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2-Amino-N-[2-(3,4-dihydroxy-phenyl)-ethyl]-3-phenyl-propionamide (DA-PHEN) has been previously synthesized to obtain a potential prodrug capable of release dopamine (DA) into CNS. However, DA-PHEN could act per se as a dopaminergic drug. In this study, the permeability transport (Pe), obtained by parallel artificial permeability assay (PAMPA), indicated a low passive transcellular transport (Pe = 0.32 ± 0.01 × 10(-6 )cm/s). Using the Caco-2 cell system, the Papp AP-BL in absorptive direction (3.36 ± 0.02 × 10(-5 )cm/s) was significantly higher than the Papp BL-AP in secretive direction (1.75 ± 0.07 × 10(-5 )cm/s), suggesting a polarized transport. The efflux ratio (Papp AP-BL/Papp BL-AP = 0.52 ± 0.02) indicated a low affinity of DA-PHEN to efflux carriers. The forced swim test highlighted a reduction of immobility time in both pre-test and test sessions (p 0.0001), with an exacerbation in the number of headshakes and divings in the pretest (p 0.0001). Morris water maze strengthened the hypothesis that DA-PHEN induces adaptive responses to environmental challenges which are involved on cognitive functions (DA-PHEN versus CTR: escape latency; p 0.001; distance swum p 0.001, time spent on target quadrant p 0.001), without any change in locomotor activity for the administered dose. The molecular docking revealed the interaction of DA-PHEN with the identified D1 site mapping human brain receptor.

Body weight control is a mechanism finely regulated by several hormonal, metabolic, and nervous pathways. The leptin receptor (Ob-R) is crucial for energy homeostasis and regulation of food uptake. Leptin is a 16 kDa hormone that is mainly secreted by fat cells into the bloodstream, and under normal circumstances, circulating levels are proportionate to the fat body mass. Sensing of elevated leptin levels by the hypothalamic neurocircutry activates a negative feedback loop resulting in reduced food intake and increased energy expenditure. Decreased concentrations lead to opposite effects. Therefore rational design of leptin agonists constitute an appealing challenge in the battle against obesity. In this study, we performed protein-protein docking among the re-built crystal structure of leptin and leptin binding domain (LBD). The obtained complex was used as a starting point to carry out nanosecond-scale molecular dynamics simulations to characterize the key regions in terms of physical-chemical features involved in the protein-protein interaction (dynamic site mapping filtered by means multivariate analysis) and used to carry out a HTVS. The main goal of this study was to suggest guidelines for the rational drug design of new agonists of leptin. Identified hits could be a consistent starting point to carry out in vitro testing.

Cystic Fibrosis patients with nonsense-mutation in h-CFTR gene generally make virtually no CFTR protein and thus often have a more severe form of CF. Ataluren (PTC124) was suggested to induce read-through of premature but not normal termination codons. Despite the promising results there is not a general consensus on the mechanism of its action (protein stabilization or codon read-through) and its efficacy, the identification of new PTC124 analogues and the study of the mechanism of action may led to a new strategy for the development of a pharmacologic approach to the cure of CF.

In this work the new protocol BIOlogical Target Assignation (BIOTA) for the prediction of the biological target from molecular structures is proposed. BIOTA is based on the Principal Components Analysis (PCA) application on a matrix of ligands versus molecular descriptors. The application of BIOTA could allow to hypothesize the mechanism of action of a candidate drug prior to its biological evaluation or to repurpose old drugs. The protocol can be fine-tuned by choosing opportune targets (biological or not) and molecular descriptors, and it can be useful in every fields in with it is possible to collect set of compounds with known properties. The robustness of the protocol depends from different factors: the correctness of biological data, the optimization of the molecular structures and their molecular descriptors calculation, the selection of the biological targets. The application of BIOTA to a new class of Hsp90 inhibitors was able to predict quite correctly their affinity for Hsp90.

