Guide Functional Protein Microarrays in Drug Discovery (Drug Discovery Series)

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Current applications of antibody microarrays

You do not have JavaScript enabled. Please enable JavaScript to access the full features of the site or access our non-JavaScript page. Add to Cart. As central actors in most biological functions, proteins are the subject of intense study. This has driven the development of increasingly sophisticated approaches for the study of proteins, which has extended to proteomic level methodologies. Yet currently no book has addressed all aspects of functional microarrays in a coherent and integrated fashion. Until now. Meeting the need for comprehensive and authoritative information, Functional Protein Microarrays in Drug Discovery provides an up-to-date overview of the field and the background required to actually design and develop arrays or perform and analyze array experiments.

The book is divided into five main sections that address critical aspects of the field. The first focuses on the generation of functional protein content, the first and perhaps most challenging aspect of protein microarrays. Similarly, the third section reviews current and next generation approaches to assay detection.

The fourth and largest section, dedicated to applications, spans the breadth of published applications, from biomolecular interaction discovery and characterization to humoral response biomarker profiling, enzyme substrate identification and drug discovery. The final section addresses fundamental computational issues including image and data analysis as well as data visualization. Indeed, challenges are to be expected in a fast-moving, interdisciplinary endeavor such as this, where molecular biology, protein chemistry, bioinformatics, engineering, and physical sciences intersect.

As the first integrated reference for functional protein microarrays, this book helps you not only meet the challenges but also excel in your research.

Protein–Protein Interactions in Plain View

Zhu, one of the contributors to this text, was recently featured in an article in Austin's The Statesman. Daniel E. He also maintains a blog that explores organic chemistry. Rupcich and J. In personalized medicine, there is a clear necessity to identify the network comprising the genome-transcriptome-proteome patient profile. Moreover, cancer incidence could achieve pandemic levels by the year Therefore, a complex approach in health needs high-throughput technologies that can sustain personalized medicine.

Developing the two-tiered health system 65 to two-tiered personalized medicines is a demanding desiderate in oncology. The implementation of omics facilities in clinical practice is warranted in order to offer effective personalized medicine to the patient.

7 Steps to Drug Discovery

However, in order to for this to be accomplished, there are several draw-backs that first need to be resolved, such as the high costs of implementation, differences between data generation and the capacity to analyze large amounts of data, the existence of multidisciplinary teams and global economic relevance An interdisciplinary effort is needed between several specialties, physicians, data scientists and health insurance systems to provide un-biased advantage to clinical practice These analyses of disease-specific mutations can lead to setting specific therapies in accordance with their gene profiles.

However, a more direct correlation with disease development is established by protein function, regulation and abundance. Driving the development of the disease protein concentrations within an organ, tissue, or cell can pinpoint an abnormality.

Bestselling Series

This goal can be achieved, however, only by combining genomic knowledge with traditional clinical approaches, the patient's personal medical and family history, and relevant clinical data, such as imaging and in vitro diagnostics results Profiling using protein microarrays, can be efficiently applied in biomarker discovery, validation and diagnosis, and can aid personalized medicine All the pathways that are deregulated in tumorigenesis and that are the result of genetic alterations accumulation can be, at least theoretically, therapeutic targets in oncology.

The real-life efficacy of such molecular therapeutics is highly variable among individuals; thus, minute details of such differences can be identified. This identification is essential for the optimization of therapy.

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RPPA is an antibody-based highly quantitative proteomic technology, used for profiling the expression and modification of signaling proteins, mainly in low-abundance analytes cases. For example, in breast cancer, which is a heterogeneous disease with various histological and molecular variants, personalized medicine has become a major goal for patient management over the past years. In this type of cancer, molecular profiling and genomic analysis based on array technologies have led to the discovery of targeted drug therapies Using a designed RPPA, personalized therapy was intended to search for the most effective drug.

Thus, drug sensitivity can be predicted in this system based on the quantitative profiles of protein expression 72 , Signaling transduction pathways that trigger oncogenesis can also be depicted by proteomics profiling and these particularities can lead the option for personalized therapy 74 , To increase the quantization sensitivity of RPPA 76 , 77 labeling was reported to be far more accurate when using quantum dots Qdots.

Briefly, sample lysates are used for serial dilution and then immobilized on the array. Primary and secondary antibodies detect the immobilized proteins, and the reaction is further detected by Qdot assay.

Daniel S. Schabacker | Argonne National Laboratory

Qdot is actually a fluorophore with a nanometal structure that develops a clear linear signal, photo-bleaching from the organic fluorophores In this form, RPPA would detect post-translational modifications, such as phosphorylation, modifications that are seminal for depicting intracellular events related to drug sensitivity Another recent version of protein arrays was published, bringing new information to personalized medicine. Thus, antibody co-localization microarray ACM , avoids some draw-backs from classical protein microarrays e. Several parameters are improved, and therefore low volumes of sample and hence, low quantities of reagents are used.

In this manner, up to different protein-targets can be measured in hundreds of samples, displaying high specificity and sensitivity As protein microarrays are furnishing a plethora of records, several systems for data analysis have been reported. Ingenuity Pathway Analysis IPA is the most commonly used software for protein microarray data exploration This software links to published database and finds function s and pathway s for microarray analysis.

It can be used to integrate complex data from gene expression, microRNAs, single nucleotide polymorphisms SNPs and protein microarray Practice has shown that improvements in data processing systems are warranted; thus, recently reported Protein Microarray Analyzer software has several improved tools, as shown in Fig. To identify tumor-associated antigens TAAs , antibody response and new antigen discovery other software were specifically developed for protein microarrays used in seromics, namely Prospector, LIMMA package, PAA package and Spotfire package 49 , 50 , 53 , The newest intervention of protein microarray technology was reported for the revolutionary immunotherapies that were recently approved.

