scholarly journals A label-free alternative to ELISA: Protein interaction analysis in drug development and production

2005 ◽  
Vol 27 (3) ◽  
pp. 28-31 ◽  
Author(s):  
Gary Franklin

With the ever-increasing understanding of the complexity of human protein interactions that impact directly on the safety and efficacy of therapeutic interventions, so the responsibility of researchers and drug companies to fully characterize drug candidates becomes a more and more onerous task. Using conventional methods, like ELISA, to examine even the most obvious interaction of, for example, a therapeutic antibody can add weeks or months on to the development process and clog up R&D programmes with thousands of man hours. And failure to fully examine the nature of important interactions may result in costly drug failures further down the pipeline.

2021 ◽  
Vol 11 (5) ◽  
pp. 578
Author(s):  
Oge Gozutok ◽  
Benjamin Ryan Helmold ◽  
P. Hande Ozdinler

Hereditary spastic paraplegia (HSP) and primary lateral sclerosis (PLS) are rare motor neuron diseases, which affect mostly the upper motor neurons (UMNs) in patients. The UMNs display early vulnerability and progressive degeneration, while other cortical neurons mostly remain functional. Identification of numerous mutations either directly linked or associated with HSP and PLS begins to reveal the genetic component of UMN diseases. Since each of these mutations are identified on genes that code for a protein, and because cellular functions mostly depend on protein-protein interactions, we hypothesized that the mutations detected in patients and the alterations in protein interaction domains would hold the key to unravel the underlying causes of their vulnerability. In an effort to bring a mechanistic insight, we utilized computational analyses to identify interaction partners of proteins and developed the protein-protein interaction landscape with respect to HSP and PLS. Protein-protein interaction domains, upstream regulators and canonical pathways begin to highlight key cellular events. Here we report that proteins involved in maintaining lipid homeostasis and cytoarchitectural dynamics and their interactions are of great importance for UMN health and stability. Their perturbation may result in neuronal vulnerability, and thus maintaining their balance could offer therapeutic interventions.


2020 ◽  
Author(s):  
Bolin Wu ◽  
Haitao Shang ◽  
Xitian Liang ◽  
Huajing Yang Huajing Yang ◽  
Hui Jing ◽  
...  

Abstract Background: Hepatocellular carcinoma (HCC) poses a severe threat to human health. The NET-1 protein has been proved to be strongly associated with HCC proliferation and metastasis in our previous study. Methods: Here, we developed a label-free proteome mass spectrometry workflow to analyze formalin-fixed and paraffin-embedded HCC xenograft samples collected in our previous study. Results: The result showed that 78 proteins were differentially expressed after NET-1 protein inhibited. Among them, the expression of 61 proteins up-regulated and the expression of 17 proteins were significantly down-regulated. Of the differentially expressed proteins, the vast majority of Gene Ontology enrichment terms belong to the biological process. The KEGG pathway enrichment analysis showed that the 78 differentially expressed proteins significantly enriched in 45 pathways. We concluded that the function of the NET-1 gene is not only to regulate HCC but also to participate in a variety of biochemical metabolic pathways in the human body. Furthermore, the protein-protein interaction analysis indicated that the interactions of differentially expressed proteins are incredibly sophisticated. All the protein-protein interactions happened after the NET-1 gene has been silenced. Conclusions: Finally, our study also provides a useful proposal for targeted therapy based on tetraspanin proteins to treat HCC, and further mechanism investigations are needed to reveal a more detailed mechanism of action for NET-1 protein regulation of HCC.


2016 ◽  
Vol 21 (10) ◽  
pp. 1100-1111 ◽  
Author(s):  
Adriana Lepur ◽  
Lucija Kovačević ◽  
Robert Belužić ◽  
Oliver Vugrek

