Computational Investigation of Gantenerumab and Crenezumab Recognition of Aβ Fibrils in Alzheimer's Disease Brain Tissue

Monoclonal antibodies and aptamers: The future therapeutics for Alzheimer's disease

Alzheimer's disease (AD) is considered the most common and prevalent form of dementia of adult-onset with characteristic progressive impairment in cognition and memory. The cure for AD has not been found yet and the treatments available until recently were only symptomatic. Regardless of multidisciplinary approaches and efforts made by pharmaceutical companies, it was only in the past two years that new drugs were approved for the treatment of the disease. Amyloid beta (Aβ) immunotherapy is at the core of this therapy, which is one of the most innovative approaches looking to change the course of AD. This technology is based on synthetic peptides or monoclonal antibodies (mAb) to reduce Aβ levels in the brain and slow down the advance of neurodegeneration. Hence, this article reviews the state of the art about AD neuropathogenesis, the traditional pharmacologic treatment, as well as the modern active and passive immunization describing approved drugs, and drug prototypes currently under investigation in different clinical trials. In addition, future perspectives on immunotherapeutic strategies for AD and the rise of the aptamer technology as a non-immunogenic alternative to curb the disease progression are discussed.

Immunotherapy in Alzheimer's disease: focusing on the efficacy of gantenerumab on amyloid-β clearance and cognitive decline

Gantenerumab, a human monoclonal antibody (mAb), has been thought of as a potential agent to treat Alzheimer's disease (AD) by specifically targeting regions of the amyloid-β (Aβ) peptide sequence. Aβ protein accumulation in the brain leads to amyloid plaques, causing neuroinflammation, oxidative stress, neuronal damage, and neurotransmitter dysfunction, thereby causing cognitive decline in AD. Gantenerumab involves disrupting Aβ aggregation and promoting the breakdown of larger Aβ aggregates into smaller fragments, which facilitates the action of Aβ-degrading enzymes in the brain, thus slowing down the progression of AD. Moreover, Gantenerumab acts as an opsonin, coating Aβ plaques and enhancing their recognition by immune cells, which, combined with its ability to improve the activity of microglia, makes it an intriguing candidate for promoting Aβ plaque clearance. Indeed, the multifaceted effects of Gantenerumab, including Aβ disaggregation, enhanced immune recognition, and improved microglia activity, may position it as a promising therapeutic approach for AD. Of note, reports suggest that Gantenerumab, albeit its capacity to reduce or eliminate Aβ, has not demonstrated effectiveness in reducing cognitive decline. This review, after providing an overview of immunotherapy approaches that target Aβ in AD, explores the efficacy of Gantenerumab in reducing Aβ levels and cognitive decline.

Two Phase 3 Trials of Gantenerumab in Early Alzheimer's Disease

BACKGROUND

Monoclonal antibodies that target amyloid-beta (Aβ) have the potential to slow cognitive and functional decline in persons with early Alzheimer's disease. Gantenerumab is a subcutaneously administered, fully human, anti-Aβ IgG1 monoclonal antibody with highest affinity for aggregated Aβ that has been tested for the treatment of Alzheimer's disease.

METHODS

We conducted two phase 3 trials (GRADUATE I and II) involving participants 50 to 90 years of age with mild cognitive impairment or mild dementia due to Alzheimer's disease and evidence of amyloid plaques on positron-emission tomography (PET) or cerebrospinal fluid (CSF) testing. Participants were randomly assigned to receive gantenerumab or placebo every 2 weeks. The primary outcome was the change from baseline in the score on the Clinical Dementia Rating scale-Sum of Boxes (CDR-SB; range, 0 to 18, with higher scores indicating greater cognitive impairment) at week 116.

RESULTS

A total of 985 and 980 participants were enrolled in the GRADUATE I and II trials, respectively. The baseline CDR-SB score was 3.7 in the GRADUATE I trial and 3.6 in the GRADUATE II trial. The change from baseline in the CDR-SB score at week 116 was 3.35 with gantenerumab and 3.65 with placebo in the GRADUATE I trial (difference, -0.31; 95% confidence interval [CI], -0.66 to 0.05; P = 0.10) and was 2.82 with gantenerumab and 3.01 with placebo in the GRADUATE II trial (difference, -0.19; 95% CI, -0.55 to 0.17; P = 0.30). At week 116, the difference in the amyloid level on PET between the gantenerumab group and the placebo group was -66.44 and -56.46 centiloids in the GRADUATE I and II trials, respectively, and amyloid-negative status was attained in 28.0% and 26.8% of the participants receiving gantenerumab in the two trials. Across both trials, participants receiving gantenerumab had lower CSF levels of phosphorylated tau 181 and higher levels of Aβ42 than those receiving placebo; the accumulation of aggregated tau on PET was similar in the two groups. Amyloid-related imaging abnormalities with edema (ARIA-E) occurred in 24.9% of the participants receiving gantenerumab, and symptomatic ARIA-E occurred in 5.0%.

