Novel small molecules inhibit proteotoxicity and inflammation: Mechanistic and therapeutic implications for Alzheimer’s Disease, healthspan and lifespan- Aging as a consequence of glycolysis

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Июнь 13, 2023

Abstract Inflammation drives many age-related, especially neurological, diseases, and likely mediates age-related proteotoxicity. For example, dementia due to Alzheimer’s Disease (AD), cerebral vascular disease, other neurodegenerative conditions is increasingly among the most devastating burdens on American (and world) health system threatens bankrupt as population ages unless effective treatments are developed. Dementia either AD or plausibly even psychiatric conditions, driven by increased inflammation, which in turn appears mediate Abeta related proteotoxic processes. The functional significance of inflammation during aging also supported fact that Humira, simply an antibody pro-inflammatory cytokine TNF-a, best-selling drug world revenue. These observations led us develop parallel high-throughput screens discover small molecules inhibit proteotoxicity a C. elegans model AND LPS-induced microglial TNF-a. In initial screen 2560 compounds (Microsource Spectrum library) delay proteotoxicity, protective were, order, phenylbutyrate, methicillin, quetiapine, belong classes (HDAC inhibitors, beta lactam antibiotics, tricyclic antipsychotics, respectably) already robustly implicated promising protect AD. RNAi chemical indicated effects HDAC inhibitors reduce mediated inhibition HDAC2, human AD, dependent HAT Creb binding protein (Cbp), required for both dietary restriction daf-2 mutation (inactivation IGF-1 signaling) aging. addition several antibiotics delayed reduced antipsychotic drugs leading synthesis novel congener, GM310, delays well Huntingtin inhibits mouse monocyte highly concentrated brain after oral delivery with no apparent toxicity, increases lifespan, produces molecular responses similar those produced restriction, including induction Cbp Cbp, genes promoting shift away from glycolysis toward metabolism alternate (e.g., lipid) substrates. FDA-approved congeners, prevented impairments associated increase TNF-a stroke. Robust reduction GM310 was functionally corroborated flux analysis, glycolytic inhibitor 2-DG inhibited markers lifespan. results support value phenotypic treat neurological stroke, clarify mechanisms driving neurodegeneration neuroinflammation subsequent neurotoxicity) suggesting (selective glycolysis).

Язык: Английский

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Peer Review #1 of "Network neighborhood operates as a drug repositioning method for cancer treatment (v0.1)"

Опубликована: Июль 10, 2023

Computational drug repositioning approaches are important, as they cost less compared to the traditional development processes.This study proposes a novel network-based approach, which computes similarities between disease-causing genes and drug-affected in network topology suggest candidate drugs with highest similarity scores.This new method aims identify better treatment options by integrating systems biology approaches.It uses protein-protein interaction that is main compute score genes.The were mapped on this structure.Transcriptome profiles of candidates taken from LINCS project individually structure.The these two networks was calculated different neighborhood metrics, including Adamic-Adar, PageRank scoring.The proposed approach identifies best choosing significant scores.The experimented melanoma, colorectal, prostate cancers.Several predicted applying AUC values 0.6 or higher.Some predictions approved clinical phase trials other in-vivo studies found literature.The would integration functional information transcriptome level effects perturbations diseases.

Язык: Английский

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Peer Review #4 of "Network neighborhood operates as a drug repositioning method for cancer treatment (v0.2)"

Опубликована: Июль 10, 2023

Computational drug repositioning approaches are important, as they cost less compared to the traditional development processes.This study proposes a novel network-based approach, which computes similarities between disease-causing genes and drug-affected in network topology suggest candidate drugs with highest similarity scores.This new method aims identify better treatment options by integrating systems biology approaches.It uses protein-protein interaction that is main compute score genes.The were mapped on this structure.Transcriptome profiles of candidates taken from LINCS project individually structure.The these two networks was calculated different neighborhood metrics, including Adamic-Adar, PageRank scoring.The proposed approach identifies best choosing significant scores.The experimented melanoma, colorectal, prostate cancers.Several predicted applying AUC values 0.6 or higher.Some predictions approved clinical phase trials other in-vivo studies found literature.The would integration functional information transcriptome level effects perturbations diseases.

