Matching Items (18)

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A Simple Platform for the Rapid Development of Antimicrobials

Description

Recent infectious outbreaks highlight the need for platform technologies that can be quickly deployed to develop therapeutics needed to contain the outbreak. We present a simple concept for rapid development

Recent infectious outbreaks highlight the need for platform technologies that can be quickly deployed to develop therapeutics needed to contain the outbreak. We present a simple concept for rapid development of new antimicrobials. The goal was to produce in as little as one week thousands of doses of an intervention for a new pathogen. We tested the feasibility of a system based on antimicrobial synbodies. The system involves creating an array of 100 peptides that have been selected for broad capability to bind and/or kill viruses and bacteria. The peptides are pre-screened for low cell toxicity prior to large scale synthesis. Any pathogen is then assayed on the chip to find peptides that bind or kill it. Peptides are combined in pairs as synbodies and further screened for activity and toxicity. The lead synbody can be quickly produced in large scale, with completion of the entire process in one week.

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Created

Date Created
  • 2017-12-14

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Peptide array based discovery of synthetic antimicrobial peptides

Description

The rise of antibiotic resistance has emphasized the shortcomings in antibiotic drug development (Boucher et al., 2013). The move from biological based discovery methods to chemical approaches to identify candidates

The rise of antibiotic resistance has emphasized the shortcomings in antibiotic drug development (Boucher et al., 2013). The move from biological based discovery methods to chemical approaches to identify candidates has left the antibiotic pipeline painfully dry (Lewis, 2013). The paucity of compounds that are effective against antibiotic resistant pathogens has led to great interest in antimicrobial peptides (AMPs) as potential solutions to the rise of resistant organisms (Hancock and Sahl, 2006; Fox, 2013). AMPs are short (5–50 amino acid) peptides that are produced by virtually all organisms as part of an innate immune system. There are 2,398 AMPs that have been reported (Antimicrobial Peptide Database—September 2013) and over 80% are cationic AMPs (CAMPs). Most positively charged AMPs interact with anionic bacterial membranes (Schmidtchen and Malmsten, 2013) which leads to a rapid breakdown in membrane function and subsequent cell death (Wimley, 2010). It is this mechanism of action that is of interest as it should be difficult for bacteria to develop resistance against lethal concentrations of CAMPs.

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Created

Date Created
  • 2013-12-25

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A Technology for Developing Synbodies with Antibacterial Activity

Description

The rise in antibiotic resistance has led to an increased research focus on discovery of new antibacterial candidates. While broad-spectrum antibiotics are widely pursued, there is evidence that resistance arises

The rise in antibiotic resistance has led to an increased research focus on discovery of new antibacterial candidates. While broad-spectrum antibiotics are widely pursued, there is evidence that resistance arises in part from the wide spread use of these antibiotics. Our group has developed a system to produce protein affinity agents, called synbodies, which have high affinity and specificity for their target. In this report, we describe the adaptation of this system to produce new antibacterial candidates towards a target bacterium. The system functions by screening target bacteria against an array of 10,000 random sequence peptides and, using a combination of membrane labeling and intracellular dyes, we identified peptides with target specific binding or killing functions. Binding and lytic peptides were identified in this manner and in vitro tests confirmed the activity of the lead peptides. A peptide with antibacterial activity was linked to a peptide specifically binding Staphylococcus aureus to create a synbody with increased antibacterial activity. Subsequent tests showed that this peptide could block S. aureus induced killing of HEK293 cells in a co-culture experiment. These results demonstrate the feasibility of using the synbody system to discover new antibacterial candidate agents.

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Created

Date Created
  • 2013-01-23

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Characterization of Therapeutic Monoclonals by Targeted Epitope

Description

Monoclonal antibody therapy focuses on engineering immune cells to target specific peptide sequences indicative of disease. An impediment in the continued advancement of this market is the lack of an

Monoclonal antibody therapy focuses on engineering immune cells to target specific peptide sequences indicative of disease. An impediment in the continued advancement of this market is the lack of an efficient, inexpensive means of characterization that can be broadly applied to any antibody while still providing high-density data. Many characterization methods address an antibody's affinity for its cognate sequence but overlook other important aspects of binding behavior such as off-target binding interactions. The purpose of this study is to demonstrate how the binding intensity between an antibody and a library of random-sequence peptides, otherwise known as an immunosignature, can be evaluated to determine antibody specificity and polyreactivity. A total of 24 commercially available monoclonal antibodies were assayed on 125K and 330K peptide microarrays and analyzed using a motif clustering program to predict candidate epitopes within each antigen sequence. The results support the further development of immunosignaturing as an antibody characterization tool that is relevant to both therapeutic and non-therapeutic antibodies.

