Bioinformatics classification of mutations in patients with Mucopolysaccharidosis IIIA

Differential glycosylation in mutant vitamin D-binding protein decimates the binding stability of vitamin D

Vitamin D (VD) is produced by the skin upon exposure to sunlight or is obtained from dietary sources. Several risk factors are associated with VD deficiency including mutations and post-translational modifications in its transport protein known as vitamin D binding protein (VDBP) or GC-globulin. The two common single nucleotide polymorphisms rs7041 and rs4588 create three major isoforms of VDBP, including GC-1F also called wild type, GC1S, and GC-2. The 3D models for both GC-1F and GC-2 were constructed in their glycosylated states to decipher the effect of these mutations on the overall conformational changes and VD-binding affinity. The binding affinities were estimated using the Molecular Mechanics Poison-Boltzmann surface area (MM-PBSA) method and conformational changes were investigated after free energy landscapes estimations. Total free energies suggest that GC-1F exhibits stronger affinity (ΔE = -116.09 kJ/mol) than GC-2 (ΔE = -95 kJ/mol) variant with VD. The GC-1F isoforms had more streamlined motion compared to GC-2 isoforms, predicting a trade-off between cross-talk residues that significantly impacts protein structural stability. The data suggest that glycation at Thr418 plays a vital role in the overall VDBP-VD affinity by stabilizing the N-T loop that holds the domain I (VD-pocket) and domain III intact. The loss of glycation in GC-2 has a pivotal role in the inter-domain conformational stability of VDBP, which may ultimately affect VD transportation and maturation. These findings describe a novel mechanism in how mutations distant from the VD-active site change the overall conformational of the VDBP and abrogate the VDBP-VD interaction.Communicated by Ramaswamy H. Sarma.

Unravelling the Relacatib activity against the CTSK proteins causing pycnodysostosis: a molecular docking and dynamics approach

Pycnodysostosis is an atypical autosomal recessive condition of Lysosomal storage disorder that originated due to the deficit of the enzyme Cathepsin K which is vital for normal osteoclast action in bone resorption. Abnormal degradation of type 1 collagen and accumulation of toxic undigested collagen fibers in lysosomes of the osteoclast cells resulting in high bone density, brittle bones, and a short stature is caused in CTSK protein-carrying individuals. The broad aim of this study is to identify the most significant variant through various computational pipelines. This study was initiated by retrieving a total number of thirty-six variants from NCBI, HGMD, and UniProt databases, and the Y283C variant was found to be more significant by various standard computational tools. A structural investigation was performed to understand and gain a better knowledge about the interaction profile for the native (1BY8) and variant (Y283C) with Relacatib (a small-molecule drug that blocks the function of Cathepsin K, an enzyme that has been linked to osteoporosis, osteoarthritis, and other bone-degrading diseases). The interaction profile was analyzed using molecular docking. Relacatib (ligand) had an average binding affinity for both native (-7.16 kcal/mol) and Y283C (-6.76 kcal/mol). Finally, Molecular dynamics simulations were done in duplicates to recognize the variant (Y283C) activity of the protein structure against Relacatib for 100 ns. This study assists in comprehending the most pathogenic amino-acid variant, the ligand interaction with the protein structure, and paves the way for understanding the steadiness of the ligand with the native and selected significant amino-acid variant.Communicated by Ramaswamy H. Sarma.

A computational approach to analyzing the functional and structural impacts of Tripeptidyl-Peptidase 1 missense mutations in neuronal ceroid lipofuscinosis

Neuronal ceroid-lipofuscinosis (NCLs) are a group of severe neurodegenerative conditions, most likely present in infantile, late infantile, juvenile, and adult-onset forms. Their phenotypic characteristics comprise eyesight damage, reduced motor activity and cognitive function, and sometimes tend to die in the initial stage. In recent studies, NCLs have been categorized into at least 14 genetic collections (CLN1-14). CLN2 gene encodes Tripeptidyl peptidase 1 (TPP1), which affects late infantile-onset form. In this study, we retrieved a mutational dataset screening for TPP1 protein from various databases (ClinVar, UniProt, HGMD). Fifty-six missense mutants were enumerated with computational methods to perceive the significant mutants (G475R and G501C) and correlated with clinical and literature data. A structure-based screening method was initiated to understand protein-ligand interaction and dynamic simulation. The docking procedure was performed for the native (3EDY) and mutant (G473R and G501C) structures with Gemfibrozil (gem), which lowers the lipid level, decreases the triglycerides amount in the blood circulation, and controls hyperlipidemia. The Native had an interaction score of -5.57 kcal/mol, and the mutants had respective average binding scores of -6.24 (G473R) and - 5.17 (G501C) kcal/mol. Finally, molecular dynamics simulation showed that G473R and G501C mutants had better flexible and stable orientation in all trajectory analyses. Therefore, this work gives an extended understanding of both functional and structural levels of influence for the mutant form that leads to NCL disorder.