CONCLUSIONS

Among persons with early Alzheimer's disease, the use of gantenerumab led to a lower amyloid plaque burden than placebo at 116 weeks but was not associated with slower clinical decline. (Funded by F. Hoffmann-La Roche; GRADUATE I and II ClinicalTrials.gov numbers, NCT03444870 and NCT03443973, respectively.).

Evaluation of Molecular Simulations and Deep Learning Prediction of Antibodies' Recognition of TRBC1 and TRBC2

T cell receptor β-chain constant (TRBC) is a promising class of cancer targets consisting of two highly homologous proteins, TRBC1 and TRBC2. Developing targeted antibody therapeutics against TRBC1 or TRBC2 is expected to eradicate the malignant T cells and preserve half of the normal T cells. Recently, several antibody engineering strategies have been used to modulate the TRBC1 and TRBC2 specificity of antibodies. Here, we used molecular simulation and artificial intelligence methods to quantify the affinity difference in antibodies with various mutations for TRBC1 and TRBC2. The affinity of the existing mutants was verified by FEP calculations aided by the AI. We also performed long-time molecular dynamics simulations to reveal the dynamical antigen recognition mechanisms of the TRBC antibodies.

Molecular Insights into the Self-Assembly of a Full-Length hIAPP Trimer: β-Protofibril Formed by β-Hairpin Lateral or Longitudinal Association

The fibrillar protein deposits of the human islet amyloid polypeptide (hIAPP) in the pancreatic islet of Langerhans are pathological hallmark of type II diabetes. Extensive experimental studies have revealed that the oligomeric formations of the hIAPP are more toxic than the mature fibrils. Exploring the oligomeric conformations in the early aggregation state is valuable for effective therapeutics. In this work, using the all-atom explicit-solvent replica exchange molecular dynamic (REMD) simulations, we investigated the structural features and the assembly mechanisms of the full-length hIAPP trimer in solution. The hIAPP trimer adopted more β-sheets than a-helix conformations, and three types of ordered conformations including open β-barrel, single-layer, and double-layer U-shaped β-sheet structures with five β-strands were captured in our simulations. A representative single-layer β-sheet conformation with a CCS value of 1400 Ų in our simulations matches exactly the experimentally ESI-IMS-MS-derived hIAPP trimer sample. These five β-strand conformations formed via the β-hairpin lateral and longitudinal association, respectively, showing two β-protofibril formation models. To the best of our knowledge, it is the first time to reveal two routes to β-sheet formation in the hIAPP trimers on the atomic level. The contact probabilities between pairs of the β-stranded residue show that the hydrophobic interactions between the residues F₁₅ ∼ V₁₇ and A₂₅ ∼ L₂₇ are responsible for the inter- and intra-peptide β-hairpin formations. All of these results indicate that the β-sheet formation is the first step in the conformational changes toward pathological aggregation and provides evidence of the β-sheet assembly mechanism into hIAPP aggregation.

Fewer Dimensions, More Structures for Improved Discrete Models of Dynamics of Free versus Antigen-Bound Antibody

Over the past decade, Markov State Models (MSM) have emerged as powerful methodologies to build discrete models of dynamics over structures obtained from Molecular Dynamics trajectories. The identification of macrostates for the MSM is a central decision that impacts the quality of the MSM but depends on both the selected representation of a structure and the clustering algorithm utilized over the featurized structures. Motivated by a large molecular system in its free and bound state, this paper investigates two directions of research, further reducing the representation dimensionality in a non-parametric, data-driven manner and including more structures in the computation. Rigorous evaluation of the quality of obtained MSMs via various statistical tests in a comparative setting firmly shows that fewer dimensions and more structures result in a better MSM. Many interesting findings emerge from the best MSM, advancing our understanding of the relationship between antibody dynamics and antibody–antigen recognition.

Molecular mechanisms of amyloid disaggregation

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Importance of disaggregation mechanism and innate disaggregation in living systems.

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Different types and mechanism of disaggregation reported in literature.

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Structural details of the interactions and the disaggregation mechanisms.

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Amyloid disaggregation in protein aggregation disorders as a potential treatment.

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Proposed amyloid disaggregation mechanism of an ATP-independent chaperone (L-PGDS).

Introduction

Protein aggregation and deposition of uniformly arranged amyloid fibrils in the form of plaques or amorphous aggregates is characteristic of amyloid diseases. The accumulation and deposition of proteins result in toxicity and cause deleterious effects on affected individuals known as amyloidosis. There are about fifty different proteins and peptides involved in amyloidosis including neurodegenerative diseases and diseases affecting vital organs. Despite the strenuous effort to find a suitable treatment option for these amyloid disorders, very few compounds had made it to unsuccessful clinical trials. It has become a compelling challenge to understand and manage amyloidosis with the increased life expectancy and ageing population.

