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Alessandro Deplano     Other 
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Alessandro Deplano published an article in January 2019.
Top co-authors
Valentina Onnis

136 shared publications

A Department of Life and Environmental Sciences - Unit of Pharmaceutical, Pharmacological and Nutraceutical Sciences , University of Cagliari , Cagliari , Italy

Jan Balzarini

71 shared publications

KU Leuven—University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, Leuven B-3000, Belgium

Sandra Liekens

33 shared publications

KU Leuven—University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, Leuven B-3000, Belgium

Salvatore Pacifico

26 shared publications

Department of Chemical and Pharmaceutical Sciences, University of Ferrara, 44121 Ferrara, Italy

Monica Demurtas

7 shared publications

Dipartimento di Scienze della Vita e dell’Ambiente, Università degli Studi di Cagliari, Cittadella Universitaria di Monserrato, 09042, Cagliari, Italy

17
Publications
62
Reads
23
Downloads
30
Citations
Publication Record
Distribution of Articles published per year 
(2014 - 2019)
Total number of journals
published in
 
12
 
Publications See all
Article 0 Reads 0 Citations Benzylamides and piperazinoarylamides of ibuprofen as fatty acid amide hydrolase inhibitors Alessandro Deplano, Mariateresa Cipriano, Federica Moraca, E... Published: 27 January 2019
Journal of Enzyme Inhibition and Medicinal Chemistry, doi: 10.1080/14756366.2018.1532418
DOI See at publisher website
Article 0 Reads 0 Citations Development and Validation of Molecular Overlays Derived from Three-Dimensional Hydrophobic Similarity with PharmScreen Javier Vázquez, Alessandro Deplano, Albert Herrero, Tiziana ... Published: 16 July 2018
Journal of Chemical Information and Modeling, doi: 10.1021/acs.jcim.8b00216
DOI See at publisher website
Article 0 Reads 3 Citations Novel propanamides as fatty acid amide hydrolase inhibitors Alessandro Deplano, Carmine Marco Morgillo, Monica Demurtas,... Published: 01 August 2017
European Journal of Medicinal Chemistry, doi: 10.1016/j.ejmech.2017.05.033
DOI See at publisher website PubMed View at PubMed
Article 0 Reads 3 Citations Design, synthesis and antiviral evaluation of novel heteroarylcarbothioamide derivatives as dual inhibitors of HIV-1 rev... Angela Corona, Valentina Onnis, Alessandro Deplano, Giulia B... Published: 10 July 2017
Pathogens and Disease, doi: 10.1093/femspd/ftx078
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Article 0 Reads 3 Citations Homology modeling of a Class A GPCR in the inactive conformation: A quantitative analysis of the correlation between mod... Stefano Costanzi, Matthew Skorski, Alessandro Deplano, Brett... Published: 01 November 2016
Journal of Molecular Graphics and Modelling, doi: 10.1016/j.jmgm.2016.10.004
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
With the present work we quantitatively studied the modellability of the inactive state of Class A G protein-coupled receptors (GPCRs). Specifically, we constructed models of one of the Class A GPCRs for which structures solved in the inactive state are available, namely the β2 AR, using as templates each of the other class members for which structures solved in the inactive state are also available. Our results showed a detectable linear correlation between model accuracy and model/template sequence identity. This suggests that the likely accuracy of the homology models that can be built for a given receptor can be generally forecasted on the basis of the available templates. We also probed whether sequence alignments that allow for the presence of gaps within the transmembrane domains to account for structural irregularities afford better models than the classical alignment procedures that do not allow for the presence of gaps within such domains. As our results indicated, although the overall differences are very subtle, the inclusion of internal gaps within the transmembrane domains has a noticeable a beneficial effect on the local structural accuracy of the domain in question.
Article 0 Reads 1 Citation Potent Nematicidal Activity of Maleimide Derivatives on Meloidogyne incognita Kodjo Eloh, Monica Demurtas, Manuel Giacomo Mura, Alessandro... Published: 09 June 2016
Journal of Agricultural and Food Chemistry, doi: 10.1021/acs.jafc.6b02250
DOI See at publisher website PubMed View at PubMed
Conference papers
CONFERENCE-ARTICLE 28 Reads 0 Citations Discovery of novel endocannabinoid level modulators by modification of old analgesic drugs Alessandro Deplano, Monica Demurtas, Valentina Onnis Published: 31 October 2018
doi: 10.3390/ecmc-4-05590
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Fatty acid amide hydrolase (FAAH) is a serine hydrolase that catalyzes the deactivating hydrolysis of the fatty acid ethanolamide family of signaling lipids, which includes anandamide (AEA), an endogenous ligand for cannabinoid receptors. Endogenous FAAH substrates such as AEA serve key regulatory functions in the body and have been implicated in a variety of pathological conditions including pain, inflammation, sleep disorders, anxiety, depression, and vascular hypertension, and there has been an increasing interest in the development of inhibitors of this enzyme.
Different structural classes of FAAH inhibitors have been reported including alpha-ketoheterocycles, (thio)hydantoins, piperidine/piperazine ureas, and carbamate derivatives. When tested, these compounds have been shown to be efficacious in models of inflammatory, visceral, and in some cases
neuropathic pain without producing the central effects seen with directly acting cannabinoid receptor agonists. An intriguing aspect of FAAH inhibition is that some currently marketed nonsteroidal anti-inflammatory drugs (NSAIDs) have also been shown to be weak inhibitors of FAAH, but can be used as a template for the design of more potent compounds. However, structure–activity relationships of analogues of clinically used NSAIDs with respect to FAAH inhibition have been examined scarcely in the literature. These findings led us to design and synthesis of new series of FAAH inhibitors derivable from conjugation of heterocyclic structures with NSAIDs as profens, fenamates, and new their correlate molecules. In this keynote we report on the synthetic pathways to transform old analgesic drugs into FAAH inhibitors and SAR studies on the new inhibitor series.

CONFERENCE-ARTICLE 30 Reads 0 Citations Field-based virtual screening: New trends to increase the chemical diversity of your leads Alessandro Deplano, Javier Vázquez, Albert Herrero, Enric Gi... Published: 31 October 2018
doi: 10.3390/ecmc-4-05589
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Computational chemistry methods can significantly reduce experimental costs in early stages of a drug development project by filtering out unsuitable candidates and discovering new chemical matter. Molecular alignment is a key pre-requisite for 3D similarity evaluation between compounds and pharmacophore elucidation. Relying on the hypothesis that the variation in maximal achievable binding affinity for an optimized drug-like molecule is largely due to desolvation, we explore herein a novel small molecule 3D alignment strategy that exploits the partitioning of molecular hydrophobicity into atomic contributions in conjunction with information about the distribution of hydrogen-bond donor/acceptor groups in each compound. A brief description of the method, as implemented in the software package PharmScreen, is presented. The computational procedure is calibrated by using a dataset of 402 molecules pertaining to 14 distinct targets taken from the literature and validated against the CCDC AstraZeneca test set of 121 experimentally derived molecular overlays. The results confirm the suitability of MST based-hydrophobic parameters for generating molecular overlays with correct predictions obtained for 100%, 93%, and 55% of the molecules classified into easy, moderate and hard sets, respectively. The potential of this tool in a drug discovery campaign is then evaluated in a retrospective study with the aim to evaluate the correlations between activities and similarity score of a series of sigma-1 receptor ligands. The results confirm the suitability of the tool for Drug Discovery purposes finding the 67% of the most active ligands (≤10 nM) in Q1 of the ranking and the most active compound in position five.

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