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Created

Date Created
  • 2018-05

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Using Technological Models to Decrease Medical/Scientific Costs

Description

Both technological and scientific fields continue to revolutionize in a similar fashion; however, a major difference is that high-tech corporations have found models to continue progressions while still keeping product

Both technological and scientific fields continue to revolutionize in a similar fashion; however, a major difference is that high-tech corporations have found models to continue progressions while still keeping product costs low. The main objective was to identify which, if any, components of certain technological models could be used with the vaccine and pharmaceutical markets to significantly lower their costs. Smartphones and computers were the two main items investigated while the two main items from the scientific standpoint were vaccines and pharmaceuticals. One concept had the ability to conceivably decrease the costs of vaccines and drugs and that was "market competition". If the United States were able to allow competition within the vaccine and drug companies, it would allow for the product prices to be best affected. It would only take a few small companies to generate generic versions of the drugs and decrease the prices. It would force the larger competition to most likely decrease their prices. Furthermore, the PC companies use a cumulative density function (CDF) to effectively divide their price setting in each product cycle. It was predicted that if this CDF model were applied to the vaccine and drug markets, the prices would no longer have to be extreme. The corporations would be able to set the highest price for the wealthiest consumers and then slowly begin to decrease the costs for the middle and lower class. Unfortunately, the problem within the vaccine and pharmaceutical markets was not the lack of innovation or business models. The problem lied with their liberty to choose product costs due to poor U.S. government regulations.

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Date Created
  • 2016-12

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Development of Synbody Peptides for PD-L1 Blockade for use as a Cancer Vaccine Adjuvant

Description

PD-L1 blockade has shown recent success in cancer therapy and cancer vaccine regimens. One approach for anti-PD-L1 antibodies has been their application as adjuvants for cancer vaccines. Given the disadvantages

PD-L1 blockade has shown recent success in cancer therapy and cancer vaccine regimens. One approach for anti-PD-L1 antibodies has been their application as adjuvants for cancer vaccines. Given the disadvantages of such antibodies, including long half-life and adverse events related to their use, a novel strategy using synbodies in place of antibodies can be tested. Synbodies offer a variety of advantages, including shorter half-life, smaller size, and cheaper cost. Peptides that could bind PD-L1 were identified via peptide arrays and used to construct synbodies. These synbodies were tested with inhibition ELISA assays, SPR, and pull down assays. Additional flow cytometry analysis was done to determine the binding specificity of the synbodies to PD-L1 and the ability of those synbodies to inhibit the PD-L1/PD-1 interaction. Although analysis of permeabilized cells expressing PD-L1 indicated that the synbodies could successfully bind PD-L1, those results were not replicated in non-permeabilized cells. Further assays suggested that the binding of the synbodies was non-specific. Other tests were done to see if the synbodies could inhibit the PD-1/PD-L1 interaction. This assay did not yield any conclusive results and further experimentation is needed to determine the efficacy of the synbodies in inhibiting this interaction.

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Created

Date Created
  • 2016-12

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VDAP[a]: An R Package for Data Visualization and Motif Analysis on Peptide Microarrays

Description

Advances in peptide microarray technology have allowed for the creation of fast-paced and modular experiments within affinity ligand discovery. Previously, low density peptide arrays of 10,000 peptides were used to

Advances in peptide microarray technology have allowed for the creation of fast-paced and modular experiments within affinity ligand discovery. Previously, low density peptide arrays of 10,000 peptides were used to identify low affinity peptide ligands for a target protein; an approach that can be subsequently improved upon with a number of techniques. VDAP[a] offers more information about the relative affinity of protein-peptide interactions via signal intensity in contrast to high throughput screening (HTS) and display technologies which offer binary data. Now, high density peptide arrays with 130,000 to 330,000 peptides are available that allow screening across peptide libraries of greater diversity. With this increase in scale and diversity, faster analytical tools are needed to adequately characterize array data. Using the statistical power available in the R programming language, we have created a flexible analysis package that efficiently processes high density peptide array data from a variety of layouts, rank existing peptide hits, and utilize signal intensity data to generate new hits. This analysis provides a user-friendly method to efficiently analyze high density peptide array data, generate peptide leads for targeted therapeutic development, and further improve peptide array technologies.