Protein interaction networks are the basis for human metabolic and signaling systems. Interaction studies often use bimolecular fluorescence complementation (BiFC) to reveal the formation and cellular localization of protein complexes. However, large-scale studies were either far from native conditions in human cells or limited by laborious restriction/ligation cloning techniques. Here, we describe a new tool for protein interaction screening based on Gateway-compatible BiFC vectors. We made a set of four new vectors that permit fusion of candidate proteins to the N or C fragment of Venus in all fusion positions. We have validated the vectors and confirmed self-association of AHCY, AHCYL1, and galectin-3. In a high-throughput BiFC screen, we identified new AHCY interaction partners: galectin-3 and PUS7L. We also describe additional steps in protein interaction analysis, applied for AHCY–galectin-3 interaction. First, we classified the interaction in intracellular vesicles using CellCognition, machine learning free software. Then we identified the vesicles as endosomal pathway compartments, in line with known galectin-3 trafficking route. This offers a platform to rapidly identify and localize new protein interactions inside living cells, a prerequisite to validate in silico interactome data, and ultimately decode complex protein networks.


Author(s):  
João Botelho ◽  
Paulo Mascarenhas ◽  
José João Mendes ◽  
Vanessa Machado

Recent studies supported a clinical association between Parkinson’s Disease (PD) and periodontitis. Hence, investigating possible protein interactions between these two conditions is of interest. In this study, we conducted a protein-protein network interaction analysis with recognized genes encoding proteins for PD and periodontitis. Genes of interest were collected via GWAS database. Then, we conducted a protein interaction analysis using STRING database, with a highest confidence cut-off of 0.9. Our protein network casted a comprehensive analysis of potential protein-protein interactions between PD and periodontitis. This analysis may underpin valuable information for new candidate molecular mechanisms between PD and periodontitis and may serve new potential targets for research purposes. These results should be carefully interpreted giving the limitations of this approach.


ACS Sensors ◽  
2016 ◽  
Vol 1 (6) ◽  
pp. 781-788 ◽  
Author(s):  
Mathias Wipf ◽  
Ralph L. Stoop ◽  
Giulio Navarra ◽  
Said Rabbani ◽  
Beat Ernst ◽  
...  

2019 ◽  
Author(s):  
David Armanious ◽  
Jessica Schuster ◽  
George F. Tollefson ◽  
Anthony Agudelo ◽  
Andrew T. DeWan ◽  
...  

AbstractBackgroundData analysis has become crucial in the post genomic era where the accumulation of genomic information is mounting exponentially. Analyzing protein-protein interactions in the context of the interactome is a powerful approach to understanding disease phenotypes.ResultsWe describe Proteinarium, a multi-sample protein-protein interaction network analysis and visualization tool. Proteinarium can be used to analyze data for samples with dichotomous phenotypes, multiple samples from a single phenotype or a single sample. Then, by similarity clustering, the network-based relations of samples are identified and clusters of related samples are presented as a dendrogram. Each branch of the dendrogram is built based on network similarities of the samples. The protein-protein interaction networks can be analyzed and visualized on any branch of the dendrogram. Proteinarium’s input can be derived from transcriptome analysis, whole exome sequencing data or any high-throughput screening approach. Its strength lies in use of gene lists for each sample as a distinct input which are further analyzed through protein interaction analyses. Proteinarium output includes the gene lists of visualized networks and PPI interaction files where users can analyze the network(s) on other platforms such as Cytoscape. In addition, since the dendrogram is written in Newick tree format, users can visualize it in other software platforms like Dendroscope, ITOL.ConclusionsProteinarium, through the analysis and visualization of PPI networks, allows researchers to make important observations on high throughput data for a variety of research questions. Proteinarium identifies significant clusters of patients based on their shared network similarity for the disease of interest and the associated genes. Proteinarium is a command-line tool written in Java with no external dependencies and it is freely available at https://github.com/Armanious/Proteinarium.


2020 ◽  
Author(s):  
Bolin Wu ◽  
Haitao Shang ◽  
Xitian Liang ◽  
Huajing Yang Huajing Yang ◽  
Hui Jing ◽  
...  

