Peptide-Based Vaccines for Neurodegenerative Diseases: Recent Endeavors and Future Perspectives

Vassilakopoulou, Vyronia; Karachaliou, Chrysoula-Evangelia; Evangelou, Alexandra; Zikos, Christos; Livaniou, Evangelia

doi:10.3390/vaccines9111278

Cited by 16 publications

(15 citation statements)

References 138 publications

(606 reference statements)

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“…Hence, subunit/peptide-based vaccines are developed in which a small portion of pathogen protein is utilized in order to generate the vaccine candidates against [24,[51][52][53][54][55][56]. While designing a subunit-vaccines it is necessary to check the peptide/antigens have the capacity to effectively stimulate the immune system and generate specific type of cytokines to send signal to the immune system to perform inflammatory responses against the pathogens and cancerous In the current study, we have used experimentally validated IFN-γ inducing and non-inducing peptides from IEDB resource.…”

Section: Discussionmentioning

confidence: 99%

A hybrid method for discovering interferon-gamma inducing peptides in human and mouse

Dhall

Patiyal

Raghava

2023

Preprint

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A host-specific technique has been developed for annotating interferon-gamma (IFN-γ) inducing peptides, it is an updated version of IFNepitope. In this study, dataset used for developing prediction method contain experimentally validated 25492 and 7983 IFN-γ inducing peptides in human and mouse host, respectively. In initial phase, machine learning techniques have been exploited to develop classification model using wide range of peptide features. In most of the case, models based on extra tree perform better than other machine learning techniques. In case of peptide features, compositional feature particularly dipeptide composition performs better than one-hot encoding or binary profile. Our best machine learning based models achieved AUROC 0.89 and 0.83 for human and mouse host, respectively. In order to improve machine learning based models or alignment free models, we explore potential of similarity-based technique BLAST. Finally, a hybrid model has been developed that combine best machine learning based model with BLAST and achieved AUROC 0.90 and 0.85 for human and mouse host, respectively. All models have been evaluated on an independent/validation dataset not used for training or testing these models. Newly developed method performs better than existing method on independent dataset. The major objective of this study is to predict, design and scan IFN-γ inducing peptides, thus server/software have been developed (https://webs.iiitd.edu.in/raghava/ifnepitope2/).

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Section: Discussionmentioning

confidence: 99%

A hybrid method for discovering interferon-gamma inducing peptides in human and mouse

Dhall

Patiyal

Raghava

2023

Preprint

View full text Add to dashboard Cite

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“…Several second-generation Aβ-targeting vaccines have been subsequently designed to minimize Aβ-related T-cell inflammation including: ACC-001 using Aβ1–7 peptide conjugated to diphtheria toxoid protein [ 93 ], CAD106 using Aβ1–6 peptide coupled to Qb virus-like particle, V950 using multivalent Aβ1–15, and affitopes AD01 and AD02 using Aβ mimetics conjugated to KLH [ 94 , 95 ]. CAD106 (Generation Study 1, NCT02565511) to treat individuals with the ApoE4 allele and amyloid burden without cognitive impairment is ongoing [ 96 ].…”

Section: Amyloid-β Proteinmentioning

confidence: 99%

Symptomatic and Disease-Modifying Therapy Pipeline for Alzheimer’s Disease: Towards a Personalized Polypharmacology Patient-Centered Approach

Morató

Pytel

Jofresa

et al. 2022

IJMS

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Since 1906, when Dr. Alois Alzheimer first described in a patient “a peculiar severe disease process of the cerebral cortex”, people suffering from this pathology have been waiting for a breakthrough therapy. Alzheimer’s disease (AD) is an irreversible, progressive neurodegenerative brain disorder and the most common form of dementia in the elderly with a long presymptomatic phase. Worldwide, approximately 50 million people are living with dementia, with AD comprising 60–70% of cases. Pathologically, AD is characterized by the deposition of amyloid β-peptide (Aβ) in the neuropil (neuritic plaques) and blood vessels (amyloid angiopathy), and by the accumulation of hyperphosphorylated tau in neurons (neurofibrillary tangles) in the brain, with associated loss of synapses and neurons, together with glial activation, and neuroinflammation, resulting in cognitive deficits and eventually dementia. The current competitive landscape in AD consists of symptomatic treatments, of which there are currently six approved medications: three AChEIs (donepezil, rivastigmine, and galantamine), one NMDA-R antagonist (memantine), one combination therapy (memantine/donepezil), and GV-971 (sodium oligomannate, a mixture of oligosaccharides derived from algae) only approved in China. Improvements to the approved therapies, such as easier routes of administration and reduced dosing frequencies, along with the developments of new strategies and combined treatments are expected to occur within the next decade and will positively impact the way the disease is managed. Recently, Aducanumab, the first disease-modifying therapy (DMT) has been approved for AD, and several DMTs are in advanced stages of clinical development or regulatory review. Small molecules, mAbs, or multimodal strategies showing promise in animal studies have not confirmed that promise in the clinic (where small to moderate changes in clinical efficacy have been observed), and therefore, there is a significant unmet need for a better understanding of the AD pathogenesis and the exploration of alternative etiologies and therapeutic effective disease-modifying therapies strategies for AD. Therefore, a critical review of the disease-modifying therapy pipeline for Alzheimer’s disease is needed.

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“…These disordered proteins often display high conformational plasticity (chameleon proteins) and multifunctionality (moonlighting proteins) and are therefore challenging drug targets [37][38][39]. Although symptomatic treatments are available, there is still a pressing and unmet need for disease-modifying therapies in PD and AD [40][41][42]. Both innovative and well-established strategies for drugs targeting interactions/assemblies of proteins are described below with examples that focus mainly on PD.…”

Section: Disordered Proteins In Ppis As Attractive Drug Targetsmentioning

confidence: 99%

Challenges in Discovering Drugs That Target the Protein–Protein Interactions of Disordered Proteins

Oláh

Szénási

Lehotzky

et al. 2022

IJMS

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Protein–protein interactions (PPIs) outnumber proteins and are crucial to many fundamental processes; in consequence, PPIs are associated with several pathological conditions including neurodegeneration and modulating them by drugs constitutes a potentially major class of therapy. Classically, however, the discovery of small molecules for use as drugs entails targeting individual proteins rather than targeting PPIs. This is largely because discovering small molecules to modulate PPIs has been seen as extremely challenging. Here, we review the difficulties and limitations of strategies to discover drugs that target PPIs directly or indirectly, taking as examples the disordered proteins involved in neurodegenerative diseases.

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Peptide-Based Vaccines for Neurodegenerative Diseases: Recent Endeavors and Future Perspectives

Cited by 16 publications

References 138 publications

A hybrid method for discovering interferon-gamma inducing peptides in human and mouse

A hybrid method for discovering interferon-gamma inducing peptides in human and mouse

Symptomatic and Disease-Modifying Therapy Pipeline for Alzheimer’s Disease: Towards a Personalized Polypharmacology Patient-Centered Approach

Challenges in Discovering Drugs That Target the Protein–Protein Interactions of Disordered Proteins

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