Objective

While most of the currently available literature and knowledge base focus on the amyloid inhibitory mechanism as a treatment option, it is equally important to organize and understand amyloid disaggregation strategies. Disaggregation strategies are important and crucial as they are present innately functional in many living systems and dissolution of preformed amyloids may provide a direct benefit in many pathological conditions. In this review, we have compiled the known amyloid disaggregation mechanism, interactions, and possibilities of using disaggregases as a treatment option for amyloidosis.

Methods

We have provided the structural details using protein-ligand docking models to visualize the interaction between these disaggregases with amyloid fibrils and their respective proposed amyloid disaggregation mechanisms.

Results

After reviewing and comparing the different amyloid disaggregase systems and their proposed mechanisms, we presented two different hypotheses for ATP independent disaggregases using L-PGDS as a model.

Conclusion

Finally, we have highlighted the importance of understanding the underlying disaggregation mechanisms used by these chaperones and organic compounds before the implementation of these disaggregases as a potential treatment option for amyloidosis.

Marine derivatives prevent wMUS81 in silico studies

The winged-helix domain of the methyl methanesulfonate and ultraviolet-sensitive 81 (wMUS81) is a potential cancer drug target. In this context, marine fungi compounds were indicated to be able to prevent wMUS81 structure via atomistic simulations. Eight compounds such as D197 (Tryptoquivaline U), D220 (Epiremisporine B), D67 (Aspergiolide A), D153 (Preussomerin G), D547 (12,13-dihydroxyfumitremorgin C), D152 (Preussomerin K), D20 (Marinopyrrole B) and D559 (Fumuquinazoline K) were indicated that they are able to prevent the conformation of wMUS81 via forming a strong binding affinity to the enzyme via perturbation approach. The electrostatic interaction is the dominant factor in the binding process of ligands to wMUS81. The residues Trp55, Arg59, Leu62, His63 and Arg69 were found to frequently form non-bonded contacts and hydrogen bonds to inhibitors. Moreover, the influence of the ligand D197, which formed the lowest binding free energy to wMUS81, on the structural change of enzyme was investigated using replica exchange molecular dynamics simulations. The obtained results indicated that D197, which forms a strong binding affinity, can modify the structure of wMUS81. Overall, the marine compounds probably inhibit wMUS81 due to forming a strong binding affinity to the enzyme as well as altering the enzymic conformation.

Accurate Structure Prediction for Protein Loops Based on Molecular Dynamics Simulations with RSFF2C

Protein loops, connecting the α-helices and β-strands, are involved in many important biological processes. However, due to their conformational flexibility, it is still challenging to accurately determine three-dimensional (3D) structures of long loops experimentally and computationally. Herein, we present a systematic study of the protein loop structure prediction via a total of ∼850 μs molecular dynamics (MD) simulations. For a set of 15 long (10-16 residues) and solvent-exposed loops, we first evaluated the performance of four state-of-the-art loop modeling algorithms, DaReUS-Loop, Sphinx, Rosetta-NGK, and MODELLER, on each loop, and none of them could accurately predict the structures for most loops. Then, temperature replica exchange molecular dynamics (REMD) simulations were conducted with three recent force fields, RSFF2C with TIP3P water model, CHARMM36m with CHARMM-modified TIP3P, and AMBER ff19SB with OPC. We found that our recently developed residue-specific force field RSFF2C performed the best and successfully predicted 12 out of 15 loops with a root-mean-square deviation (RMSD) < 1.5 Å. As an alternative with lower computational cost, normal MD simulations at high temperatures (380, 500, and 620 K) were investigated. Temperature-dependent performance was observed for each force field, and, for RSFF2C+TIP3P, we found that three independent 100-ns MD simulations at 500 K gave comparable results with REMD simulations. These results suggest that MD simulations, especially with enhanced sampling techniques such as replica exchange, with the RSFF2C force field could be useful for accurate loop structure prediction.

Directed evolution of conformation-specific antibodies for sensitive detection of polypeptide aggregates in therapeutic drug formulations

Biologics such as peptides and proteins possess a number of attractive attributes that make them particularly valuable as therapeutics, including their high activity, high specificity, and low toxicity. However, one of the key challenges associated with this class of drugs is their propensity to aggregate. Given the safety and immunogenicity concerns related to polypeptide aggregates, it is particularly important to sensitively detect aggregates in therapeutic drug formulations as part of the quality control process. Here, we report the development of conformation-specific antibodies that recognize polypeptide aggregates composed of a GLP-1 receptor agonist (liraglutide) and their integration into a sensitive immunoassay for detecting liraglutide amyloid fibrils. We sorted single-chain antibody libraries against liraglutide fibrils using yeast surface display and magnetic-activated cell sorting, and identified several antibodies with high conformational specificity. Interestingly, these antibodies cross-react with amyloid fibrils formed by several other polypeptides, revealing that they recognize molecular features common to different types of fibrils. Moreover, we find that our immunoassay using these antibodies is >50-fold more sensitive than the conventional method for detecting liraglutide aggregation (Thioflavin T fluorescence). We expect that our systematic approach for generating a sensitive, aggregate-specific immunoassay can be readily extended to other biologics to improve the quality and safety of formulated drug products.