Abstract Hepatocellular carcinoma (HCC) poses a severe threat to human health. The NET-1 protein has been proved to be strongly associated with HCC proliferation and metastasis in our previous study. Here, we established and validated NET-1 siRNA nanoparticles system to conduct targeted gene therapy of HCC xenograft in vivo with the aid of sonodynamic therapy (SDT). Then, a label-free proteome mass spectrometry workflow to analyze formalin-fixed and paraffin-embedded HCC xenograft samples collected in this study. The result showed that 78 proteins were differentially expressed after NET-1 protein inhibited. Among them, the expression of 61 proteins up-regulated and the expression of 17 proteins were significantly down-regulated. Of the differentially expressed proteins, the vast majority of Gene Ontology enrichment terms belong to the biological process. The KEGG pathway enrichment analysis showed that the 78 differentially expressed proteins significantly enriched in 45 pathways. We concluded that the function of the NET-1 gene is not only to regulate HCC but also to participate in a variety of biochemical metabolic pathways in the human body. Furthermore, the protein-protein interaction analysis indicated that the interactions of differentially expressed proteins are incredibly sophisticated. All the protein-protein interactions happened after the NET-1 gene has been silenced. Finally, our study also provides a useful proposal for targeted therapy based on tetraspanin proteins to treat HCC, and further mechanism investigations are needed to reveal a more detailed mechanism of action for NET-1 protein regulation of HCC.


2020 ◽  
Author(s):  
Md. Shahadat Hossain ◽  
Arpita Singha Roy ◽  
Md. Sajedul Islam

AbstractRas association domain-containing protein 5 (RASSF5), one of the prospective biomarkers for tumors, generally plays a crucial role as a tumor suppressor. As deleterious effects can result from functional differences through SNPs, we sought to analyze the most deleterious SNPs of RASSF5 as well as predict the structural changes associated with the mutants that hamper the normal protein-protein interactions. We adopted both sequence and structure based approaches to analyze the SNPs of RASSF5 protein. We also analyzed the putative post translational modification sites as well as the altered protein-protein interactions that encompass various cascades of signals. Out of all the SNPs obtained from the NCBI database, only 25 were considered as highly deleterious by six in silico SNP prediction tools. Among them, upon analyzing the effect of these nsSNPs on the stability of the protein, we found 17 SNPs that decrease the stability. Significant deviation in the energy minimization score was observed in P350R, F321L, and R277W. Besides this, docking analysis confirmed that P350R, A319V, F321L, and R277W reduce the binding affinity of the protein with H-Ras, where P350R shows the most remarkable deviation. Protein-protein interaction analysis revealed that RASSF5 acts as a hub connecting two clusters consisting of 18 proteins and alteration in the RASSF5 may lead to disassociation of several signal cascades. Thus, based on these analyses, our study suggests that the reported functional SNPs may serve as potential targets for different proteomic studies, diagnosis and therapeutic interventions.


2021 ◽  
Vol 8 ◽  
Author(s):  
Bolin Wu ◽  
Haitao Shang ◽  
Jiayin Liu ◽  
Xitian Liang ◽  
Yanchi Yuan ◽  
...  

Hepatocellular carcinoma (HCC) poses a severe threat to human health. The NET-1 protein has been proved to be strongly associated with HCC proliferation and metastasis in our previous study. Here, we established and validated the NET-1 siRNA nanoparticles system to conduct targeted gene therapy of HCC xenograft in vivo with the aid of sonodynamic therapy. Then, we conducted a label-free proteome mass spectrometry workflow to analyze formalin-fixed and paraffin-embedded HCC xenograft samples collected in this study. The result showed that 78 proteins were differentially expressed after NET-1 protein inhibited. Among them, the expression of 17 proteins upregulated and the expression of 61 proteins were significantly downregulated. Of the protein abundance, the vast majority of Gene Ontology enrichment terms belong to the biological process. The KEGG pathway enrichment analysis showed that the 78 differentially expressed proteins significantly enriched in 45 pathways. We concluded that the function of the NET-1 gene is not only to regulate HCC but also to participate in a variety of biochemical metabolic pathways in the human body. Furthermore, the protein–protein interaction analysis indicated that the interactions of differentially expressed proteins are incredibly sophisticated. All the protein–protein interactions happened after the NET-1 gene has been silenced. Finally, our study also provides a useful proposal for targeted therapy based on tetraspanin proteins to treat HCC, and further mechanism investigations are needed to reveal a more detailed mechanism of action for NET-1 protein regulation of HCC.


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