Computing the Pathogenicity of Alzheimer’s Disease Presenilin 1 Mutations

Computational saturation mutagenesis to explore the effect of pathogenic mutations on extra-cellular domains of TREM2 associated with Alzheimer's and Nasu-Hakola disease

CONTEXT

The specialised family of triggering receptors expressed on myeloid cells (TREMs) plays a pivotal role in causing neurodegenerative disorders and activating microglial anti-inflammatory responses. Nasu-Hakola disease (NHD), a rare autosomal recessive disorder, has been associated with mutations in TREM2, which is also responsible for raising the risk of Alzheimer's disease (AD). Herein, we have made an endeavour to differentiate the confirmed pathogenic variants in TREM2 extra-cellular domain (ECD) linked with NHD and AD using mutation-induced fold stability change (∆∆G), with the computation of 12distinct structure-based methods through saturation mutagenesis. Correlation analysis between relative solvent accessibility (RSA) and ∆∆G expresses the discrete distributive behaviour of mutants associated with TREM2 in AD (R2 = 0.061) and NHD (R2 = 0.601). Our findings put an emphasis on W50 and V126 as major players in maintaining V-like domain in TREM2. Interestingly, we discern that both of them interact with a common residue Y108, which is dissolved upon mutation. This Y108 could have structural or functional role for TREM2 which can be an ideal candidate for further study. Furthermore, the residual interaction network highlights the importance of R47 and R62 in maintaining the CDR loops that are crucial for ligand binding. Future studies using biophysical characterisation of ligand interactions in TREM2-ECD would be helpful for the development of novel therapeutics for AD and NHD.

METHODS

ConSurf algorithm and ENDscript were used to determine the position and conservation of each residue in the wild-type ECD of TREM2. The mutation-induced fold stability change (∆∆G) of confirmed pathogenic mutants associated with NHD and AD was estimated using 12 state-of-the-art structure-based protein stability tools. Furthermore, we also computed the effect of random mutation on these sites using computational saturation mutagenesis. Linear regression analysis was performed using mutants ∆∆G and RSA through GraphPad software. In addition, a comprehensive non-bonded residual interaction network (RIN) of wild type and its mutants of TREM2-ECD was enumerated using RING3.0.

The amyloid cascade hypothesis: an updated critical review

Results from recent clinical trials of antibodies that target amyloid-β (Aβ) for Alzheimer's disease have created excitement and have been heralded as corroboration of the amyloid cascade hypothesis. However, while Aβ may contribute to disease, genetic, clinical, imaging and biochemical data suggest a more complex aetiology. Here we review the history and weaknesses of the amyloid cascade hypothesis in view of the new evidence obtained from clinical trials of anti-amyloid antibodies. These trials indicate that the treatments have either no or uncertain clinical effect on cognition. Despite the importance of amyloid in the definition of Alzheimer's disease, we argue that the data point to Aβ playing a minor aetiological role. We also discuss data suggesting that the concerted activity of many pathogenic factors contribute to Alzheimer's disease and propose that evolving multi-factor disease models will better underpin the search for more effective strategies to treat the disease.

Active site geometry stabilization of a presenilin homolog by the lipid bilayer promotes intramembrane proteolysis

Cleavage of membrane proteins in the lipid bilayer by intramembrane proteases is crucial for health and disease. Although different lipid environments can potently modulate their activity, how this is linked to their structural dynamics is unclear. Here, we show that the carboxy-peptidase-like activity of the archaeal intramembrane protease PSH, a homolog of the Alzheimer’s disease-associated presenilin/γ-secretase is impaired in micelles and promoted in a lipid bilayer. Comparative molecular dynamics simulations revealed that important elements for substrate binding such as transmembrane domain 6a of PSH are more labile in micelles and stabilized in the lipid bilayer. Moreover, consistent with an enhanced interaction of PSH with a transition-state analog inhibitor, the bilayer promoted the formation of the enzyme’s catalytic active site geometry. Our data indicate that the lipid environment of an intramembrane protease plays a critical role in structural stabilization and active site arrangement of the enzyme-substrate complex thereby promoting intramembrane proteolysis.

Cutting proteins into pieces is a crucial process in the cell, allowing several important processes to take place, including cell differentiation (which allows cells to develop into specific types), cell death, protein quality control, or even where in the cell a protein will end up. However, the specialized proteins that carry out this task, known as proteases, can also be involved in the development of disease. For example, in the brain, a protease called γ-secretase cuts up the amyloid-β protein precursor, producing toxic forms of amyloid-β peptides that are widely believed to cause Alzheimer’s disease.

Proteases like γ-secretase carry out their role in the membrane, the layer of fats (also known as lipids) that forms the outer boundary of the cell. The environment in this area of the cell can influence the activity of proteases, but it is poorly understood how this happens.