BMP4, SGSH, and SLC11A2 are Predicted to Be Biomarkers of Aging Associated with Programmed Cell Death

Most neurodegenerative diseases are exacerbated by aging, with symptoms often worsening over time. Programmed cell death (PCD) is a controlled cell suicide mechanism that is essential for the stability, growth, and homeostasis of organisms. Understanding the effects of aging at the level of systems biology could lead to new therapeutic approaches for a broad spectrum of neurodegenerative diseases. In the absence of comprehensive functional studies on the relationship between PCD and aging of the prefrontal cortex, this study provides prefrontal brain biomarkers of aging associated with PCD that could open the way for improved therapeutic techniques for age-related neurodegenerative diseases. To this end, publicly available transcriptome data were subjected to bioinformatic analyses such as differential gene expression, functional enrichment, and the weighted gene coexpression network analysis (WGCNA). The diagnostic utility of the biomarkers was tested using a logistic regression-based prediction model. Three genes, namely BMP4, SGSH, and SLC11A2, were found to be aging biomarkers associated with PCD. Finally, a multifactorial regulatory network with interacting proteins, transcription factors (TFs), competing endogenous RNAs (ceRNAs), and microRNAs (miRNAs) was constructed around these biomarkers. The elements of this multifactorial regulatory network were mainly enriched in BMP signaling. Further exploration of these three biomarkers and their regulatory elements would enable the development of 3PM (predictive, preventive, and personalized) medicine for the treatment of age-related neurodegenerative diseases.

Controlling cell proliferation by targeting cyclin-dependent kinase 6 using drug repurposing approach

Cyclin-dependent kinase 6 (CDK6) is an essential kinase in cell cycle progression, which is a viable target for inhibitors in various malignancies, including breast cancer. This study aimed to virtually screen efficient compounds as new leads in treating breast cancer using a drug repurposing approach. Apoptosis regulatory compounds were taken from the seleckchem database. Molecular docking experiments were carried out in the presence of abemaciclib, a routinely used FDA drug. Compared to conventional drugs, the two compounds demonstrated a higher binding affinity for CDK6. Compounds (N-benzyl-6-[(4-hydroxyphenyl)methyl]-8-(naphthalen-1-ylmethyl)-4,7-dioxo-3,6,9,9a-tetrahydro-2H-pyrazino[1,2-a]pyrimidine-1-carboxamide) and (1'-[4-[1-(4-fluorophenyl)indol-3-yl]butyl]spiro[1H-2-benzofuran-3,4'-piperidine]) were discovered to have an inhibitory effect against CDK6 at -8.49 and -6.78kcal/mol, respectively, compared to -8.09kcal/mol of the control molecule, the interacting residues of these two new compounds were found to fall within the binding site of the CDK6 molecule. Both compounds exhibited equal ADME features compared with abemaciclib and would be well distributed and metabolized by the body with an appropriate druglikeness range. Lastly, molecular dynamics was initiated for 200ns for the selected potent inhibitors and abemaciclib as complexed with CDK6. The RMSD, RMSF, Rg, H-Bond interactions, SASA, PCA, FEL, and MM/PBSA analysis were performed for the complexes to assess the stability, fluctuations, radius of gyration, hydrogen bond interaction, solvent accessibility, essential dynamics, free energy landscape, and MM/PBSA. The selected two compounds are small molecules in the appropriate druglikeness range. The results observed in molecular docking and molecular dynamics simulations were most promising for two compounds, suggesting their potent inhibitory effect against CDK6. We propose that these candidate compounds can undergo in vitro validation and in vivo testing for their further use against cancer.

