In Silico Analysis of the Molecular-Level Impact of SMPD1 Variants on Niemann-Pick Disease Severity

Autor: François Ancien, Marianne Rooman, Fabrizio Pucci
Přispěvatelé: Department of Bio-engineering Sciences, Faculty of Sciences and Bioengineering Sciences, IR Academic Unit
Jazyk: angličtina
Rok vydání: 2021
Předmět:
0301 basic medicine
Genetic variants
Informatique appliquée logiciel
Disease
Sphingomyelin phosphodiesterase
Severity of Illness Index
Physico-chimie générale
0302 clinical medicine
Molecular level
hemic and lymphatic diseases
Databases
Genetic
Exons/genetics
Sphingomyelin Phosphodiesterase/genetics
Biology (General)
Spectroscopy
Niemann-Pick Diseases
General Medicine
Exons
Phenotype
Computer Science Applications
Parkinson disease
Chemistry
Genetic Variation/genetics
disease severity prediction
Niemann–Pick disease
Niemann-Pick disease
Mutation/genetics
QH301-705.5
In silico
Computational biology
Biology
Chimie inorganique
sphingomyelin phosphodiesterase
Catalysis
Article
Inorganic Chemistry
03 medical and health sciences
medicine
Humans
Computer Simulation
Spectroscopie [état condense]
Physical and Theoretical Chemistry
Molecular Biology
QD1-999
Sphingolipids
genetic variants
Organic Chemistry
Genetic Variation
Biologie moléculaire
Chimie théorique
Disease severity prediction
medicine.disease
Chimie organique
030104 developmental biology
Spectroscopie [électromagnétisme
optique
acoustique]
Sphingolipid metabolism
Mutation
Catalyses hétérogène et homogène
Sphingolipids/genetics
030217 neurology & neurosurgery
Function (biology)
Niemann-Pick Diseases/genetics
Zdroj: International Journal of Molecular Sciences
Volume 22
Issue 9
International journal of molecular sciences, 22 (9
International Journal of Molecular Sciences, Vol 22, Iss 4516, p 4516 (2021)
ISSN: 1422-0067
DOI: 10.3390/ijms22094516
Popis: Sphingomyelin phosphodiesterase (SMPD1) is a key enzyme in the sphingolipid metabolism. Genetic SMPD1 variants have been related to the Niemann-Pick lysosomal storage disorder, which has different degrees of phenotypic severity ranging from severe symptomatology involving the central nervous system (type A) to milder ones (type B). They have also been linked to neurodegenerative disorders such as Parkinson and Alzheimer. In this paper, we leveraged structural, evolutionary and stability information on SMPD1 to predict and analyze the impact of variants at the molecular level. We developed the SMPD1-ZooM algorithm, which is able to predict with good accuracy whether variants cause Niemann-Pick disease and its phenotypic severity; the predictor is freely available for download. We performed a large-scale analysis of all possible SMPD1 variants, which led us to identify protein regions that are either robust or fragile with respect to amino acid variations, and show the importance of aromatic-involving interactions in SMPD1 function and stability. Our study also revealed a good correlation between SMPD1-ZooM scores and in vitro loss of SMPD1 activity. The understanding of the molecular effects of SMPD1 variants is of crucial importance to improve genetic screening of SMPD1-related disorders and to develop personalized treatments that restore SMPD1 functionality.
SCOPUS: ar.j
info:eu-repo/semantics/published
Databáze: OpenAIRE
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