The OB-receptor or leptin receptor (LR) is crucial for energy homeostasis and regulation of food uptake. Leptin is a 16 kDa hormone that is mainly secreted by fat cells into the bloodstream. Under normal circumstances, circulating leptin levels are proportionate to the fat body mass. Sensing of elevated leptin levels by the hypothalamic neuro-circuitry activates a negative feedback loop resulting in reduced food intake and increased energy expenditure. Decreased leptin concentrations lead to opposite effects. Therefore, rational design of leptin agonists/antagonists could be an appealing challenge in the battle against obesity. The Leptin/LR interactions have been studied in several works by means of different molecular modelling approaches, spreading from homology modelling to manual docking. No small molecules have ever been proposed as agonists of the Ob receptor but researchers’ efforts focused only on leptin-related synthetic peptides as receptor antagonists and on peptidomimetics. In this review we try to track a timeline of obtained in silico information to clarify the mechanism of interaction between leptin and its receptor, together to summarize the more recent efforts to propose new drugs usable in anti-obesity therapy. Final considerations could be useful starting points for the rational drug design of new lead compounds.

Purpose: This study investigated the absorption mechanism of the phytochemicals indicaxanthin and betanin and the influence of their food matrix (cactus pear and red beet) on the intestinal transport. Methods: Trans-epithelial transport of dietary-consistent amounts of indicaxanthin and betanin in Caco-2 cell monolayers seeded on TranswellR inserts was measured in apical to basolateral (AP-BL) and basolateral to apical (BL-AP) direction, under an inwardly directed pH gradient (pH 6.0/7.4, AP/BL) mimicking luminal and serosal sides of human intestinal epithelium. The effect of inhibitors of membrane transporters on the absorption was also evaluated. Contribution of the paracellular route was investigated after EDTA treatment of the cell monolayer. In vitro digestion of betalainic food was performed to provide a post-intestinal fraction containing bioaccessible pigments. Results: Apparent permeability coefficients (P app) in the absorptive direction were (4.4 ± 0.4) × 10-6 and (3.2 ± 0.3) × 10-6 cm s-1 for indicaxanthin and betanin, respectively. Transport of indicaxanthin was non-polarized, linear as a function of time and concentration, and unaffected by inhibitors of membrane transporters. Betanin exhibited significantly different bidirectional P app values and non-linear efflux kinetics. The concentration- dependent betanin efflux was described by a kinetic model including one non-saturable (K d = 0.042 μL cm-2 min-1) and one saturable component identified as the apical multidrug resistance-associated protein 2 (MRP2; K m = 275 μM; J max = 42 pmol min-1 cm-2). Permeation of both betalains increased remarkably after EDTA treatment of the cell monolayer. Neither indicaxanthin nor betanin underwent metabolic transformation. Food matrix did not affect trans-epithelial transfer of indicaxanthin, but reduced the absorption rate of betanin, red beet more than cactus pear. Conclusions: Dietary indicaxanthin and betanin can substantially be absorbed through paracellular junctions of intestinal epithelial cells. Additional trans-membrane permeation can be considered for betanin, whose absorption is limited by a MRP2-mediated efflux and negatively affected by its food matrix. Present findings are consistent with the quite higher bioavailability of indicaxanthin over betanin established in humans. © 2012 Springer-Verlag.

The goal of computer-aided molecular design methods in modern medicinal chemistry is to reduce the overall cost and time associated to the discovery and development of a new drug by identifying the most promising candidates to focus the experimental efforts on. Very often, many drug discovery projects have reached already a well-advanced stage before detailed structural data on the protein target have become available. A possible consequence is that often, medicinal chemists develop novel compounds for a target using preliminary structure–activity information, together with the theoretical models of interactions. Only responses that are consistent with the working hypothesis contribute to an evolution of the used models. Within this framework, the pharmacophore approach has proven to be successful, allowing the perception and understanding of key interactions between a receptor and a ligand[1]. In recent years, our research group exploited this useful modeling tool with the aim to identify new chemical entities and/or optimizing known lead compounds to obtain more active drugs in the field of antitumor, antiviral, and antibacterial drugs. In this communication, we present an overview of our recent works in which we used the pharmacophore modelling approach combined with induced fit docking, 3D-QSAR approach, and HTVS for the analysis of drug-receptor interactions and the discovery of new inhibitors of IKKβ, Bcl-xl, and c-kit tyrosine kinase, all targets involved into the initiation and the development of different types of cancer[2-5].

