A number of incurable retinal diseases causing vision impairments derive from alterations in visual phototransduction. Unraveling the structural determinants of even monogenic retinal diseases would require network-centered approaches combined with atomistic simulations. The transducin G38D mutant associated with the Nougaret Congenital Night Blindness (NCNB) was thoroughly investigated by both mathematical modeling of visual phototransduction and atomistic simulations on the major targets of the mutational effect. Mathematical modeling, in line with electrophysiological recordings, indicates reduction of phosphodiesterase 6 (PDE) recognition and activation as the main determinants of the pathological phenotype. Sub-microsecond molecular dynamics (MD) simulations coupled with Functional Mode Analysis improve the resolution of information, showing that such impairment is likely due to disruption of the PDEgamma binding cavity in transducin. Protein Structure Network analyses additionally suggest that the observed slight reduction of theRGS9-catalyzed GTPase activity of transducin depends on perturbed communication between RGS9 and GTP binding site. These findings provide insights into the structural fundamentals of abnormal functioning of visual phototransduction caused by a missense mutation in one component of the signaling network. This combination of network-centered modeling with atomistic simulations represents a paradigm for future studies aimed at thoroughly deciphering the structural determinants of genetic retinal diseases. Analogous approaches are suitable to unveil the mechanism of information transfer in any signaling network either in physiological or pathological conditions.

Network and atomistic simulations unveil the structural determinants of mutations linked to retinal diseases / S., Mariani; D., Dell'Orco; Felline, Angelo Nicola; Raimondi, Francesco; Fanelli, Francesca. - In: PLOS COMPUTATIONAL BIOLOGY. - ISSN 1553-7358. - ELETTRONICO. - 9:(2013), pp. e1003207-e1003207. [10.1371/journal.pcbi.1003207]

Network and atomistic simulations unveil the structural determinants of mutations linked to retinal diseases

FELLINE, Angelo Nicola;RAIMONDI, Francesco;FANELLI, Francesca
2013

Abstract

A number of incurable retinal diseases causing vision impairments derive from alterations in visual phototransduction. Unraveling the structural determinants of even monogenic retinal diseases would require network-centered approaches combined with atomistic simulations. The transducin G38D mutant associated with the Nougaret Congenital Night Blindness (NCNB) was thoroughly investigated by both mathematical modeling of visual phototransduction and atomistic simulations on the major targets of the mutational effect. Mathematical modeling, in line with electrophysiological recordings, indicates reduction of phosphodiesterase 6 (PDE) recognition and activation as the main determinants of the pathological phenotype. Sub-microsecond molecular dynamics (MD) simulations coupled with Functional Mode Analysis improve the resolution of information, showing that such impairment is likely due to disruption of the PDEgamma binding cavity in transducin. Protein Structure Network analyses additionally suggest that the observed slight reduction of theRGS9-catalyzed GTPase activity of transducin depends on perturbed communication between RGS9 and GTP binding site. These findings provide insights into the structural fundamentals of abnormal functioning of visual phototransduction caused by a missense mutation in one component of the signaling network. This combination of network-centered modeling with atomistic simulations represents a paradigm for future studies aimed at thoroughly deciphering the structural determinants of genetic retinal diseases. Analogous approaches are suitable to unveil the mechanism of information transfer in any signaling network either in physiological or pathological conditions.
2013
9
e1003207
e1003207
Network and atomistic simulations unveil the structural determinants of mutations linked to retinal diseases / S., Mariani; D., Dell'Orco; Felline, Angelo Nicola; Raimondi, Francesco; Fanelli, Francesca. - In: PLOS COMPUTATIONAL BIOLOGY. - ISSN 1553-7358. - ELETTRONICO. - 9:(2013), pp. e1003207-e1003207. [10.1371/journal.pcbi.1003207]
S., Mariani; D., Dell'Orco; Felline, Angelo Nicola; Raimondi, Francesco; Fanelli, Francesca
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/980508
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