Язык: Английский

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Peer Review #2 of "Network neighborhood operates as a drug repositioning method for cancer treatment (v0.2)"

Опубликована: Июль 10, 2023

Computational drug repositioning approaches are important, as they cost less compared to the traditional development processes.This study proposes a novel network-based approach, which computes similarities between disease-causing genes and drug-affected in network topology suggest candidate drugs with highest similarity scores.This new method aims identify better treatment options by integrating systems biology approaches.It uses protein-protein interaction that is main compute score genes.The were mapped on this structure.Transcriptome profiles of candidates taken from LINCS project individually structure.The these two networks was calculated different neighborhood metrics, including Adamic-Adar, PageRank scoring.The proposed approach identifies best choosing significant scores.The experimented melanoma, colorectal, prostate cancers.Several predicted applying AUC values 0.6 or higher.Some predictions approved clinical phase trials other in-vivo studies found literature.The would integration functional information transcriptome level effects perturbations diseases.

Язык: Английский

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Peer Review #3 of "Network neighborhood operates as a drug repositioning method for cancer treatment (v0.1)"

Опубликована: Июль 10, 2023

Computational drug repositioning approaches are important, as they cost less compared to the traditional development processes.This study proposes a novel network-based approach, which computes similarities between disease-causing genes and drug-affected in network topology suggest candidate drugs with highest similarity scores.This new method aims identify better treatment options by integrating systems biology approaches.It uses protein-protein interaction that is main compute score genes.The were mapped on this structure.Transcriptome profiles of candidates taken from LINCS project individually structure.The these two networks was calculated different neighborhood metrics, including Adamic-Adar, PageRank scoring.The proposed approach identifies best choosing significant scores.The experimented melanoma, colorectal, prostate cancers.Several predicted applying AUC values 0.6 or higher.Some predictions approved clinical phase trials other in-vivo studies found literature.The would integration functional information transcriptome level effects perturbations diseases.

Язык: Английский

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Peer Review #2 of "Network neighborhood operates as a drug repositioning method for cancer treatment (v0.1)"

Опубликована: Июль 10, 2023

Computational drug repositioning approaches are important, as they cost less compared to the traditional development processes.This study proposes a novel network-based approach, which computes similarities between disease-causing genes and drug-affected in network topology suggest candidate drugs with highest similarity scores.This new method aims identify better treatment options by integrating systems biology approaches.It uses protein-protein interaction that is main compute score genes.The were mapped on this structure.Transcriptome profiles of candidates taken from LINCS project individually structure.The these two networks was calculated different neighborhood metrics, including Adamic-Adar, PageRank scoring.The proposed approach identifies best choosing significant scores.The experimented melanoma, colorectal, prostate cancers.Several predicted applying AUC values 0.6 or higher.Some predictions approved clinical phase trials other in-vivo studies found literature.The would integration functional information transcriptome level effects perturbations diseases.

Язык: Английский

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Leveraging Genomic and Bioinformatic Analysis to Enhance Drug Repositioning for Dermatomyositis

Bioengineering, Год журнала: 2023, Номер 10(8), С. 890 - 890

Опубликована: Июль 27, 2023

Dermatomyositis (DM) is an autoimmune disease that classified as a type of idiopathic inflammatory myopathy, which affects human skin and muscles. The most common clinical symptoms DM are muscle weakness, rash, scaly skin. There currently no cure for DM. Genetic factors known to play pivotal role in progression, but few have utilized this information geared toward drug discovery the disease. Here, we exploited genomic variation associated with integrated bioinformatic analyses discover new candidates. We first genome-wide association study (GWAS) phenome-wide (PheWAS) catalogs identify disease-associated variants. Biological risk genes were prioritized using strict functional annotations, further identifying candidate targets based on druggable from databases. Overall, analyzed 1239 variants obtained 43 drugs overlapped 13 target (JAK2, FCGR3B, CD4, CD3D, LCK, CD2, CD3E, FCGR3A, CD3G, IFNAR1, CD247, JAK1, IFNAR2). Six clinically investigated DM, well eight under pre-clinical investigation, could be repositioned Further studies necessary validate potential biomarkers novel therapeutics our findings.

Язык: Английский

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