Structure-based virtual screening, molecular dynamics simulation and in vitro evaluation to identify inhibitors against NAMPT

Nicotinamide phosphoribosyltransferase (NAMPT) is a bottleneck enzyme that plays a key role in recycling nicotinamide to maintain the adequate NAD + level inside the cell. It involves maintaining the cellular bioenergetics and providing a necessary substrate for functions essential to rapidly proliferating the cancer cells. Therefore, inhibition of NAMPT appears as a therapeutic potential for cancer treatment. Here, the vast virtual screening followed by focused docking and in-vitro analysis was carried out to identify the promising hits of NAMPT. We have identified two potential hits from the filtered molecules, which are chemically diverse and have shown comparable quantitative values with reported co-crystal '1QS' as their binding pattern matched nicely. These two compounds are further explored through molecular dynamics simulations (MD) combined with pharmacokinetics profiling and thermodynamic analysis demonstrating their suitability as novel NAMPT inhibitors that can be used as starting points for a hit-to-lead campaign.Communicated by Ramaswamy H. Sarma.

Decoding Diabetes Biomarkers and Related Molecular Mechanisms by Using Machine Learning, Text Mining, and Gene Expression Analysis

The molecular basis of diabetes mellitus is yet to be fully elucidated. We aimed to identify the most frequently reported and differential expressed genes (DEGs) in diabetes by using bioinformatics approaches. Text mining was used to screen 40,225 article abstracts from diabetes literature. These studies highlighted 5939 diabetes-related genes spread across 22 human chromosomes, with 112 genes mentioned in more than 50 studies. Among these genes, HNF4A, PPARA, VEGFA, TCF7L2, HLA-DRB1, PPARG, NOS3, KCNJ11, PRKAA2, and HNF1A were mentioned in more than 200 articles. These genes are correlated with the regulation of glycogen and polysaccharide, adipogenesis, AGE/RAGE, and macrophage differentiation. Three datasets (44 patients and 57 controls) were subjected to gene expression analysis. The analysis revealed 135 significant DEGs, of which CEACAM6, ENPP4, HDAC5, HPCAL1, PARVG, STYXL1, VPS28, ZBTB33, ZFP37 and CCDC58 were the top 10 DEGs. These genes were enriched in aerobic respiration, T-cell antigen receptor pathway, tricarboxylic acid metabolic process, vitamin D receptor pathway, toll-like receptor signaling, and endoplasmic reticulum (ER) unfolded protein response. The results of text mining and gene expression analyses used as attribute values for machine learning (ML) analysis. The decision tree, extra-tree regressor and random forest algorithms were used in ML analysis to identify unique markers that could be used as diabetes diagnosis tools. These algorithms produced prediction models with accuracy ranges from 0.6364 to 0.88 and overall confidence interval (CI) of 95%. There were 39 biomarkers that could distinguish diabetic and non-diabetic patients, 12 of which were repeated multiple times. The majority of these genes are associated with stress response, signalling regulation, locomotion, cell motility, growth, and muscle adaptation. Machine learning algorithms highlighted the use of the HLA-DQB1 gene as a biomarker for diabetes early detection. Our data mining and gene expression analysis have provided useful information about potential biomarkers in diabetes.

Dynamic insights into the effects of nonsynonymous polymorphisms (nsSNPs) on loss of TREM2 function

Single nucleotide variations in Triggering Receptor Expressed on Myeloid Cells 2 (TREM2) are associated with many neurodegenerative diseases, including Nasu-Hakola disease (NHD), frontotemporal dementia (FTD), and late-onset Alzheimer's disease because they disrupt ligand binding to the extracellular domain of TREM2. However, the effects of nonsynonymous single nucleotide polymorphisms (nsSNPs) in TREM2 on disease progression remain unknown. In this study, we identified several high-risk nsSNPs in the TREM2 gene using various deleterious SNP predicting algorithms and analyzed their destabilizing effects on the ligand recognizing region of the TREM2 immunoglobulin (Ig) domain by molecular dynamics (MD) simulation. Cumulative prediction by all tools employed suggested the three most deleterious nsSNPs involved in loss of TREM2 function are rs549402254 (W50S), rs749358844 (R52C), and rs1409131974 (D104G). MD simulation showed that these three variants cause substantial structural alterations and conformational remodeling of the apical loops of the TREM2 Ig domain, which is responsible for ligand recognition. Detailed analysis revealed that these variants substantially increased distances between apical loops and induced conformation remodeling by changing inter-loop nonbonded contacts. Moreover, all nsSNPs changed the electrostatic potentials near the putative ligand-interacting region (PLIR), which suggested they might reduce specificity or loss of binding affinity for TREM2 ligands. Overall, this study identifies three potential high-risk nsSNPs in the TREM2 gene. We propose further studies on the molecular mechanisms responsible for loss of TREM2 function and the associations between TREM2 nsSNPs and neurodegenerative diseases.