One way to address this question would be to compare the activity of γ-secretase in the lipid environment of the membrane to its activity when it is entirely surrounded by different molecules, such as detergent molecules. Unfortunately, γ-secretase is not active when it is removed from its lipid environment by a detergent, making it difficult to perform this comparison. To overcome this issue, Feilen et al. chose to study PSH, a protease similar to γ-secretase that produces the same amyloid-β peptides but remains active in detergent.

When Feilen et al. mixed PSH with lipid molecules like those found in the membrane and amyloid-β precursor protein, PSH produced amyloid-β peptides including those that are thought to cause Alzheimer’s. However, when a detergent was substituted for the lipid molecules this led to longer amyloid-β peptides than usual, indicating that PSH was not able to cut proteins as effectively. The change in environment appeared to reduce PSH’s ability to progressively trim small segments from the peptides.

Computer modelling of the protease’s structure in lipids versus detergent supported the experimental findings: the model predicted that the areas of PSH important for recognizing and cutting other proteins would be more stable in the membrane compared to the detergent.

These results indicate that the cell membrane plays a vital role in the stability of the active regions of proteases that are cleaving in this environment. In the future, this could help to better understand how changes to the lipid molecules in the membrane may contribute to the activity of γ-secretase and its role in Alzheimer’s disease.

Data set and fitting dependencies when estimating protein mutant stability: Toward simple, balanced, and interpretable models

Accurate prediction of protein stability changes upon mutation (ΔΔG) is increasingly important to evolution studies, protein engineering, and screening of disease-causing gene variants but is challenged by biases in training data. We investigated 45 linear regression models trained on data sets that account systematically for destabilization bias and mutation-type bias B_M . The models were externally validated on three test data sets probing different pathologies and for internal consistency (symmetry and neutrality). Model structure and performance substantially depended on training data and even fitting method. We developed two final models: SimBa-IB for typical natural mutations and SimBa-SYM for situations where stabilizing and destabilizing mutations occur to a similar extent. SimBa-SYM, despite is simplicity, is essentially non-biased (vs. the S^sym data set) while still performing well for all data sets (R ~ 0.46-0.54, MAE = 1.16-1.24 kcal/mol). The simple models provide advantage in terms of interpretability, use and future improvement, and are freely available on GitHub.

An insight into Alzheimer’s disease and its on-setting novel genes

According to the World Health Organisation, as of 2019, globally around 50 million people suffer from dementia, with approximately another 10 million getting added to the list every year, wherein Alzheimer’s disease (AD) stands responsible for almost a whopping 60–70% for the existing number of cases. Alzheimer’s disease is one of the progressive, cognitive-declining, age-dependent, neurodegenerative diseases which is distinguished by histopathological symptoms, such as formation of amyloid plaque, senile plaque, neurofibrillary tangles, etc. Majorly four vital transcripts are identified in the AD complications which include Amyloid precursor protein (APP), Apolipoprotein E (ApoE), and two multi-pass transmembrane domain proteins—Presenilin 1 and 2. In addition, the formation of the abnormal filaments such as amyloid beta (Aβ) and tau and their tangling with some necessary factors contributing to the formation of plaques, neuroinflammation, and apoptosis which in turn leads to the emergence of AD. Although multiple molecular mechanisms have been elucidated so far, they are still counted as hypotheses ending with neuronal death on the basal forebrain and hippocampal area which results in AD. This review article is aimed at addressing the overview of the molecular mechanisms surrounding AD and the functional forms of the genes associated with it.

Potential improvement of the thermal stability of sweet-tasting proteins by structural calculations

The low thermal stability of the sweet-tasting proteins limited their applications in food industry. Improve their thermal stability is the key to developing their applications in food processing. In the present study, saturation mutagenesis was performed on 4 sweet-tasting proteins, brazzein (988 mutations), curculin (2109 mutations), monellin (1824 mutations) and thaumatin (3933 mutations), using structural calculations in order to find more thermal stable mutations. The obtained results indicated that our calculated ΔΔG value (ΔΔG < 0 stabilizing, ΔΔG > 0 destabilizing) was a good predictor for predicting changes in thermal stability caused by mutations. Moreover, mutating the negatively charged residues to the other non-negatively charged amino acids was an efficient way to improve the thermal stability of the investigated sweet-tasting proteins. In addition, some promising mutations sites were identified for improving thermal stability using mutagenesis. This study provides useful information for future protein engineering to improve the thermal stability of the sweet-tasting proteins.