New combinations of therapies are tested in pre-clinical settings. In this section, we will comment on the most frequent human pathologies that entail protein microarray technology in order to come one step closer to personalized therapy. Due to this extended array of samples, the proteins that can be identified in these diseases comprise a huge span of molecules in terms of types and concentrations. Sputum proteomes from lung diseases [e.

In acute respiratory distress ARDS , drug development and biomarkers to prognosticate the disease are crucial Deregulated cellular pathways leading to inflammation and epithelial injury have been revealed in ARDS. However, there are still no validated markers available for subclassifying patients 92,95, Therefore, subgroups of patients displaying particular molecular and clinical parameters could be identified using integrative omics data that will be required to accelerate personalized medicine upcoming in pulmonary diseases Hence, these markers could be further used for personalized care in patients with lung cancer In lung cancer therapy, the identification of immune-checkpoints before therapy commences is a recent goal of personalized medicine.

Tissue arrays and multiplex immunofluorescence have been used to evaluate 25 different types of immune-checkpoints and neoantigens. A recent study demonstrated that in lung therapy, protein-protein interaction and thorough intracellular signaling pathway mapping can reveal immune-checkpoint nodes that are associated with positive outcomes of the administered therapy As breast cancer is the second leading cause of cancer-related mortality among women worldwide, research has advanced at an accelerated pace.

Over the past ten years, significant assessments, such as cytogenetics, SNPs and gene expression arrays, copy number variation and DNA methylation, have aimed to divide breast cancer types on a genetic basis. Recent proteomics studies have focused on drug-induced signaling events that would trigger a process that is of seminal importance to clinical application, namely acquired drug resistance. The activation of kinases families e.

These approaches bring into the light individual networks that can be activated when acquiring resistance to HER2-targeted therapies The reported results revealed that apart from standard trastuzumab therapies, the combination with the dual mammalian target of rapamycin mTOR complex inhibitor impeded tumor growth. Thus, this study opens the door for personalized medicine clinical trials From lysates obtained from samples of breast cancer tissues, a personalized medicine protocol was recently reported using RPPA. This protocol could be used for the pharmacodynamic effects of standard therapies in various molecular subtypes Drug resistance in breast cancer is a therapeutic domain where protein microarray can bring new information.

Chemotherapy-resistant breast cancer stem cells CSCs were analyzed with protein arrays and the paclitaxel-resistant phenotype was associated with the overexpression of several proteins, such as growth factors, MMP proteins, Frizzled proteins and interleukin IL Ovarian cancer also has a large array of subtypes, serous, clear cell, endometrioid and mucinous epithelial ovarian carcinoma, all these having various chemotherapeutic sensitivities. Clear cell carcinoma CCC has high rates of recurrence associated with low chemosensitivity.

The reported differences would lead to new candidate target drugs In CCC, various activating pathways have been reported, yet again, possible personalized drug targets For example, 11 out of proteins identified from CCC samples were appending to different signaling networks in comparisons to other ovarian cancer samples, giving ground to the further development of personalized therapy in this particular type of ovarian cancer which is difficult to treat Signaling pathways that are enhanced in ovarian clear cell carcinoma in comparison to other sub-types In clear cell renal carcinoma ccRCC , which is the most frequent renal cancer type, it is assumed that one third of patients would progress after surgery.

A critical comparison of protein microarray fabrication technologies

Therefore, establishing molecular patterns that would stratify patients would significantly improve survival. In vitro cultures established from patient specimens have been used to develop orthotopic xenograft tumors in animal models. RPPA was used to evaluate the proteome in tumor cells and it was shown that tumor-propagating cells had clear altered kinase cascades, alterations that were associated with stage, the angiogenesis level and mTOR pathways.

Testing in vitro and in vivo pharmacological action on ccRCC tumor cells can bring a personalized screening for therapies in patients, hence personalizing the therapy. Accordinly, only a high-throughput profiling, such as the one provided by RPPA could cover all the triggered pathways Custom RPPA was used to establish the protein profiling in pediatric acute myeloid leukemia AML bone marrow samples in comparison to normal samples.

Protein functional groups and protein clusters identification has shown that there are 12 protein clusters that can stratify AML patients into 8 protein signatures. The identification of particular protein signatures creates the premises for specific combinations of therapies with increased therapeutic efficacy In colorectal cancer the immunoproteomics endeavor was reported for discovering auto-antibodies as possible cancer markers.

Tissue proteins were extracted from primary tumors, metastastic and benign tissues, and autoantigens were identified. These autoantigens can have prognostic significance in colorectal cancer that has a tendency to induce liver metastases. Autoantibodies can be found in the sera of patients diagnosed with colorectal cancer; thus, finding the tissue antigens that are specific for the neoplastic tissue is of outmost importance in personalizing therapy When studying the association of angiogenesis-related proteins with anti-angiogenic therapy in colorectal cancer protein, arrays were used.

The proteome profiler array identified in dynamics the proteins before, after treatment and after tumor progression. The antibody arrays revealed that during treatment, alterations in the levels of protein, such as MMP8, tissue inhibitor of matrix metalloproteinase TIMP 4 and epidermal growth factor EGF were observed.

In organ transplantation, immunological rejection is the main clinical drawback; thus, the optimal proteomics characterization would ensure the best match between donor and recipient. Recently, a screening tool was developed using peptide array from the donor's human leukocyte antigen HLA to assess post-transplant sera from the recipient and evaluate the risk of immune-mediated rejection. In this pilot study, up to individual peptides were customized.