Structural Consequence of Non-Synonymous Single-Nucleotide Variants in the N-Terminal Domain of LIS1

Disruptive neuronal migration during early brain development causes severe brain malformation. Characterized by mislocalization of cortical neurons, this condition is a result of the loss of function of migration regulating genes. One known neuronal migration disorder is lissencephaly (LIS), which is caused by deletions or mutations of the LIS1 (PAFAH1B1) gene that has been implicated in regulating the microtubule motor protein cytoplasmic dynein. Although this class of diseases has recently received considerable attention, the roles of non-synonymous polymorphisms (nsSNPs) in LIS1 on lissencephaly progression remain elusive. Therefore, the present study employed combined bioinformatics and molecular modeling approach to identify potential damaging nsSNPs in the LIS1 gene and provide atomic insight into their roles in LIS1 loss of function. Using this approach, we identified three high-risk nsSNPs, including rs121434486 (F31S), rs587784254 (W55R), and rs757993270 (W55L) in the LIS1 gene, which are located on the N-terminal domain of LIS1. Molecular dynamics simulation highlighted that all variants decreased helical conformation, increased the intermonomeric distance, and thus disrupted intermonomeric contacts in the LIS1 dimer. Furthermore, the presence of variants also caused a loss of positive electrostatic potential and reduced dimer binding potential. Since self-dimerization is an essential aspect of LIS1 to recruit interacting partners, thus these variants are associated with the loss of LIS1 functions. As a corollary, these findings may further provide critical insights on the roles of LIS1 variants in brain malformation.

Computational strategies to identify new drug candidates against neuroinflammation

The even more increasing application of computational approaches in these last decades has deeply modified the process of discovery and commercialization of new therapeutic entities. This is especially true in the field of neuroinflammation, in which both the peculiar anatomical localization and the presence of the blood-brain barrier makeit mandatory to finely tune the candidates' physicochemical properties from the early stages of the discovery pipeline. The aim of this review is therefore to provide a general overview to the readers about the topic of neuroinflammation, together with the most common computational strategies that can be exploited to discover and design small molecules controlling neuroinflammation, especially those based on the knowledge of the three-dimensional structure of the biological targets of therapeutic interest. The techniques used to describe the molecular recognition mechanisms, such as molecular docking and molecular dynamics, will therefore be eviscerated, highlighting their advantages and their limitations. Finally, we report several case studies in which computational methods have been applied in drug discovery on neuroinflammation, focusing on the last decade's research.

Computational Insights into the Deleterious Impacts of Missense Variants on N-Acetyl-d-glucosamine Kinase Structure and Function

An enzyme of the mammalian amino-sugar metabolism pathway, N-acetylglucosamine kinase (NAGK), that synthesizes N-acetylglucosamine (GlcNAc)-6-phosphate, is reported to promote dynein functions during mitosis, axonal and dendritic growth, cell migration, and selective autophagy, which all are unrelated to its enzyme activity. As non-enzymatic structural functions can be altered by genetic variation, we made an effort in this study aimed at deciphering the pathological effect of nonsynonymous single-nucleotide polymorphisms (nsSNPs) in NAGK gene. An integrated computational approach, including molecular dynamics (MD) simulation and protein-protein docking simulation, was used to identify the damaging nsSNPs and their detailed structural and functional consequences. The analysis revealed the four most damaging variants (G11R, G32R, G120E, and A156D), which are highly conserved and functional, positioned in both small (G11R and G32R) and large (G120E and A156D) domains of NAGK. G11R is located in the ATP binding region, while variants present in the large domain (G120E and A156D) were found to induce substantial alterations in the structural organizations of both domains, including the ATP and substrate binding sites. Furthermore, all variants were found to reduce binding energy between NAGK and dynein subunit DYNLRB1, as revealed by protein-protein docking and MM-GBSA binding energy calculation supporting their deleteriousness on non-canonical function. We hope these findings will direct future studies to gain more insight into the role of these variants in the loss of NAGK function and their role in neurodevelopmental disorders.

