Current Proteomics - Volume 21, Issue 3, 2024

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition. The genetic basis of ASD involves numerous loci converging on neural pathways, particularly affecting excitatory synapses. SHANK3, an essential protein in the post-synaptic neurons, has been implicated in ASD, with mutations affecting its N-terminal, including the SPN domain.

This study aims to investigate the impact of the N52R mutation on SHANK3 and assess the dynamics, stability, flexibility, and compactness of the N52R mutant compared to SHANK3 WT.

Molecular dynamics simulations were conducted to investigate the structural dynamics of SHANK3 WT and the N52R mutant. The simulations involved heating dynamics, density equilibrium, and production dynamics. The trajectories were analyzed for RMSD, RMSF, Rg, hydrogen bond analysis, and secondary structure.

The simulations revealed that the N52R mutant disrupts the stability and folding of SHANK3, affecting intramolecular contacts between SPN and ARR. This disruption opens up the distance between SPN and ARR domains, potentially influencing the protein's interactions with partners, including αCaMKII and α-Fodrin. The altered conformation of the SPN-ARR tandem in the N52R mutant suggests a potential impact on dendritic spine shape and synaptic plasticity.

The findings shed light on the structural consequences of the N52R mutation in SHANK3, emphasizing its role in influencing intramolecular interactions and potential effects on synaptic function. Understanding these molecular dynamics contributes to unraveling the intricate relationship between genetic variations in SHANK3 and clinical traits associated with ASD. Further investigations are warranted to explore the physiological implications of these structural alterations in vivo.

Hypothetical proteins (HPs) are those proteins whose functions are unknown; therefore, the present study was carried out to predict similarity-based functionality of HPs in selected bacteria Streptomyces coelicolor A3(2) and Neisseria meningitidis.

Annotation-based approaches using Pfam, orthology, String, Bi-directional Best Blast Hit, PSLpred, Subloc, Cello, homology modeling, and computational tools were used in evaluating the functionality of HPs.

Thirty-one domains in both bacterial species were retrieved based on the E-value score and compared with bacterial species already existing in databases. Statistical analysis was duly done to check which features performed well.

Out of 31 HPs found in Streptomyces coleicolor strain A3(2), 14 domains were found to be uncharacterized in their functionality, while 2 uncharacterized domains in the case of Neisseria meningitidis were assigned a function on similarity-based approaches. The annotation of HPs is a challenge in bacteria as these are based on the similarity of proteins in other species.

Diabetic kidney disease (DKD) is a common microvascular complication of diabetic mellitus (DM). At present, the early diagnosis of DKD mainly depends on microalbuminuria, which is prone to be affected by confounding factors such as urinary tract infections.

To identify the more stable early diagnosis markers, the whole proteome in the circulating exosomes from controls, DM patients, and DKD patients was quantified by label-free proteomics analysis and then validated with parallel reaction monitoring.

Three hundred ninety-one quantitative proteins were detected, and the expression trends of 7 proteins in the validation phase were consistent with that in the discovery phase. The expression level assessment results revealed that the expression of EFEMP1 and ApoA4 in the DKD group was significantly higher than those in DM and controls. Correlation analysis showed that EFEMP1 and APOA4 were positively correlated with urinary microalbumin and urinary albumin creatinine ratio and had excellent diagnostic values for distinguishing DKD from DM and controls.

ApoA4 and EFEMP1 could serve as the early diagnosis markers of DKD. These findings provide a possibility for the development of a clinical diagnostic index that can efficiently distinguish DKD from DM in the near future.