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Molecules 2018, 23(1), 120; https://doi.org/10.3390/molecules23010120

Speeding Up the Identification of Cystic Fibrosis Transmembrane Conductance Regulator-Targeted Drugs: An Approach Based on Bioinformatics Strategies and Surface Plasmon Resonance

1
Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy
2
Institute for Biomedical Technologies, National Research Council (ITB-CNR), 20090 Segrate, Italy
3
Department of Pharmacy, Section of Medicinal Chemistry, School of Medical and Pharmaceutical Sciences, University of Genoa, 16132 Genoa, Italy
4
Department of Experimental Medicine, Section of Biochemistry, University of Genoa, 16132 Genoa, Italy
5
Center of Excellence for Biomedical Research (CEBR), University of Genoa, 16132 Genoa, Italy
6
Istituto Giannina Gaslini, 16147 Genoa, Italy
These authors contributed equally to this work.
*
Authors to whom correspondence should be addressed.
Received: 24 October 2017 / Revised: 29 December 2017 / Accepted: 4 January 2018 / Published: 8 January 2018
(This article belongs to the Section Medicinal Chemistry)
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Abstract

Cystic fibrosis (CF) is mainly caused by the deletion of Phe 508 (ΔF508) in the cystic fibrosis transmembrane conductance regulator (CFTR) protein that is thus withheld in the endoplasmic reticulum and rapidly degraded by the ubiquitin/proteasome system. New drugs able to rescue ΔF508-CFTR trafficking are eagerly awaited. An integrated bioinformatics and surface plasmon resonance (SPR) approach was here applied to investigate the rescue mechanism(s) of a series of CFTR-ligands including VX809, VX770 and some aminoarylthiazole derivatives (AAT). Computational studies tentatively identified a large binding pocket in the ΔF508-CFTR nucleotide binding domain-1 (NBD1) and predicted all the tested compounds to bind to three sub-regions of this main pocket. Noticeably, the known CFTR chaperone keratin-8 (K8) seems to interact with some residues located in one of these sub-pockets, potentially interfering with the binding of some ligands. SPR results corroborated all these computational findings. Moreover, for all the considered ligands, a statistically significant correlation was determined between their binding capability to ΔF508-NBD1 measured by SPR and the pockets availability measured by computational studies. Taken together, these results demonstrate a strong agreement between the in silico prediction and the SPR-generated binding data, suggesting a path to speed up the identification of new drugs for the treatment of cystic fibrosis. View Full-Text
Keywords: cystic fibrosis; computational chemistry; molecular dynamics; molecular modeling; surface plasmon resonance cystic fibrosis; computational chemistry; molecular dynamics; molecular modeling; surface plasmon resonance
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Rusnati, M.; Sala, D.; Orro, A.; Bugatti, A.; Trombetti, G.; Cichero, E.; Urbinati, C.; Di Somma, M.; Millo, E.; Galietta, L.J.V.; Milanesi, L.; Fossa, P.; D’Ursi, P. Speeding Up the Identification of Cystic Fibrosis Transmembrane Conductance Regulator-Targeted Drugs: An Approach Based on Bioinformatics Strategies and Surface Plasmon Resonance. Molecules 2018, 23, 120.

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