediaminato) was investigated by UV-visible absorption and circular dichroism spectroscopy. The results obtained, in particular the values of the DNA-binding constants, Kb, point out that the nickel(II) complexes show a higher affinity toward both duplex and G-quadruplex DNA, compared to the analogous zinc(II) complexes. Interestingly, the zinc(II) complexes possess high selectivity toward G-quadruplex DNA, being negligible their binding with duplex DNA. Molecular dynamics (MD) simulations provided atomistic models for the interpretation of the binding of the zinc(II) complexes with G-quadruplex DNA, allowing a structural comparison of the three salphen-like ligands, due to the presence of different substituents (H, F, CF3) on the position 4 of the phenyl ring on the N,N? bridge. © 2017 Elsevier Inc.

Indicaxanthin is a bioactive and bioavailable betalain pigment from the Opuntia ficus-indica fruits. In this in vivo study, kinetic measurements showed that indicaxanthin is revealed in the rat brain within 1 h from oral administration of 2 μmol/ kg, an amount compatible with a dietary consumption of cactus pear fruits in humans. A peak (20 ± 2.4 ng of indicaxanthin per whole brain) was measured after 2.5 h; thereafter the molecule disappeared with first order kinetics within 4 h. The potential of indicaxanthin to affect neural activities was in vivo investigated by a microiontophoretic approach. Indicaxanthin, administered in a range between 0.085 ng and 0.34 ng per neuron, dose-dependently modulated the rate of discharge of spontaneously active neurons of the hippocampus, with reduction of the discharge and related changes of latency and duration of the effect. Indicaxanthin (0.34 ng/neuron) showed inhibitory effects on glutamate-induced excitation, indicating activity at the level of glutamatergic synapses. A molecular target of indicaxanthin is suggested by in silico molecular modeling of indicaxanthin with N- methyl-D-aspartate receptor (NMDAR), the most represented of the glutamate receptor family in hippocampus. Therefore, at nutritionally compatible amounts indicaxanthin (i) crosses the rat BBB and accumulates in brain; (ii) can affect the bioelectric activity of hippocampal neurons locally treated with amounts comparable with those measured in the brain; and (iii) modulates glutamate-induced neuronal excitation. The potential of dietary indicaxanthin as a natural neuromodulatory agent deserves further mechanistic and neurophysiologic investigation.

Zinc(ii) complexes are effective and selective nucleic acid-binders and strongly fluorescent molecules in the low energy range, from the visible to the near infrared. These two properties have often been exploited to quantitatively detect nucleic acids in biological samples, in both in vitro and in vivo models. In particular, the fluorescent emission of several zinc(ii) complexes is drastically enhanced or quenched by the binding to nucleic acids and/or upon visible light exposure, in a different fashion in bulk solution and when bound to DNA. The twofold objective of this perspective is (1) to review recent utilisations of zinc(ii) complexes as selective fluorescent probes for nucleic acids and (2) to highlight their novel potential applications as diagnostic tools based on their photophysical properties. This journal is

We present a new approach that incorporates flexibility based on extensive MD simulations of protein-ligand complexes into structure-based pharmacophore modeling and virtual screening. The approach uses the multiple coordinate sets saved during the MD simulations and generates for each frame a pharmacophore model. Pharmacophore models with the same pharmacophore features are pooled. In this way the high number of pharmacophore models that results from the MD simulation is reduced to only a few hundred representative pharmacophore models. Virtual screening runs are performed with every representative pharmacophore model; the screening results are combined and rescored to generate a single hit-list. The score for a particular molecule is calculated based on the number of representative pharmacophore models which classified it as active. Hence, the method is called common hits approach (CHA). The steps between the MD simulation and the final hit-list are performed automatically and without user interaction. We test the performance of CHA for virtual screening using screening databases with active and inactive compounds for 40 protein-ligand systems. The results of the CHA are compared to the (i) median screening performance of all representative pharmacophore models of protein-ligand systems, as well as to the virtual screening performance of (ii) a random classifier, (iii) the pharmacophore model derived from the experimental structure in the PDB, and (iv) the representative pharmacophore model appearing most frequently during the MD simulation. For the 34 (out of 40) protein-ligand complexes, for which at least one of the approaches was able to perform better than a random classifier, the highest enrichment was achieved using CHA in 68% of the cases, compared to 12% for the PDB pharmacophore model and 20% for the representative pharmacophore model appearing most frequently. The availabilithy of diverse sets of different pharmacophore models is utilized to analyze some additional questions of interest in 3D pharmacophore-based virtual screening.