Side-by-side comparison of Notch- and C83 binding to γ-secretase in a complete membrane model at physiological temperature

γ-Secretase cleaves the C99 fragment of the amyloid precursor protein, leading to formation of aggregated β-amyloid peptide central to Alzheimer's disease, and Notch, essential for cell regulation. Recent cryogenic electron microscopy (cryo-EM) structures indicate major changes upon substrate binding, a β-sheet recognition motif, and a possible helix unwinding to expose peptide bonds towards nucleophilic attack. Here we report side-by-side comparison of the 303 K dynamics of the two proteins in realistic membranes using molecular dynamics simulations. Our ensembles agree with the cryo-EM data (full-protein Cα-RMSD = 1.62–2.19 Å) but reveal distinct presenilin helix conformation states and thermal β-strand to coil transitions of C83 and Notch100. We identify distinct 303 K hydrogen bond dynamics and water accessibility of the catalytic sites. The RKRR motif (1758–1761) contributes significantly to Notch binding and serves as a “membrane anchor” that prevents Notch displacement. Water that transiently hydrogen bonds to G1753 and V1754 probably represents the catalytic nucleophile. At 303 K, Notch and C83 binding induce different conformation states, with Notch mostly present in a closed state with shorter Asp–Asp distance. This may explain the different outcome of Notch and C99 cleavage, as the latter is more imprecise with many products. Our identified conformation states may aid efforts to develop conformation-selective drugs that target C99 and Notch cleavage differently, e.g. Notch-sparing γ-secretase modulators.

Distinct membrane dynamics and conformations of C83- and Notch-bound γ-secretase may aid the development of Notch-sparing treatments of Alzheimer's disease.

Survival of the cheapest: how proteome cost minimization drives evolution

Darwin's theory of evolution emphasized that positive selection of functional proficiency provides the fitness that ultimately determines the structure of life, a view that has dominated biochemical thinking of enzymes as perfectly optimized for their specific functions. The 20th-century modern synthesis, structural biology, and the central dogma explained the machinery of evolution, and nearly neutral theory explained how selection competes with random fixation dynamics that produce molecular clocks essential e.g. for dating evolutionary histories. However, quantitative proteomics revealed that selection pressures not relating to optimal function play much larger roles than previously thought, acting perhaps most importantly via protein expression levels. This paper first summarizes recent progress in the 21st century toward recovering this universal selection pressure. Then, the paper argues that proteome cost minimization is the dominant, underlying 'non-function' selection pressure controlling most of the evolution of already functionally adapted living systems. A theory of proteome cost minimization is described and argued to have consequences for understanding evolutionary trade-offs, aging, cancer, and neurodegenerative protein-misfolding diseases.

Revisiting the Impact of Neurodegenerative Proteins in Epilepsy: Focus on Alpha-Synuclein, Beta-Amyloid, and Tau

Lack of disease-modifying therapy against epileptogenesis reflects the complexity of the disease pathogenesis as well as the high demand to explore novel treatment strategies. In the pursuit of developing new therapeutic strategies against epileptogenesis, neurodegenerative proteins have recently gained increased attention. Owing to the fact that neurodegenerative disease and epileptogenesis possibly share a common underlying mechanism, targeting neurodegenerative proteins against epileptogenesis might represent a promising therapeutic approach. Herein, we review the association of neurodegenerative proteins, such as α-synuclein, amyloid-beta (Aβ), and tau protein, with epilepsy. Providing insight into the α-synuclein, Aβ and tau protein-mediated neurodegeneration mechanisms, and their implication in epileptogenesis will pave the way towards the development of new agents and treatment strategies.

Computing the Pathogenicity of Wilson's Disease ATP7B Mutations: Implications for Disease Prevalence

Genetic variations in the gene encoding the copper-transport protein ATP7B are the primary cause of Wilson's disease. Controversially, clinical prevalence seems much smaller than the prevalence estimated by genetic screening tools, causing fear that many people are undiagnosed, although early diagnosis and treatment is essential. To address this issue, we benchmarked 16 state-of-the-art computational disease-prediction methods against established data of missense ATP7B mutations. Our results show that the quality of the methods varies widely. We show the importance of optimizing the threshold of the methods used to distinguish pathogenic from nonpathogenic mutations against data of clinically confirmed pathogenic and nonpathogenic mutations. We find that most methods use thresholds that predict too many ATP7B mutations to be pathogenic. Thus, our findings explain the current controversy on Wilson's disease prevalence because meta-analysis and text search methods include many computational estimates that lead to higher disease prevalence than clinically observed. As proteins and diseases differ widely, a one-size-fits-all threshold cannot distinguish pathogenic and nonpathogenic mutations efficiently, as shown here. We also show that amino acid changes with small evolutionary substitution probability, mainly due to amino acid volume, are more associated with the disease, implying a pathological effect on the conformational state of the protein, which could affect copper transport or adenosine triphosphate recognition and hydrolysis. These findings may be a first step toward a more quantitative genotype-phenotype relationship of Wilson's disease.