Giulio Rastelli

Università degli Studi di Modena e Reggio Emilia, Modène, Emilia-Romagna, Italy

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Publications (82)210.48 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: This study aimed to explore the capability of potentially probiotic bifidobacteria to hydrolyze chlorogenic acid into caffeic acid (CA), and to recognize the enzymes involved in this reaction. Bifidobacterium strains belonging to eight species occurring in the human gut were screened. The hydrolysis seemed peculiar of Bifidobacterium animalis, whereas the other species failed to release CA. Intracellular feruloyl esterase activity capable of hydrolyzing chlorogenic acid was detected only in B. animalis. In silico research among bifidobacteria esterases identified Balat_0669 as the cytosolic enzyme likely responsible of CA release in B. animalis. Comparative modeling of Balat_0669 and molecular docking studies support its role in chlorogenic acid hydrolysis. Expression, purification, and functional characterization of Balat_0669 in Escherichia coli were obtained as further validation. A possible role of B. animalis in the activation of hydroxycinnamic acids was demonstrated and new perspectives were opened in the development of new probiotics, specifically selected for the enhanced bioconversion of phytochemicals into bioactive compounds.
    MicrobiologyOpen. 10/2014;
  • Andrew Anighoro, Jürgen Bajorath, Giulio Rastelli
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    ABSTRACT: At present, the legendary magic bullet, i.e. a drug with high potency and selectivity towards a specific biological target, shares the spotlight with an emerging and alternative polypharmacology approach. Polypharmacology suggests that more effective drugs can be developed by specifically modulating multiple targets. It is generally thought that complex diseases such as cancer and central nervous system diseases may require complex therapeutic approaches. In this respect, a drug that "hits" multiple sensitive nodes belonging to a network of interacting targets offers the potential for higher efficacy, and may limit drawbacks generally arising from the use of a single-target drug or a combination of multiple drugs. In this article, we will compare advantages and disadvantages of multi-target versus combination therapies, discuss potential drug promiscuity arising from off-target effects, comment on drug repurposing, and introduce approaches to the computational design of multi-target drugs.
    Journal of medicinal chemistry. 06/2014;
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    ABSTRACT: Allosteric targeting of protein kinases via displacement of the structural αC helix with type III allosteric inhibitors is currently gaining a foothold in drug discovery. Recently, the first crystal structure of CDK2 with an open allosteric pocket adjacent to the αC helix has been described, prospecting new opportunities to design more selective inhibitors, but the structure has not yet been exploited for the structure-based design of type III allosteric inhibitors. In this work we report the results of a virtual screening campaign that resulted in the discovery of the first-in-class type III allosteric ligands of CDK2. Using a combination of docking and post-docking analyses made with our tool BEAR, 7 allosteric ligands (hit rate of 20%) with micromolar affinity for CDK2 were identified, some of them inhibiting the growth of breast cancer cell lines in the micromolar range. Competition experiments performed in the presence of the ATP-competitive inhibitor staurosporine confirmed that the 7 ligands are truly allosteric, in agreement with their design. Of these, compound 2 bound CDK2 with an EC 50 value of 3 μM and inhibited the proliferation of MDA-MB231 and ZR-75-1 breast cancer cells with IC 50 values of approximately 20 μM, while compound 4 had an EC 50 value of 71 μM and IC 50 values around 4 μM. Remarkably, the most potent compound 4 was able to selectively inhibit CDK2-mediated Retinoblastoma phosphorylation, confirming that its mechanism of action is fully compatible with a selective inhibition of CDK2 phosphorylation in cells. Finally, hit expansion through analog search of the most potent inhibitor 4 revealed an additional ligand 4g with similar in vitro potency on breast cancer cells.
    Cell cycle (Georgetown, Tex.) 06/2014; 13(14). · 5.24 Impact Factor
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    Giulio Rastelli, Maria Paola Costi
    Computational and Theoretical Chemistry 04/2014; · 1.14 Impact Factor
  • Andrew Anighoro, Giulio Rastelli
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    ABSTRACT: G-protein coupled receptors (GPCRs) are highly relevant drug targets. Four GPCRs with known crystal structure were analyzed with docking (AutoDock4) and post-docking (MM-PBSA) in order to evaluate the ability to recognize known antagonists from a larger database of molecular decoys and to predict correct binding modes. Moreover, implications on multitarget drug screening are put forward. The results suggest that these methods may be of interest to the growing field of GPCR structure based virtual screening.
    Journal of Chemical Information and Modeling 03/2013; · 4.30 Impact Factor
  • Giulio Rastelli
