Proteins

Casem, Merri Lynn

doi:10.1016/b978-0-12-801394-6.00003-8

Cited by 6 publications

(3 citation statements)

References 6 publications

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“…Specifically, 98.19% of MRSA was inhibited by the nanoreactors, while only 22.64% of B. subtilis was inhibited at the same concentration, rising to 96.71% when alpha toxin was added to the nanoreactor in the presence of B. subtilis . Cytotoxicity was probed with an MTT assay, with >90% cell viability of Vero cells (monkey kidney epithelial cells) 448 observed after 24 hours of nanoreactor treatment up to 500 μg mL −1 . Histological analysis verified these results, revealing no significant difference in tissue damage, inflammation or lesions between control mice and nanoreactor treated mice.…”

Section: Nanoscale Triggered Release Of Antimicrobial Agentsmentioning

confidence: 99%

Advancements in antimicrobial nanoscale materials and self-assembling systems

et al. 2022

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Section: Nanoscale Triggered Release Of Antimicrobial Agentsmentioning

confidence: 99%

Advancements in antimicrobial nanoscale materials and self-assembling systems

et al. 2022

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“…Proteins are involved in a host of cellular functions like transport across membranes, catalyzing chemical reactions, organizing DNA, etc. 1 In order to be functional, proteins need to fold into their native structures. Disruption of protein folding due to cellular stress leads to the disruption of biological function.…”

Section: Introductionmentioning

confidence: 99%

Molecular Aspects of Insulin Aggregation and Various Therapeutic Interventions

Das

Shah

Saraogi

2022

ACS Bio Med Chem Au

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Protein aggregation leading to the formation of amyloid fibrils has various adverse effects on human health ranging from fatigue and numbness to organ failure and death in extreme cases. Insulin, a peptide hormone commonly used to treat diabetes, undergoes aggregation at the site of repeated injections in diabetic patients as well as during its industrial production and transport. The reduced bioavailability of insulin due to aggregation hinders the proper control of glucose levels in diabetic patients. Thus, it is necessary to develop rational approaches for inhibiting insulin aggregation, which in turn requires a detailed understanding of the mechanism of fibrillation. Given the relative simplicity of insulin and ease of access, insulin has also served as a model system for studying amyloids. Approaches to inhibit insulin aggregation have included the use of natural molecules, synthetic peptides or small molecules, and bacterial chaperone machinery. This review focuses on insulin aggregation with an emphasis on its mechanism, the structural features of insulin fibrils, and the reported inhibitors that act at different stages in the aggregation pathway. We discuss molecules that can serve as leads for improved inhibitors for use in commercial insulin formulations. We also discuss the aggregation propensity of fast- and slow-acting insulin biosimilars, commonly administered to diabetic patients. The development of better insulin aggregation inhibitors and insights into their mechanism of action will not only aid diabetic therapies, but also enhance our knowledge of protein amyloidosis.

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“…Proteins are ubiquitous in all aspects of cellular life where they fulfil crucial functions, while their malfunction could result in disease states [1, 2]. By 2017, 70% of small molecule drugs on the market targeted four types of proteins, namely protein kinases, ion channels, rhodopsin-like G protein-coupled receptors (GPCRs), and nuclear hormone receptors [3].…”

Section: Introductionmentioning

confidence: 99%

Prediction of allosteric sites and signalling: insights from benchmarking datasets

Strömich

2021

Preprint

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Allostery is a pervasive mechanism which regulates the activity of proteins in living systems through binding of a molecule at a distant site from the orthosteric site of the protein. The universality of allosteric regulation complemented by the benefits of highly specific, potentially non-toxic and protein activity modulating allosteric drugs makes uncovering allosteric sites on proteins invaluable for drug discovery. However, there are few computational methods to effectively predict them. Bond-to-bond propensity analysis, a recently developed method, has successfully predicted allosteric sites for a diverse group of proteins with only the knowledge of the orthosteric sites and the corresponding ligands in 19 of 20 cases. The method is based on an energy-weighted atomistic protein graph and allows for computationally highly efficient analysis in atomistic detail. We here extended the analysis onto 432 structures of 146 proteins from two existing benchmarking datasets for allosteric proteins: ASBench and CASBench. We further refined the metrics to account for the cumulative effect of residues with high propensities and the crucial residues in a given site with two additional measures. The allosteric site is recovered for 95/113 proteins (99/118 structures) from ASBench and 32/33 proteins (304/314 structures) from CASBench, with the only a priori knowledge being the orthosteric site residues. Knowing the orthosteric ligands of the protein, the allosteric site is identified for 32/33 proteins (308/314 structures) from CASBench.

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Proteins

Cited by 6 publications

References 6 publications

Advancements in antimicrobial nanoscale materials and self-assembling systems

Advancements in antimicrobial nanoscale materials and self-assembling systems

Molecular Aspects of Insulin Aggregation and Various Therapeutic Interventions

Prediction of allosteric sites and signalling: insights from benchmarking datasets

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