Surfactants are an interesting class of compounds characterized by the segregation of polar and apolar domains in the same molecule. This peculiarity makes possible a whole series of microscopic and macroscopic effects. Among their features, their ability to segregate particles (fluids or entire domains) and to reduce the surface/interfacial tension is the utmost important. The interest in the chemistry of surfactants never weakened; instead, waves of increasing interest have occurred every time a new field of application of these molecules has been discovered. All these special characteristics depend largely on the ability of surfactants to self-assemble and constitute supramolecular structures where their chemical properties are amplified. The possibility to obtain structural and energy information and, above all, the possibility of forecast the self-organizing mechanisms of surfactants have had a significant boost via computational chemistry. The molecular dynamics models, initially coarse-grained and subsequently (with the increasing computer power) using more accurate models, allowed, over the years, to better understand different aspects of the processes of dispersion, self-assembly, segregation of surfactant. Moreover, several other aspects have been investigated as the effect of the counterions of many ionic surfactants in defining the final supramolecular structures, the mobility of side chains, and the capacity of some surfactant to envelope entire proteins. This review constitutes a perspective/prospective view of these results. On the other hand, some comparison of in silico results with experimental information recently acquired through innovative analytical techniques such as ion mobility mass spectrometry which have been introduced.

In a previous work, we developed the in house Virtual Lock-and-Key Approach (VLKA) in order to evaluate target assignment starting from molecular descriptors calculated on known inhibitors used as an information source. This protocol was able to predict the correct biological target for the whole dataset with a good degree of reliability (80%), and proved experimentally, which was useful for the target fishing of unknown compounds. In this paper, we tried to remodel the previous in house developed VLKA in a more sophisticated one in order to evaluate the influence of 3D conformation of ligands on the accuracy of the prediction. We applied the same previous algorithm of scoring and ranking but, this time, combining it with a structure-based approach as docking. For this reason, we retrieved from the RCSB Protein Data Bank (PDB), the available 3D structures of the biological targets included into the previous work, and we used them to calculate poses of the 7352 dataset compounds in the VLKA biological targets. First, docking protocol has been used to retrieve docking scores, then, from the docked poses of each molecule, 3D-descriptors were calculated (Conf-VLKA), While the use of the simple docking scores proved to be inadequate to improve compounds classification, the Conf-VLKA showed some interesting variations compared to the original VLKA, especially for targets whose ligands present a high number of rotamers. This work represent a first preliminary study to be completed using other techniques such as induced fit docking or molecular dynamics structure clustering to take into account the protein side chains adaptation to ligands structures.

The cyclin dependent kinases (CDKs) are a small family of serine/threonine protein kinases that can act as a potential therapeutic target in several proliferative diseases, including cancer. This short review is a survey on the more recent research progresses in the field achieved by using in silico methods. All the "armamentarium" available to the medicinal chemists (docking protocols and molecular dynamics, fragment-based, de novo design, virtual screening, and QSAR) has been employed to the discovery of new, potent, and selective inhibitors of cyclin dependent kinases. The results cited herein can be useful to understand the nature of the inhibitor-target interactions, and furnish an insight on the structural/molecular requirements necessary to achieve the required selectivity against cyclin dependent kinases over other types of kinases.

1,3-Dipolar cycloaddition reactions can be considered a powerful synthetic tool in the building of heterocyclic rings, with applications in different fields. In this review we focus on the synthesis of biologically active compounds possessing the 1,2,3-triazole core through 1,3-dipolar cycloaddition reactions. The 1,2,3-triazole skeleton can be present as a single disubstituted ring, as a linker between two molecules, or embedded in a polyheterocycle. The cycloaddition reactions are usually catalysed by copper or ruthenium. Domino reactions can be achieved through dipolarophile anion formation, generally followed by cyclisation. The variety of attainable heterocyclic structures gives an illustration of the importance of the 1,2,3-triazole core in medicinal chemistry.