A computational approach to analyse the amino acid variants of GLB1 protein causing GM1 Gangliosidosis

Lysosomal storage diseases comprise different forms of autosomal recessive disorders from which GM1 gangliosidosis has categorized by the accumulation of complex glycolipids associated with a range of progressive neurologic phenotypes. GM1 gangliosidosis is an inherited disorder that progressively destroys nerve cells (neurons) in the brain and spinal cord. GM1 has three main types of onsets, namely infantile (type I), juvenile (type II), and adult (type III) forms. This study provides a series of computational methods that examine the mutations that occurred in GLB1 protein. Initially, the mutational analysis started with 689 amino acid variants for a sequence-based screening and it was done with quite a few In-silico tools to narrow down the most significant variants by utilizing the standard tools; namely, Evolutionary analysis (77 variants), Pathogenicity prediction (44 variants), Stability predictions (30 variants), Biophysical functions (19 variants) and according to the binding site of protein structure with PDB ID 3THC, seven variants (Y83D, Y83H, Y270S, Y270D, W273R, W273D, and Y333H) were narrowed down. Structure based analysis was performed to understand the interacting profile of the native protein and variants with Miglustat; which is the currently used FDA drug as an alternative to enzyme replacement therapy. Molecular Docking study was done to analyze the protein interaction with Miglustat (ligand), as a result native (3THC) structure had a binding affinity of -8.18 kcal/mol and two variant structures had an average binding affinities of -2.61 kcal/mol (Y83D) and - 7.63 kcal/mol (Y270D). Finally, Molecular Dynamics Simulation was performed to know the mutational activity of the protein structures on Miglustat for 50,000 ps. The Y83D variant showed higher deviation than native protein and Y270D in all trajectory analysis. The analysis was done to the protein structures to check the structural variations happened through simulations. This study aids to understand the most deleterious mutants, the activity of the drug to the protein structure and also gives an insight on the stability of the drug with the native and selected variants.

Epidemiology of Mucopolysaccharidoses Update

Mucopolysaccharidoses (MPS) are a group of lysosomal storage disorders caused by a lysosomal enzyme deficiency or malfunction, which leads to the accumulation of glycosaminoglycans in tissues and organs. If not treated at an early stage, patients have various health problems, affecting their quality of life and life-span. Two therapeutic options for MPS are widely used in practice: enzyme replacement therapy and hematopoietic stem cell transplantation. However, early diagnosis of MPS is crucial, as treatment may be too late to reverse or ameliorate the disease progress. It has been noted that the prevalence of MPS and each subtype varies based on geographic regions and/or ethnic background. Each type of MPS is caused by a wide range of the mutational spectrum, mainly missense mutations. Some mutations were derived from the common founder effect. In the previous study, Khan et al. 2018 have reported the epidemiology of MPS from 22 countries and 16 regions. In this study, we aimed to update the prevalence of MPS across the world. We have collected and investigated 189 publications related to the prevalence of MPS via PubMed as of December 2020. In total, data from 33 countries and 23 regions were compiled and analyzed. Saudi Arabia provided the highest frequency of overall MPS because of regional or consanguineous marriages (or founder effect), followed by Portugal, Brazil, the Netherlands, and Australia. The newborn screening is an efficient and early diagnosis for MPS. MPS I has been approved for newborn screening in the United States. After the newborn screening of MPS I, the frequency of MPS I increased, compared with the past incidence rates. Overall, we conclude that the current identification methods are not enough to recognize all MPS patients, leading to an inaccurate incidence and status. Differences in ethnic background and/or founder effects impact on the frequency of MPS, which affects the prevalence of MPS. Two-tier newborn screening has accelerated early recognition of MPS I, providing an accurate incidence of patients.

Computational SNP Analysis and Molecular Simulation Revealed the Most Deleterious Missense Variants in the NBD1 Domain of Human ABCA1 Transporter