The body weight control is a mechanism thinly regulated by several hormonal, metabolic, and nervous pathways (1). Recessive homozygous mutations in the ob/ob and db/db mouse strain cause extreme obesity. The products of the ob and db genes are leptin and its receptor, respectively. The leptin receptor is crucial for energy homeostasis and regulation of food uptake. Leptin is a 16 kDa hormone that is mainly secreted by fat cells into the bloodstream. Under normal circumstances, circulating leptin levels are proportionate to the fat body mass. Sensing of elevated leptin levels by the hypothalamic neurocircutry activates a negative feedback loop resulting in reduced food intake and increased energy expenditure. Decreased leptin concentrations lead to opposite effectsTherefore rational design of leptin agonists could be an appealing challenge in the battle against obesity. Unfortunately only the crystal structure of leptin is available, but not that of the leptin receptor. In this work, first, we built, by homology modelling, the leptin receptor starting from FASTA sequence and the similarity search of templates. The obtained model was used to perform a protein-protein docking with the crystal structure of leptine by means Gramm-X server, with the aim to define the complementary surfaces of the two proteins. The complex of leptin/leptin receptor was then used as starting point to carry out molecular dynamics simulations in water solvent to characterize the key residues involved into the protein-protein interaction. Snapshots of leptin were used as template to build a pharmacophore hypothesis to carry out virtual screening on a large database of compounds. (1) Friedman, J. M., Halaas, J. L. Nature 1998, 395, 763-770 IN THE SEARCH OF LEPTIN AGONISTS AS ANTI-OBESITY DRUGS: PROTEIN/PROTEIN DOCKING, MOLECULAR DYNAMICS, AND VIRTUAL SCREENING

Studies of the the three-dimensional quantitative structure–activity relationships for ninety-five c-kit tyrosine kinase inhibitors were performed. Based on a co-crystallized compound (1 T46), known inhibitors were aligned with c-kit by induced-fit docking, and multiple training/test set splitting was performed to validate the selected pharmacophore model. The best pharmacophore model consisted of five features: one hydrogen-bond donor and four aromatic rings. Reliable statistics were obtained (R 2 = 0.95, R pred 2 = 0.75), and the model was validated by using it to select c-kit inhibitors from a database; 82.1% of the hits it retrieved were active. Accordingly, our model can be reliably used to identify new c-kit inhibitors, and can provide useful information when designing new inhibitors.

La sovraespressione del proto-oncogene c-kit è stata riscontrata nelle cellule ematopoietiche, nel cancro a piccole cellule del polmone e nei tumori stromali gastrointestinali1-3. L’importanza clinica dell’espressione di c-kit nei tumori ha indirizzato la ricerca verso inibitori di questa tirosina chinasi. Imatinib (Gleevec®) (in figura) è stato il primo farmaco utilizzato in terapia, ma la comparsa di mutazioni su c-kit ha portato ad una riduzione dell’efficacia o a completa resistenza a questo trattamento. In alternativa, altri composti si sono mostrati attivi anche nei confronti dei mutanti come ad esempio Sunitinib (Sutent®)4, ma la necessità di nuovi e più efficaci inibitori contro i mutanti rimane ancora un punto critico della ricerca. Si riporta uno studio misto Dinamica Molecolare/Docking (IFD) con lo scopo di svelare i meccanismi molecolari coinvolti nella resistenza a Imatinib, Sunitinib e altri inibitori contro le mutazioni “gatekeeper” V654A e T670I, provando ad evidenziare i punti forti e deboli degli attuali inibitori (Nilotinib, Sorafenib, Motesanib, PKC412, una tienopirimidina TPD, un aminobenzoisossazolo ABIOZ). Questo approccio in silico può consentire di identificare le linee guida per la progettazione di nuovi farmaci attivi contro i mutanti.

Obesity is a chronic pathology with multi-factorial aetiology, characterized by extreme body weight due to storing of fat in the adipose tissue, caused by an increase of caloric income, decrease of energetic intake, or both. The body weight control is a mechanism finely regulated by several hormonal, metabolic, and nervous pathways. Recessive homozygous mutations in the ob/ob and db/db mouse strain cause extreme obesity. The products of the ob and db genes are leptin and its receptor, respectively (1,2). The leptin receptor is critical for energy homeostasis and regulation of food uptake. Leptin is a 16 kDa hormone that is mainly secreted by fat cells into the bloodstream. Under normal circumstances, circulating leptin levels are proportionate to the fat body mass. Sensing of elevated leptin levels by the hypothalamic neurocircutry activates a negative feedback loop resulting in reduced food intake and increased energy expenditure. Decreased leptin concentrations lead to opposite effects. Therefore rational design of leptin agonists could be an interesting challenge in the fight against obesity. Unfortunately only the crystal structure of leptin is available, but not that of the leptin receptor. In this work, first, we build by homology modelling the leptin receptor starting from FASTA sequence and the similarity search of templates. The obtained model was used to perform a protein-protein docking with the crystal structure of leptine by means Gramm-X server, with the aim to define the complementary surfaces of the two proteins. The complex of leptin/leptin receptor was then used as starting point to carry out molecular dynamics simulations in water solvent to characterize the key residues involved into the protein-protein interaction and to identify the guidelines for rational drug design of new agonists of leptin, which could be used in the therapy of obesity.