In efforts to find agents with improved biological activity against cancer cells, recent years have seen an increased interest in the study of small molecules able to bind the deoxyribonucleic acid (DNA) when it assumes secondary structures known as G-quadruplexes (G4s) preferring them over the B form. Currently, several compounds reported in literature have already shown to be good candidates as G4s DNA stabilizers. Even though some specific features for the G4s affinity are known, such as a π-delocalized system able to stack at the top/end of a G-tetrad and positively charged substituents able to interact with the grooves, it is not clear yet what kind of structural features affect more the G4 arrangement. This is mainly due to the structure heterogeneity of both the G4 stabilizer compounds and the DNA G4s isoforms. In this review, we aim to classify some known G4 binders by analyzing them from a new perspective surprisingly never approached up to date: the symmetry features. Molecular symmetry could be responsible for the specific binding mode to the G4-DNA but could also be crucial in determining different isoform affinity. We propose to classify the G4s stabilizers in five main point group symmetry classes. This classification could be useful to design new ligands able to stabilize a specific G-quadruplex isoform, in order to increase the selectivity of new potential anticancer G-quadruplex targeting drugs, a goal yet highly sought by researchers.

The affinity of three square-planar nickel(II) (1), copper(II) (2) and zinc(II) (3) Schiff-base complexes for wild-type human telomeric (h-Telo) and protooncogene c-myc G-quadruplex (G4) DNA was investigated by UV-visible absorption spectroscopy and circular dichroism. DNA-binding constants (Kb) were determined by spectrophotometric titrations for both G4-DNA and B-DNA. The results obtained point out that the three metal complexes selectively bind G4-DNA with higher affinity, up to two orders of magnitude, with respect to B-DNA. The nickel(II) complex 1 was found to be the most effective G4-DNA stabilizer and the Kb values decrease in the order 1 > 2 ≈ 3. Innovative computational investigations, consisting of molecular dynamics (MD) simulations followed by density functional theory/molecular mechanics (DFT/MM) calculations, provide atomistic support for the interpretation of the binding mechanism to G4-DNA by end stacking and also of the experimental affinity order. Interestingly, 1 is able to induce G4-DNA formation of h-Telo sequences, also in the absence of K+ cations. This last result is nicely confirmed and highlighted by polymerase chain reaction (PCR) stop assays, which show the ability of the title compounds to induce and stabilize G4 structures inhibiting the amplification of PCR products. Finally, compounds 1–3 showed concentration and time-dependent cytotoxicity towards HeLa and MCF-7 human cancer cell lines, inducing significant effects on cell cycle distribution with G2/M arrest in HeLa cells and G0/G1 arrest in MCF-7 cells. Overall, the PCR inhibition and anticancer activity of the three compounds decreases in the same order 1 > 2 ≈ 3, in excellent correlation with the G4-DNA-binding affinity, implying that G4-DNA is the biotarget for their biological activity.

The reaction mechanism of 1,3-dipolar cycloadditions of both symmetric and unsymmetric benzo-condensed diazines with a nitrilimine dipole, to give two different mono- and bis-cycloadducts, in tetrahydrofuran (THF) solution, was studied by DFT calculations. The results obtained show that each 1,3-dipolar cycloaddition reaction always proceeds by a two steps mechanism, in which the first intermediate shows only one covalent bond between the beta carbon of the nitrilimine and the aromatic nitrogen of the diazine molecule. The structure and energy content of the two transition states of the two cycloaddition steps, in the case of the unsymmetric benzo-condensed diazine, nicely explains why the product of the bis-cycloadditions is exclusively observed and why the product of a mono-cycloaddition is not isolated for the symmetric reaction pathway.

Heat shock protein 60 kDa (Hsp60) is a chaperone classically believed to be involved in assisting the correct folding of other mitochondrial proteins. Hsp60 also plays a role in cytoprotection against cell stressors, displaying for example, antiapoptotic potential. Despite the plethora of studies devoted to the mechanism of Hsp60's function, especially in prokaryotes, fundamental issues still remain unexplored, including the definition of its role in cancer. Key questions still unanswered pertain to the differences in structure-function features that might exist between the well-studied prokaryotic GroEL and the largely unexplored eukaryotic Hsp60 proteins. In this article we discuss these differences in sequence, structure, and roles of Hsp60, focusing on the human ortholog with the view of devising compounds to block its ability to favour tumor-cell growth and survival. Compounds currently known to directly or indirectly affect Hsp60 functions, such as protein folding, HIF-1α accumulation, or Hsp60-induced cell proliferation, are discussed along with strategies that might prove effective for developing Hsp60-targeting drugs for anticancer therapy.