The ATP-binding cassette transporter A1 (ABCA1) is a membrane-bound exporter protein involved in regulating serum HDL level by exporting cholesterol and phospholipids to load up in lipid-poor ApoA-I and ApoE, which allows the formation of nascent HDL. Mutations in the ABCA1 gene, when presents in both alleles, disrupt the canonical function of ABCA1, which associates with many disorders related to lipid transport. Although many studies have reported the phenotypic effects of a large number of ABCA1 variants, the pathological effect of non-synonymous polymorphisms (nsSNPs) in ABCA1 remains elusive. Therefore, aiming at exploring the structural and functional consequences of nsSNPs in ABCA1, in this study, we employed an integrated computational approach consisting of nine well-known in silico tools to identify damaging SNPs and molecular dynamics (MD) simulation to get insights into the magnitudes of the damaging effects. In silico tools revealed four nsSNPs as being most deleterious, where the two SNPs (G1050V and S1067C) are identified as the highly conserved and functional disrupting mutations located in the NBD1 domain. MD simulation suggested that both SNPs, G1050V and S1067C, changed the overall structural flexibility and dynamics of NBD1, and induced substantial alteration in the structural organization of ATP binding site. Taken together, these findings direct future studies to get more insights into the role of these variants in the loss of the ABCA1 function.

Enzyme therapy: a forerunner in catalyzing a healthy society?

INTRODUCTION

The use of enzymes in various industries has been prevalent for centuries. However, their potency as therapeutics remained latent until the late 1950 s, when scientists finally realized the gold mine they were sitting on. Enzyme therapy has seen rapid development over the past few decades and has been widely used for the therapy of myriad diseases, including lysosomal storage disorders, cancer, Alzheimer's disease, irritable bowel syndrome, exocrine pancreatic insufficiency, and hyperuricemia. Enzymes are also used for wound healing, the treatment of microbial infections, and gene therapy.

AREAS COVERED

This is a comprehensive review of the therapeutic use of enzymes that can act as a guidepost for researchers and academicians and presents a general overview of the developments in enzyme therapy over the years, along with updates on recent advancements in enzyme therapy research.

EXPERT OPINION

Although enzyme therapy is immensely beneficial and induces little auxiliary damage, it has several drawbacks, ranging from high cost, low stability, low production, and hyperimmune responses to the failure to cure a variety of the problems associated with a disease. Further fine-tuning and additional clinical efficacy studies are required to establish enzyme therapy as a forerunner to catalyzing a healthy society.

Comprehensive in silico screening and molecular dynamics studies of missense mutations in Sjogren-Larsson syndrome associated with the ALDH3A2 gene

Sjögren-Larsson syndrome (SLS) is an autoimmune disorder inherited in an autosomal recessive pattern. To date, 80 missense mutations have been identified in association with the Aldehyde Dehydrogenase 3 Family Member A2 (ALDH3A2) gene causing SLS. Disruption of the function of ALDH3A2 leads to excessive accumulation of fat in the cells, which interferes with the normal function of protective membranes or materials that are necessary for the body to function normally. We retrieved 54 missense mutations in the ALDH3A2 from the OMIM, UniProt, dbSNP, and HGMD databases that are known to cause SLS. These mutations were examined with various in silico stability tools, which predicted that the mutations p.S308N and p.R423H that are located at the protein-protein interaction domains are the most destabilizing. Furthermore, to determine the atomistic-level differences within the protein-protein interactions owing to mutations, we performed macromolecular simulation (MMS) using GROMACS to validate the motion patterns and dynamic behavior of the biological system. We found that both mutations (p.S380N and p.R423H) had significant effects on the protein-protein interaction and disrupted the dimeric interactions. The computational pipeline provided in this study helps to elucidate the potential structural and functional differences between the ALDH3A2 native and mutant homodimeric proteins, and will pave the way for drug discovery against specific targets in the SLS patients.

Molecular Bases of Neurodegeneration and Cognitive Decline, the Major Burden of Sanfilippo Disease

The mucopolysaccharidoses (MPS) are a group of diseases caused by the lysosomal accumulation of glycosaminoglycans, due to genetic deficiencies of enzymes involved in their degradation. MPS III or Sanfilippo disease, in particular, is characterized by early-onset severe, progressive neurodegeneration but mild somatic involvement, with patients losing milestones and previously acquired skills as the disease progresses. Despite being the focus of extensive research over the past years, the links between accumulation of the primary molecule, the glycosaminoglycan heparan sulfate, and the neurodegeneration seen in patients have yet to be fully elucidated. This review summarizes the current knowledge on the molecular bases of neurological decline in Sanfilippo disease. It emerges that this deterioration results from the dysregulation of multiple cellular pathways, leading to neuroinflammation, oxidative stress, impaired autophagy and defects in cellular signaling. However, many important questions about the neuropathological mechanisms of the disease remain unanswered, highlighting the need for further research in this area.