In the last years the application of computational methodologies in the medicinal chemistry fields has found an amazing development. All the efforts were focused on the searching of new leads featuring a close affinity on a specific biological target. Thus, different molecular modeling approaches in simulation of molecular behavior for a specific biological target were employed. In spite of the increasing reliability of computational methodologies, not always the designed lead, once synthesized and screened, are suitable for the chosen biological target. To give another chance to these compounds, this work tries to resume the old concept of Fischer lock-and-key model. The same can be done for the “re-purposing” of old drugs. In fact, it is known that drugs may have many physiological targets, therefore it may be useful to identify them. This aspect, called “polypharmacology”, is known to be therapeutically essential in the different treatments. The proposed protocol, the virtual lock-and-key approach (VLKA), consists in the “virtualization” of biological targets through the respectively known inhibitors. In order to release a real lock it is necessary the key fits the pins of the lock. The molecular descriptors could be considered as pins. A tested compound can be considered a potential inhibitor of a biological target if the values of its molecular descriptors fall in the calculated range values for the set of known inhibitors. The proposed protocol permits to transform a biological target in a “lock model” starting from its known inhibitors. To release a real lock all pins must fit. In the proposed protocol, it was supposed that the higher is the number of fit pins, the higher will be the affinity to the considered biological target. Therefore, each biological target was converted in a sequence of “weighted” molecular descriptor range values (locks) by using the structural features of the known inhibitors. Each biological target lock was tested by performing a molecular descriptors “fitting” on known inhibitors not used in the model construction (keys or test set). The results showed a good predictive capability of the protocol (confidence level 80%). This method gives interesting and convenient results because of the user-defined descriptors and biological targets choice in the process of new inhibitors discovery.

The over-expression of c-kit proto-oncogene has been reported in hematopoietic cells, small cell lung cancer, and gastrointestinal stromal tumors. The clinical importance of c-kit expression in tumors focused the research towards inhibitors of this tyrosine kinase. Imatinib (Gleevec®) was the first compound used in therapy, but mutations on c-kit led to reduced effectiveness or ineffectiveness of this treatment. Other compounds are likely to be effective against mutants, such as Sunitinib (Sutent®), but the need for new and most effective inhibitors against mutants is still critical. We report mixed Molecular Dynamics/Docking study with the aim to unveil the molecular mechanism involved in the resistance of Imatinib, Sunitinib, and other known compounds against the “gatekeeper” mutants V654A and T670I. We tried to evidence strong and weak features of actual inhibitors in order to identify the guidelines to design new and most potent inhibitors against c-kit mutants.

Infective diseases caused by protozoarian agents are still relevant today more than ever. In fact, they represent the first cause of death all over the world with seventeen millions victims every year. The development of drug resistance and the broad diffusion of these pathologies make actual the research of new molecules able to act as selective and effective anti-infective chemotherapics.[1] Recently several polycondensed diazine derivatives, by means 1,3-dipolar cycloaddition, reactions [2, 3] were synthesized. A broad selection of these compounds chosen with a wide pattern of substitutions were submitted to biological in vitro screening against Plasmodium falciparum, Leishmania Infantum, Trypanosoma brucei e Trypanosoma cruzi, and they resulted active at micromolar level. In order to identify molecular targets able to explain the mechanism of action of these compounds, we performed Induced Fit Docking/MM-GBSA modeling studies. The obtained results give interesting indications about the probable mechanism of action of the most active compounds. [1] M. Gonzaalez, H. Cerecetto, Expert Opinion on Therapeutic Patents, 21, 2011, 699-715. [2] A. Lauria, A. Guarcello, G. Dattolo, A.M. Almerico, Tetrahedron Lett., 49, 2008, 1847-1850. [3] A. Lauria, A. Guarcello, G. Macaluso, G. Dattolo, A.M. Almerico, Tetrahedron Lett., 50, 2009, 7333-7336.