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    ABSTRACT: Molecular dynamics simulations and the generation of ad hoc chemical libraries are playing an increasingly important and recognized role in structure-based virtual screening. These approaches are important for treating target flexibility and improving the drug discovery pipeline. In this article I will comment on these two topics and put them into perspective.
    Pharmaceutical Research 03/2013; · 4.74 Impact Factor
  • Lorenzo Palmieri, Giulio Rastelli
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    ABSTRACT: Displacement of the αC helix in kinases by allosteric modulators is becoming a prominent approach in drug discovery, owing to its potential ability to provide inhibitor selectivity. According to recent evidence, this approach appears to be more generally applicable to a broader number of kinases of the human kinome than was previously expected. Owing to their crucial role in the modulation of cell pathways, protein kinases are important targets for a number of human diseases, including but not limited to cancer. The classic approach of targeting the ATP active site has recently come up against selectivity issues, which can be considerably reduced by following an allosteric modulation approach. Being closely related to protein kinase inactivation, allosteric targeting via displacement of the conserved structural αC helix enables a direct and specific modulation mechanism. A structure-based survey of the allosteric regulation of αC helix conformation in various kinase families is provided, highlighting key allosteric pockets and modulation mechanisms that appear to be more broadly conserved than was previously thought.
    Drug discovery today 11/2012; · 6.63 Impact Factor
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    ABSTRACT: In the last decades, molecular docking has emerged as an increasingly useful tool in the modern drug discovery process, but it still needs to overcome many hurdles and limitations such as how to account for protein flexibility and poor scoring function performance. For this reason, it has been recognized that in many cases docking results need to be post-processed to achieve a significant agreement with experimental activities. In this study, we have evaluated the performance of MM-PBSA and MM-GBSA scoring functions, implemented in our post-docking procedure BEAR, in rescoring docking solutions. For the first time, the performance of this post-docking procedure has been evaluated on six different biological targets (namely estrogen receptor, thymidine kinase, factor Xa, adenosine deaminase, aldose reductase, and enoyl ACP reductase) by using i) both a single and a multiple protein conformation approach, and ii) two different software, namely AutoDock and LibDock. The assessment has been based on two of the most important criteria for the evaluation of docking methods, i.e., the ability of known ligands to enrich the top positions of a ranked database with respect to molecular decoys, and the consistency of the docking poses with crystallographic binding modes. We found that, in many cases, MM-PBSA and MM-GBSA are able to yield higher enrichment factors compared to those obtained with the docking scoring functions alone. However, for only a minority of the cases, the enrichment factors obtained by using multiple protein conformations were higher than those obtained by using only one protein conformation.
    European Journal of Medicinal Chemistry 10/2012; 58C:431-440. · 3.43 Impact Factor
  • Marco Daniele Parenti, Giulio Rastelli
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    ABSTRACT: Nowadays, the improvement of R&D productivity is the primary commitment in pharmaceutical research, both in big pharma and smaller biotech companies. To reduce costs, to speed up the discovery process and to increase the chance of success, advanced methods of rational drug design are very helpful, as demonstrated by several successful applications. Among these, computational methods able to predict the binding affinity of small molecules to specific biological targets are of special interest because they can accelerate the discovery of new hit compounds. Here we provide an overview of the most widely used methods in the field of binding affinity prediction, as well as of our own work in developing BEAR, an innovative methodology specifically devised to overtake some limitations in existing approaches. The BEAR method was successfully validated against different biological targets, and proved its efficacy in retrieving active compounds from virtual screening campaigns. The results obtained so far indicate that BEAR may become a leading tool in the drug discovery pipeline. We primarily discuss advantages and drawbacks of each technique and show relevant examples and applications in drug discovery.
    Biotechnology advances 08/2011; 30(1):244-50. · 8.25 Impact Factor
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    ABSTRACT: Cytochrome P450 aromatase catalyzes the conversion of androgen substrates into estrogens. Aromatase inhibitors (AIs) have been used as first-line drugs in the treatment of estrogen-dependent breast cancer in postmenopausal women. However, the search for new, more potent, and selective AIs still remains necessary to avoid the risk of possible resistances and reduce toxicity and side effects of current available drugs. The publication of a high resolution X-ray structure of human aromatase has opened the way to structure-based virtual screening to identify new small-molecule inhibitors with structural motifs different from all known AIs. In this context, a high-throughput docking protocol was set up and led to the identification of nanomolar AIs with new core structures.