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Date Created
  • 2015-12

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Evaluation of Norovirus Detection in Dilute Solutions

Description

In this project, biochemical characteristics of peptide binding agents, synthetic antibodies or synbodies, were examined with respect to the capture efficiency and specific binding ability to norovirus. Norovirus, although generally

In this project, biochemical characteristics of peptide binding agents, synthetic antibodies or synbodies, were examined with respect to the capture efficiency and specific binding ability to norovirus. Norovirus, although generally not a deadly pathogen, is the most common cause of acute gastroenteritis and outbreaks present a large social and financial burden to the healthcare and food service industries. With Dr. Diehnelt's laboratory group, a platform has been developed that enables us to rapidly construct peptide-based affinity ligands that can be characterized for binding to norovirus. The design needed to display clear results, be simple to operate, and be inexpensive to produce and use. Four synbodies, originally engineered with a specificity to the GII.4 Minerva genotype were tested with different virus strains varying in similarity to the GII.4 Minerva between 43% and 95.4%. Initial assays utilized norovirus-like particles to qualitatively compare the capture efficiency of the different synbodies without utilizing limited resources. To quantify the amount of actual virus captured by the synbodies, western blots with RT-PCR and RT-qPCR were utilized. The results indicated the synbodies were able to enrich the dilute solutions of the different noroviruses utilizing a magnetic bead pull-down assay. The capture efficiencies of the synbodies were comparable to currently utilized binding agents such as aptamers and porcine gastric mucine magnetic beads. This thesis presents data collected over nearly two years of research at the Center for Innovations in Medicine at the Biodesign Institute located at Arizona State University.

Contributors

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Created

Date Created
  • 2016-05

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Can Akt3 Decrease Tumorigenicity in Glioblastoma Multiforme Through a Cell Cycle Mechanism?

Description

Glioblastoma multiforme is associated with a very low survival rate and is recognized as the most vicious form of intracranial cancer. The Akt gene pathway has three different isoforms, each

Glioblastoma multiforme is associated with a very low survival rate and is recognized as the most vicious form of intracranial cancer. The Akt gene pathway has three different isoforms, each of which has a different role in the tumors of GBM. Preliminary data suggests that Akt3 may work to decrease tumorigenicity. A produced image that visualizes the subcellular localization of Akt3 led the author to believe that Akt3 may reduce tumorigenicity by decreasing genomic instability caused by the cancer. To explore this, flow cytometry was performed on GBM cell lines with Akt3v1 over-expression, Akt3v2 over-expression, and a control glioma cell line.

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Date Created
  • 2012-12

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Predicting the Binding Interactions of TNFR2 and PD-L1 on LT-ɑ, TRAF2, and CD80

Description

The field of biomedical research relies on the knowledge of binding interactions between various proteins of interest to create novel molecular targets for therapeutic purposes. While many of these interactions

The field of biomedical research relies on the knowledge of binding interactions between various proteins of interest to create novel molecular targets for therapeutic purposes. While many of these interactions remain a mystery, knowledge of these properties and interactions could have significant medical applications in terms of understanding cell signaling and immunological defenses. Furthermore, there is evidence that machine learning and peptide microarrays can be used to make reliable predictions of where proteins could interact with each other without the definitive knowledge of the interactions. In this case, a neural network was used to predict the unknown binding interactions of TNFR2 onto LT-ɑ and TRAF2, and PD-L1 onto CD80, based off of the binding data from a sampling of protein-peptide interactions on a microarray. The accuracy and reliability of these predictions would rely on future research to confirm the interactions of these proteins, but the knowledge from these methods and predictions could have a future impact with regards to rational and structure-based drug design.

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Agent

Created

Date Created
  • 2021-05