: Amyloid fibrils are highly stable protein fibrillar aggregates believed to be involved in various neurodegenerative diseases, which include Alzheimer’s disease, Parkinson’s disease, and prion diseases. Inhibiting the aggregation process is a potential strategy to prevent diseases caused by amyloid formation. In this regard, nanoparticles have emerged as promising candidates owing to their unique physical/chemical properties of small size, large surface area, biocompatibility, biodegradability, non-toxicity, and ease of functionalization. Human Serum Albumin (HSA) is a soluble multidomain monomeric protein that interacts with various ligands and hormones, aiding in their transport, distribution, metabolism in the circulatory system, and also plays a vital role in extracellular fluid volume stabilization. Under certain in vitro conditions, HSA has been reported to undergo conformational changes leading to fibril formation and hence acts as a suitable model for studying amyloidogenesis. In this review, we have explored the effects of various nanoparticles on HSA aggregation and their mechanism of action. The study will throw light on the mechanistic details of nanoparticle-mediated amyloid modulation, which will help in the development of effective therapeutics against amyloidosis.
Aims: Alzheimer's disease is a neurodegenerative disease for which no cure is available. The presence of amyloid plaques in the extracellular space of neural cells is the key feature of this fatal disease. Background: The proteolysis of Amyloid Precursor Protein by presenilin leads to the formation of Amyloid-beta peptides (Aβ 42/40). Deposition of 42 residual Aβ peptides forms fibril’s structure, disrupting neuron synaptic transmission, inducing neural cell toxicity, and ultimately leading to neuron death. Objective: Various novel peptides have been investigated via molecular docking and molecular dynamic simulation studies to investigate their effects on Aβ amyloidogenesis. Method: The sequence-based peptides were rationally designed and investigated for their interaction with Aβ42 monomer and fibril, and their influence on the structural stability of target proteins was studied. Result: Analyzed docking results suggest that the peptide YRIGY (P6) has the highest binding affinity with Aβ42 fibril amongst all the synthetic peptides, and the peptide DKAPFF (P12) similarly shows a better binding with the Aβ42 monomer. Moreover, simulation results also suggest that the higher the binding affinity, the better the inhibitory action. Conclusion: These findings indicate that both the rationally designed peptides can modulate amyloidogenesis, but peptide (P6) has better potential for the disaggregation of the fibrils. In contrast, peptide P12 stabilizes the native structure of the Aβ42 monomer more effectively and hence can serve as a potential amyloid inhibitor. Thus, these peptides can be explored as therapeutic agents against Alzheimer's disease. Experimental testing of these peptides for immunogenicity, stability in cellular conditions, toxic effects and membrane permeability can be the future research scope of this study.
Diffuse large B-cell lymphoma (DLBCL) is an aggressive form of non-Hodgkin lymphoma with poor response to R-CHOP therapy due to remarkable heterogeneity. Based on gene expression, DLBCL cases were divided into two subtypes, i.e. ABC and GCB, where ABC subtype is associated with poor outcomes. Due to its association with clinical outcome, this classification, also known as cell-of-origin (COO), is an efficient way to predict the response to R-CHOP therapy. Previous COO classification methods have some shortcomings, e.g. limited number of samples in the training dataset. These shortcomings challenge the robustness of methods and make it difficult to implicate these methods at clinical level. To overcome the shortcomings of previous methods, we developed a deep learning-based classifier model on a cohort of 381 DLBCL patients using expression data of 20 genes. We implemented multilayer perceptron (MLP) to train deep learning-based classifier, named MLP-COO. MLP-COO achieved accuracy of 99.70% and 94.70% on training and testing datasets, respectively, with 10-fold cross-validation. We also assessed its performance on an independent dataset of 294 DLBCL patients. On independent dataset, we achieved an accuracy of 95.90% with MCC of 0.917. To show its broader applicability, we used this classifier to predict the clinical outcome using survival data from two large cohorts of DLBCL patients. In survival analysis, MLP-COO recapitulates the survival probabilities of DLBCL patients based on their COO in both cohorts. We anticipate that MLP-COO model developed in this study will benefit in the accurate COO prediction of DLBCL patients and their clinical outcomes.
Alzheimer’s Disease is a neurodegenerative disease for which no cure is available at present. The presence of amyloid plaques in the extracellular space of neural cells is the key feature of this fatal disease. Amyloid-Beta (Aβ) is a 40-42 amino acid peptide and the main component of amyloid plaques. This peptide is produced by the proteolysis of Amyloid Precursor Protein by presenilin. Deposition of 42 residual Aβ peptides forms fibrils structure, leading to disruption of neuron synaptic transmission, inducing neural cell toxicity, ultimately leading to neuron death. To modulate the amyloidosis of Aβ peptides, various novel peptides have been investigated via molecular docking and molecular dynamic simulation studies. The sequence-based peptides were designed and investigated for their interaction with Aβ42 monomer and fibril using the molecular docking method, and their influence on the structural stability of target proteins was studied using molecular simulations. According to the docking results, amongst all the synthetic peptides, the peptide YRIGY (P6) has the highest binding affinity with Aβ42 fibril, and the peptide DKAPFF (P12) shows better binding with Aβ42 monomer. Moreover, simulation results also suggest that the higher the binding affinity, the better the inhibitory action. From these findings, it is suggested that both the peptides can modulate the amyloidogenesis, but peptide (P6) has better potential for the disaggregation of the fibrils, whereas peptide P12 stabilizes the native structure of the Aβ42 monomer more effectively and hence can serve as a potential amyloid inhibitor. Thus, these peptides can be explored as therapeutic agents against Alzheimer’s Disease.
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