Exploitation of a novel biosensor based on the full-length human F508del-CFTR with computational studies, biochemical and biological assays for the characterization of a new Lumacaftor/Tezacaftor analogue

D’Ursi, Pasqualina; Uggeri, Matteo; Urbinati, Chiara; Millo, Enrico; Paiardi, Giulia; Milanesi, Luciano; Ford, Robert C.; Clews, Jack; Meng, Xianjun; Bergese, Paolo; Ridolfi, Andrea; Pedemonte, Nicoletta; Fossa, Paola; Orro, Alessandro; Rusnati, Marco

doi:10.1016/j.snb.2019.127131

Cited by 11 publications

(47 citation statements)

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“…Important to note, the validity of the proposed pipeline can be already assessed retrospectively, by evaluating the degree of consensus of the prediction and results obtained with the various techniques employed. In effect, already reported cases of this consensus are: computational predictions vs. SPR [52] or vs. cell-based assays [49], immunoprecipitation vs. overlay assays or vs. SPR [70], SPR vs. thermostability assays or vs. cell-based assays [48].…”

Section: Discussionmentioning

confidence: 99%

“…Among the computational models listed above, only a few have been used to better characterize the binding mode of known F508del-CFTR-rescuing drugs, to virtually screen libraries of molecules aimed at the identification of new putative F508del-CFTR-binding compounds or to design new CFTR-targeted drugs [48,49]. On the contrary, a huge amount of computational studies has been developed in the attempt of clarifying at a molecular level the mechanism of action of F508del-CFTR-ligands, using several NBDs RX data [23,[50][51][52] or the more recent cryo EM structures [53].…”

Section: Cftr Computational Modelsmentioning

confidence: 99%

“…(ii) SPR has been used to the study of the direct interaction with mutated CFTR of correctors VRT-325 and Corr-4a [14] and of either F508del-NBD1 [52] or intact F508del-CFTR [48] with a panel of AAT derivatives. Additionally, the pyrazole compound 4172 was demonstrated to bind F508del-CFTR with an affinity that is 25 times higher than that of the first identified type III corrector BIA [73].…”

Section: Binding Assays: Surface Plasmon Resonance (Spr) Spectroscopymentioning

confidence: 99%

“…As apparent by Figure 4D and Tables 3 and 4, a large part of SPR studies have been so far directed only to NBD1, which may not contain the features needed to build high-affinity interactions [23], greatly limiting the identification of high-affinity CFTR-rescuing drugs. Relevant to this point, a purified form of human intact F508del-CFTR [75] has been recently used to identify new putative CF drugs and to characterize the CFTR-binding modes and/or molecular mechanisms of action of known CF drugs such as VX660, VX770 and VX809 [48,76].…”

Section: Binding Assays: Surface Plasmon Resonance (Spr) Spectroscopymentioning

confidence: 99%

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Recent Strategic Advances in CFTR Drug Discovery: An Overview

Rusnati

D’Ursi

Pedemonte

et al. 2020

IJMS

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Cystic fibrosis transmembrane conductance regulator (CFTR)-rescuing drugs have already transformed cystic fibrosis (CF) from a fatal disease to a treatable chronic condition. However, new-generation drugs able to bind CFTR with higher specificity/affinity and to exert stronger therapeutic benefits and fewer side effects are still awaited. Computational methods and biosensors have become indispensable tools in the process of drug discovery for many important human pathologies. Instead, they have been used only piecemeal in CF so far, calling for their appropriate integration with well-tried CF biochemical and cell-based models to speed up the discovery of new CFTR-rescuing drugs. This review will give an overview of the available structures and computational models of CFTR and of the biosensors, biochemical and cell-based assays already used in CF-oriented studies. It will also give the reader some insights about how to integrate these tools as to improve the efficiency of the drug discovery process targeted to CFTR.

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Section: Discussionmentioning

confidence: 99%

Section: Cftr Computational Modelsmentioning

confidence: 99%

Section: Binding Assays: Surface Plasmon Resonance (Spr) Spectroscopymentioning

confidence: 99%

Section: Binding Assays: Surface Plasmon Resonance (Spr) Spectroscopymentioning

confidence: 99%

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Recent Strategic Advances in CFTR Drug Discovery: An Overview

Rusnati

D’Ursi

Pedemonte

et al. 2020

IJMS

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“…The drugs of the data set were evaluated for their capability to bind F508del-CFTR by means of a suitable F508del-CFTR 3D model available to date (further described below) and an ad hoc designed pipeline, whose first part (Fig. 1, part A) overlaps that already used in our previous work to identify the druggable pocket 1 (DP1) by using VX809 as template [24].…”

Section: Computational Drug Repositioningmentioning

confidence: 99%

In silico drug repositioning on F508del-CFTR: A proof-of-concept study on the AIFA library

Orro

Uggeri

Rusnati

et al. 2021

European Journal of Medicinal Chemistry

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Computational drug repositioning is of growing interest to academia and industry, for its ability to rapidly screen a huge number of candidates in silico (exploiting comprehensive drug datasets) together with reduced development cost and time. The potential of drug repositioning has not been fully evaluated yet for cystic fibrosis (CF), a disease mainly caused by deletion of Phe 508 (F508del) of the cystic fibrosis transmembrane conductance regulator (CFTR) protein. F508del-CFTR is thus withheld in the endoplasmic reticulum and rapidly degraded by the ubiquitin/proteasome system. CF is still a fatal disease. Nowadays, it is treatable by some CFTR-rescuing drugs, but new-generation drugs with stronger therapeutic benefits and fewer side effects are still awaited. In this manuscript we report about the results of a pilot computational drug repositioning screening in search of F508del-CFTR-targeted drugs performed on AIFA library by means of a dedicated computational pipeline and surface plasmon resonance binding assay to experimentally validate the computational findings.

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