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

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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 remain a mystery, knowledge of these properties and interactions could…

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.

Date Created
2021-05
Agent

Early Detection of MicroRNA Biomolecular Markers using CRISPR-Cas12a

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Description
Extensive efforts have been made to develop efficient and low-cost methods for diagnostics to identify molecular biomarkers that are linked to a wide array of conditions, including cancer. A highly developed method includes utilizing the gene-editing enzyme CRISPR-Cas12a (Cpf1), which…

Extensive efforts have been made to develop efficient and low-cost methods for diagnostics to identify molecular biomarkers that are linked to a wide array of conditions, including cancer. A highly developed method includes utilizing the gene-editing enzyme CRISPR-Cas12a (Cpf1), which demonstrates double-stranded DNase activity with RuvC catalytic domain with high sensitivity and specificity. This DNase activity is RNA-guided and requires a T-rich PAM site on the target sequence for functional cleavage. There have been recent efforts to utilize this DNase activity of Cas12a by combining it with isothermal amplification and analysis by lateral strip tests. This project examined CRISPR-based early detection of microRNA biomarkers. MicroRNA are short RNA molecules that have large roles in post-transcriptional gene regulation. However, due the short length of microRNA and its single-stranded nature, it is challenging to use Cas12a for microRNA detection using existing methods. Thus, this project investigated the potential of two microRNA detection strategies for recognition by CRISPR-Cas12a. These methods were microRNA-splinted ligation with polymerase chain reaction (PCR) and MicroRNA-specific reverse transcriptase PCR (RT-PCR). Gel imaging demonstrated effective amplification of ligated DNA through microRNA-splinted ligation with PCR/RPA. In addition, lateral strips tests showed effective cleavage of the target sequences by Cas12a. However, RT-PCR method demonstrated low amplification by PCR and inefficient poly(A) elongation. This project paves the way for the detection of an extensive range of microRNA biomarkers that are linked to an array of diseases. Future directions include analysis and modifications of RT-PCR method to improve experimental results, extending these detection methods to a larger range of microRNA sequences, and eventually utilizing them for detection in human samples.
Date Created
2019-05
Agent

Algorithmic Prediction of Binding Sites of TNFα/TNFR2 and PD-1/PD-L1

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Description
Predicting the binding sites of proteins has historically relied on the determination of protein structural data. However, the ability to utilize binding data obtained from a simple assay and computationally make the same predictions using only sequence information would be…

Predicting the binding sites of proteins has historically relied on the determination of protein structural data. However, the ability to utilize binding data obtained from a simple assay and computationally make the same predictions using only sequence information would be more efficient, both in time and resources. The purpose of this study was to evaluate the effectiveness of an algorithm developed to predict regions of high-binding on proteins as it applies to determining the regions of interaction between binding partners. This approach was applied to tumor necrosis factor alpha (TNFα), its receptor TNFR2, programmed cell death protein-1 (PD-1), and one of its ligand PD-L1. The algorithms applied accurately predicted the binding region between TNFα and TNFR2 in which the interacting residues are sequential on TNFα, however failed to predict discontinuous regions of binding as accurately. The interface of PD-1 and PD-L1 contained continuous residues interacting with each other, however this region was predicted to bind weaker than the regions on the external portions of the molecules. Limitations of this approach include use of a linear search window (resulting in inability to predict discontinuous binding residues), and the use of proteins with unnaturally exposed regions, in the case of PD-1 and PD-L1 (resulting in observed interactions which would not occur normally). However, this method was overall very effective in utilizing the available information to make accurate predictions. The use of the microarray to obtain binding information and a computer algorithm to analyze is a versatile tool capable of being adapted to refine accuracy.
Date Created
2018-05
Agent

A Simple Platform for the Rapid Development of Antimicrobials

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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 of new antimicrobials. The goal was to produce in as…

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.

Date Created
2017-12-14
Agent

Characterization of Therapeutic Monoclonals by Targeted Epitope

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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 efficient, inexpensive means of characterization that can be broadly applied…

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.
Date Created
2018-05
Agent

Evaluation of Norovirus Detection in Dilute Solutions

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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 not a deadly pathogen, is the most common cause of…

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.
Date Created
2016-05
Agent

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

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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 of such antibodies, including long half-life and adverse events related…

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.
Date Created
2016-12
Agent

Development and In Depth Characterization of High Affinity Ligands for the Ebola Virus

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Description
The devastating 2014 Ebola virus outbreak in Western Africa demonstrated the lack of therapeutic approaches available for the virus. Although monoclonal antibodies (mAb) and other molecules have been developed that bind the virus, no therapeutic has shown the efficacy needed…

The devastating 2014 Ebola virus outbreak in Western Africa demonstrated the lack of therapeutic approaches available for the virus. Although monoclonal antibodies (mAb) and other molecules have been developed that bind the virus, no therapeutic has shown the efficacy needed for FDA approval. Here, a library of 50 peptide based ligands that bind the glycoprotein of the Zaire Ebola virus (GP) were developed. Using whole virus screening of vesicular stomatitis virus pseudotyped with GP, low affinity peptides were identified for ligand construction. In depth analysis showed that two of the peptide based molecules bound the Zaire GP with <100 nM KD. One of these two ligands was blocked by a known neutralizing mAb, 2G4, and showed cross-reactivity to the Sudan GP. This work presents ligands with promise for therapeutic applications across multiple variants of the Ebola virus.
Date Created
2016-12
Agent

Using Technological Models to Decrease Medical/Scientific Costs

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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 costs low. The main objective was to identify which, if…

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.
Date Created
2016-12
Agent

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

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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 of which has a different role in the tumors of…

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.
Date Created
2012-12
Agent
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