The mdm2 oncogene product, MDM2, is an ubiquitin protein ligase that inhibits the transcriptional activity of the tumor suppressor p53 and promotes its degradation. About 50% of all human cancers present mutations or deletions in the TP53 gene. In the remaining half of all human neoplasias that express the wild-type protein, aberrations of p53 regula- tors, such as MDM2, account for p53 inhibition. For this reason, designing small-molecule inhibitors of the p53-MDM2 protein-protein interaction is a promising strategy for the treatment of cancers retaining wild-type p53. The development of inhibitors has been challenging. Although many small-molecule MDM2 inhibitors have shown potent in vitro activity, only a limited number of compounds have demonstrated to possess acceptable pharmacokinetic properties for in vivo evaluation. To date, the most studied chemotypes have been cis-imidazolines (such as nutlins), benzodiazepines, and spiro-oxindoles. The cis-imidazolines were the first discovered potent and selective small-molecule inhibitors of the p53- MDM2 interaction, and they continue to show therapeutic potential. This review will focus on recent molecular modeling approaches (molecular dynamics, pharmacophore-based, molecular docking, structure-based design) used with the aim to better understand the behavior of these proteins and to discover new small-molecule inhibitors of the p53-MDM2 protein-protein interaction for the treatment of cancer.

Bcl-2 proteins family members play several roles in tumoral proliferation: they inhibit proapoptotic activity during oncogenesis, support tumor cells survival, induce chemoresistance. The discovery of new small inhibitors of Bcl-xl represents a new frontier for cancer treatment. In this study, a 3D-QSAR pharmacophore model was developed, based on 42 biarylacylsulfonamides, and used to understand the structural factors affecting the inhibitory potency of these derivatives. Aromatic, negative charge, and hydrogen bond acceptor effects contribute to the inhibitory activity. The model was then employed as 3D search query to screen ZINC drug-like database in order to select new scaffolds. Finally six hits were identified. Docking study evidenced the capability of these compounds to interact with Bcl-xl receptor, and they were selected for further in vitro and in vivo assay studies.

This paper describes the use of the multivariate statistical procedure principal component analysis as a tool to explore the inhibitory activity of classes of protease inhibitors (PIs) against HIV-1 viruses (wild type and more-frequent single mutants, V82A, V82F, and I84V) and against protease enzymes. The analysis of correlations between biological activity and molecular descriptors or similarity indexes allowed a reliable classification of the 51 derivatives considered in this study. The best results were obtained in the case of the I84V mutant for which a high number of predictions was achieved. On this basis, this statistical approach is proposed as a reliable method for the prediction of the activity of PIs, for which the data against mutant strains have not been reported.

A QSAR study, involving the use of calculated physical-chemical properties (TSAR TM ), and the use of a neural network approach (TSAR TM ), has been performed on the potential anti-HIV-1 activity of a series of Acyclovir and Ganciclovir analogs. Model obtained allows reliable predictions for the anti-HIV-1 activity of these derivatives, and showed that the presence of the Ganciclovir chain in triazolopyrrolopyrimidine and pyrimidopyrrolopyrimidine series seems to increase the antiviral effect.

This paper describes the use of multivariate statistical procedure PCA as a tool to explore the inhibitory activity of classes of NNRTIs against HIV-1 viruses (wild type and more frequent mutants, Y181C, V106A, K103N, L100I) and against RT enzyme. The analysis of correlations between biological activity and molecular descriptors or similarity indexes allowed a reliable classification of the fifty five derivatives considered in this study. The best results were obtained in the case of L100I and K103N mutants for which the higher number of assignments was found when the principal components derived from the descriptors were used. On this basis this statistical approach is proposed as a reliable method for the prediction of the activity of NNRTIs, for which the data against mutant strains have not been reported.

The design of new series of pyrrolo-pyrimidine derivatives, further annelated with a third heterocycle of different size, which also present several chain shape moieties of variable length and with different physico-chemical character, is reported. In this contribution we showed that the combination of docking-based and QSPR-based methods could lead to good models for ligand-DNA interaction prediction. By means of these computational approaches on 360 proposed inhibitors, we were able to select the most promising candidates as DNA-interactive drugs potentially endowed with antitumor activity.