Reduction of Promiscuous Peptides-Enzyme Inhibition and Aggregation by Negatively Charged Biopolymers

Fu, Jinglin; Nguyen, Kaitlyn

doi:10.1021/acsabm.1c01128

Cited by 5 publications

(5 citation statements)

References 30 publications

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“…A Zetasizer Pro (Malvern Instruments) was used for DLS experiments as reported previously . All buffers used for the DLS experiment were filtered by a 0.2 μm filter.…”

Section: Methodsmentioning

confidence: 99%

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A Robust and Efficient Method to Purify DNA-Scaffolded Nanostructures by Gravity-Driven Size Exclusion Chromatography

Ebrahimimojarad,

Wang,

Zhang

et al. 2024

Langmuir

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In recent decades, nucleic acid self-assemblies have emerged as popular nanomaterials due to their programmable and robust assembly, prescribed geometry, and versatile functionality. However, it remains a challenge to purify large quantities of DNA nanostructures or DNA-templated nanocomplexes for various applications. Commonly used purification methods are either limited by a small scale or incompatible with functionalized structures. To address this unmet need, we present a robust and scalable method of purifying DNA nanostructures by Sepharose resin-based size exclusion. The resin column can be manually packed in-house with reusability. The separation is driven by a low-pressure gravity flow in which large DNA nanostructures are eluted first followed by smaller impurities of ssDNA and proteins. We demonstrated the efficiency of the method for purifying DNA origami assemblies and protein-immobilized DNA nanostructures. Compared to routine agarose gel electrophoresis that yields 1 μg or less of purified products, this method can purify ∼100−1000 μg of DNA nanostructures in less than 30 min, with the overall collection yield of 50−70% of crude preparation mixture. The purified nanocomplexes showed more precise activity in evaluating enzyme functions and antibody-triggered activation of complement protein reactions.

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“…A Zetasizer Pro (Malvern Instruments) was used for DLS experiments as reported previously . All buffers used for the DLS experiment were filtered by a 0.2 μm filter.…”

Section: Methodsmentioning

confidence: 99%

“…A Zetasizer Pro (Malvern Instruments) was used for DLS experiments as reported previously. 28 All buffers used for the DLS experiment were filtered by a 0.2 μm filter. A disposal cuvette was rinsed with distilled water three times prior to use.…”

Section: Atomic Force Microscope (Afm) Imaging and Dynamic Light Scat...mentioning

confidence: 99%

A Robust and Efficient Method to Purify DNA-Scaffolded Nanostructures by Gravity-Driven Size Exclusion Chromatography

Ebrahimimojarad,

Wang,

Zhang

et al. 2024

Langmuir

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“…Peptides consist of short chains of amino acids, with a molecular weight ranging from 0.5 to 10 kDa [ 15 ], and a length ranging from a couple of amino acids up to 100 [ 16 ]. Their role in biological processes is diverse, including functions as structural components, enzymatic inhibitors, hormones, host defence molecules and neurotransmitters [ 11 ].…”

Section: Peptides and Their Biotechnology Applicationsmentioning

confidence: 99%

Peptide-based drug discovery through artificial intelligence: towards an autonomous design of therapeutic peptides

Goles,

Daza,

Cabas-Mora

et al. 2024

Briefings in Bioinformatics

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With their diverse biological activities, peptides are promising candidates for therapeutic applications, showing antimicrobial, antitumour and hormonal signalling capabilities. Despite their advantages, therapeutic peptides face challenges such as short half-life, limited oral bioavailability and susceptibility to plasma degradation. The rise of computational tools and artificial intelligence (AI) in peptide research has spurred the development of advanced methodologies and databases that are pivotal in the exploration of these complex macromolecules. This perspective delves into integrating AI in peptide development, encompassing classifier methods, predictive systems and the avant-garde design facilitated by deep-generative models like generative adversarial networks and variational autoencoders. There are still challenges, such as the need for processing optimization and careful validation of predictive models. This work outlines traditional strategies for machine learning model construction and training techniques and proposes a comprehensive AI-assisted peptide design and validation pipeline. The evolving landscape of peptide design using AI is emphasized, showcasing the practicality of these methods in expediting the development and discovery of novel peptides within the context of peptide-based drug discovery.

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“…[1][2][3][4][5][6][7][8][9] Furthermore, a multitude of chemical agents have been identified as interacting, either reversibly or irreversibly, with essential enzymes, leading to their inactivation and thereby impeding their vital biological functionality. [10][11][12][13][14][15][16] Consequently, monitoring of enzyme inhibition arises as an equally essential challenge as tracking their activity. Nevertheless, the discernment of enzymatic activity and inhibition within blood plasma poses a far greater challenge compared to monitoring enzymes in a clean, simple, and homogenous environment, primarily due to two critical factors.…”

Section: Introductionmentioning

confidence: 99%

Rationally Designed Functionalization of Single‐Walled Carbon Nanotubes for Real‐Time Monitoring of Cholinesterase Activity and Inhibition in Plasma

Basu,

Hendler‐Neumark,

Bisker

2024

Small

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Enzymes play a pivotal role in regulating numerous bodily functions. Thus, there is a growing need for developing sensors enabling real‐time monitoring of enzymatic activity and inhibition. The activity and inhibition of cholinesterase (CHE) enzymes in blood plasma are fluorometrically monitored using near‐infrared (NIR) fluorescent single‐walled carbon nanotubes (SWCNTs) as probes, strategically functionalized with myristoylcholine (MC)– the substrate of CHE. A significant decrease in the fluorescence intensity of MC‐suspended SWCNTs upon interaction with CHE is observed, attributed to the hydrolysis of the MC corona phase of the SWCNTs by CHE. Complementary measurements for quantifying choline, the product of MC hydrolysis, reveal a correlation between the fluorescence intensity decrease and the amount of released choline, rendering the SWCNTs optical sensors with real‐time feedback in the NIR biologically transparent spectral range. Moreover, when synthetic and naturally abundant inhibitors inhibit the CHE enzymes present in blood plasma, no significant modulations of the MC‐SWCNT fluorescence are observed, allowing effective detection of CHE inhibition. The rationally designed SWCNT sensors platform for monitoring of enzymatic activity and inhibition in clinically relevant samples is envisioned to not only advance the field of clinical diagnostics but also deepen further understanding of enzyme‐related processes in complex biological fluids.

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Reduction of Promiscuous Peptides-Enzyme Inhibition and Aggregation by Negatively Charged Biopolymers

Cited by 5 publications

References 30 publications

A Robust and Efficient Method to Purify DNA-Scaffolded Nanostructures by Gravity-Driven Size Exclusion Chromatography

A Robust and Efficient Method to Purify DNA-Scaffolded Nanostructures by Gravity-Driven Size Exclusion Chromatography

Peptide-based drug discovery through artificial intelligence: towards an autonomous design of therapeutic peptides

Rationally Designed Functionalization of Single‐Walled Carbon Nanotubes for Real‐Time Monitoring of Cholinesterase Activity and Inhibition in Plasma

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