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Modelling and Characterization of Glial Fibrillary Acidic Protein.

ABSTRACT: Glial Fibrillary Acidic Protein (GFAP) is an intermediate-filament (IF) protein that maintains the astrocytes of the Central Nervous System in Human. This is differentially expressed during serological studies in inflamed condition such as Rheumatoid Arthritis (RA). Therefore, it is of interest to glean molecular insight using a model of GFAP (49.88 kDa) due to its crystallographic nonavailability. The present study has been taken into consideration to construct computational protein model using Modeller 9.11. The structural relevance of the protein was verified using Gromacs 4.5 followed by validation through PROCHECK, Verify 3D, WHAT-IF, ERRAT and PROVE for reliability. The constructed three dimensional (3D) model of GFAP protein had been scrutinized to reveal the associated functions by identifying ligand binding sites and active sites. Molecular level interaction study revealed five possible surface cavities as active sites. The model finds application in further computational analysis towards drug discovery in order to minimize the effect of inflammation.

SUBMITTER: Deka H

PROVIDER: S-EPMC4574122 | biostudies-other | 2015

REPOSITORIES: biostudies-other

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Modelling and Characterization of Glial Fibrillary Acidic Protein.

Deka Hemchandra H Sarmah Rajeev R Sharma Ankita A Biswas Sagarika S

Bioinformation 20150831 8

Glial Fibrillary Acidic Protein (GFAP) is an intermediate-filament (IF) protein that maintains the astrocytes of the Central Nervous System in Human. This is differentially expressed during serological studies in inflamed condition such as Rheumatoid Arthritis (RA). Therefore, it is of interest to glean molecular insight using a model of GFAP (49.88 kDa) due to its crystallographic nonavailability. The present study has been taken into consideration to construct computational protein model using ...[more]

PMID: 26420920

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Project description:IntroductionThere is a tremendous need for identifying reliable blood-based biomarkers for Alzheimer's disease (AD) that are tied to the biological ATN (amyloid, tau and neurodegeneration) framework as well as clinical assessment and progression.MethodsOne hundred forty-four elderly participants underwent 18F-AV45 positron emission tomography (PET) scan, structural magnetic resonance imaging (MRI) scan, and blood sample collection. The composite standardized uptake value ratio (SUVR) was derived from 18F-AV45 PET to assess brain amyloid burden, and the hippocampal volume was determined from structural MRI scans. Plasma glial fibrillary acidic protein (GFAP), phosphorylated tau-181 (ptau-181), and neurofilament light (NfL) measured by single molecular array (SIMOA) technology were assessed with respect to ATN framework, genetic risk factor, age, clinical assessment, and future functional decline among the participants.ResultsAmong the three plasma markers, GFAP best discriminated participants stratified by clinical diagnosis and brain amyloid status. Age was strongly associated with NfL, followed by GFAP and ptau-181 at much weaker extent. Brain amyloid was strongly associated with plasma GFAP and ptau-181 and to a lesser extent with plasma NfL. Moderate association was observed between plasma markers. Hippocampal volume was weakly associated with all three markers. Elevated GFAP and ptau-181 were associated with worse cognition, and plasma GFAP was the most predictive of future functional decline. Combining GFAP and ptau-181 together was the best model to predict brain amyloid status across all participants (AUC = 0.86) or within cognitively impaired participants (AUC = 0.93); adding NfL as an additional predictor only had a marginal improvement.ConclusionOur findings indicate that GFAP is of potential clinical utility in screening amyloid pathology and predicting future cognitive decline. GFAP, NfL, and ptau-181 were moderately associated with each other, with discrepant relevance to age, sex, and AD genetic risk, suggesting their relevant but differential roles for AD assessment. The combination of GFAP with ptau-181 provides an accurate model to predict brain amyloid status, with the superior performance of GFAP over ptau-181 when the prediction is limited to cognitively impaired participants.

Dataset Information

Modelling and Characterization of Glial Fibrillary Acidic Protein.

Publications

Modelling and Characterization of Glial Fibrillary Acidic Protein.

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