    Journal of Medicinal Chemistry 06/2011; 54(12):4006-17. · 5.61 Impact Factor
  • Elena Muzzioli, Alberto Del Rio, Giulio Rastelli
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    ABSTRACT: An application of molecular dynamics and molecular mechanics Poisson-Boltzmann surface area techniques to the prediction of protein kinase inhibitor selectivity is presented. A highly active and selective ERK2 inhibitor was placed in equivalent orientations in five different protein kinases (SRC, LCK, GSK3, JNK3 and Aurora-A). Binding free energies were then computed with the molecular mechanics Poisson-Boltzmann surface area approach using 15 nanosecond fully solvated molecular dynamics trajectories of the corresponding protein-ligand complexes. The results show correlation with experimentally determined selectivities and provide useful insights into the underlying structural determinants for selectivity.
    Chemical Biology &amp Drug Design 05/2011; 78(2):252-9. · 2.47 Impact Factor
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    ABSTRACT: BEAR (binding estimation after refinement) is a new virtual screening technology based on the conformational refinement of docking poses through molecular dynamics and prediction of binding free energies using accurate scoring functions. Here, the authors report the results of an extensive benchmark of the BEAR performance in identifying a smaller subset of known inhibitors seeded in a large (1.5 million) database of compounds. BEAR performance proved strikingly better if compared with standard docking screening methods. The validations performed so far showed that BEAR is a reliable tool for drug discovery. It is fast, modular, and automated, and it can be applied to virtual screenings against any biological target with known structure and any database of compounds.
    Journal of Biomolecular Screening 11/2010; 16(1):129-33. · 2.21 Impact Factor
  • Journal of Biotechnology 11/2010; 150:94-95. · 3.18 Impact Factor
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    ABSTRACT: The 90 kDa heat shock protein (Hsp90) is a prominent target for anticancer drug discovery. While its N-terminal domain has been widely exploited, several lines of evidence are emerging in favor of targeting its C-terminal domain to conceive innovative drugs based on perturbation of the dimer interface. Here, we describe the application of several computational approaches useful to predict the location of the C-terminal binding site.
    Journal of Chemical Information and Modeling 09/2010; 50(9):1522-8. · 4.30 Impact Factor
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    ABSTRACT: Design of irreversible inhibitors is an emerging and relatively less explored strategy for the design of protein kinase inhibitors. In this paper, we present a computational workflow that was specifically conceived to assist such design. The workflow takes the form of a multi-step procedure that includes: the creation of a database of already known reversible inhibitors of protein kinases, the selection of the most promising scaffolds that bind one or more desired kinase templates, the modification of the scaffolds by introduction of chemically reactive groups (suitable cysteine traps) and the final evaluation of the reversible and irreversible protein-ligand complexes with molecular dynamics simulations and binding free energy predictions. Most of these steps were automated. In order to prove that this is viable, the workflow was tested on a database of known inhibitors of ERK2, a protein kinase possessing a cysteine in the ATP site. The modeled ERK2-ligand complexes and the values of the estimated binding free energies of the putative ligands provide useful indicators of their aptitude to bind reversibly and irreversibly to the protein kinase. Moreover, the computational data are used to rank the ligands according to their computed binding free energies and their ability to bind specific protein residues in the reversible and irreversible complexes, thereby providing a useful decision-making tool for each step of the design. In this work we present the overall procedure and the first proof of concept results.
    Journal of Computer-Aided Molecular Design 03/2010; 24(3):183-94. · 3.17 Impact Factor
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    ABSTRACT: ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
    ChemInform 01/2010; 31(28).
  • [Show abstract] [Hide abstract]
    ABSTRACT: ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
    ChemInform 01/2010; 30(16).
  • ChemInform 01/2010; 33(13).
  • [Show abstract] [Hide abstract]
    ABSTRACT: ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
    ChemInform 01/2010; 33(21).
  • Giulio Rastelli
    ChemMedChem 10/2009; 4(10). · 2.84 Impact Factor

Publication Stats

1k Citations
210.48 Total Impact Points

Institutions

  • 1997–2014
    • Università degli Studi di Modena e Reggio Emilia
      • • Department of Life Sciences
      • • Department of Biomedical, Metabolical and Neurosciences
      Modène, Emilia-Romagna, Italy
  • 2001–2010
    • Università degli Studi di Sassari
      • Department of Chemistry and Pharmacy
      Sassari, Sardinia, Italy
  • 2000–2002
    • Università di Pisa
      • Department of Biology
      Pisa, Tuscany, Italy