Methods in molecular biology
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Multiplex assays that allow the simultaneous measurement of multiple analytes in small sample quantities have developed into a widely used technology. Their implementation spans across multiple assay systems and can provide readouts of similar quality as the respective single-plex measures, albeit at far higher throughput. Multiplex assay systems are therefore an important element for biomarker discovery and development strategies but analysis of the derived data can face substantial challenges that may limit the possibility of identifying meaningful biological markers. This chapter gives an overview of opportunities and challenges of multiplexed biomarker analysis, in particular from the perspective of machine learning aimed at identification of predictive biological signatures.
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Post-translational modifications (PTMs) are covalent modifications that proteins might undergo following or sometimes during the process of translation. Together with gene diversity, PTMs contribute to the overall variety of possible protein function for a given organism. Single-nucleotide polymorphisms (SNPs) are the most common form of variations found in the human genome, and have been found to be associated with diseases like Alzheimer's disease (AD) and Parkinson's disease (PD), among many others. ⋯ However, these data are unsystematically distributed across a number of diverse databases. Thus, there is a need for efforts toward data standardization and validation of bioinformatics algorithms that can fully leverage SNP and PTM information for biomedical research. In this book chapter, we will present some of the commonly used databases for both SNVs and PTMs and describe a broad approach that can be applied to many scenarios for studying the impact of nsSNVs on PTM sites of human proteins.
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High resolution mass spectrometry has revolutionized proteomics over the past decade, resulting in tremendous amounts of data in the form of mass spectra, being generated in a relatively short span of time. The mining of this spectral data for analysis and interpretation though has lagged behind such that potentially valuable data is being overlooked because it does not fit into the mold of traditional database searching methodologies. ⋯ In this chapter, we propose a methodology to integrate de novo peptide sequencing using three commonly available software solutions in tandem, complemented by homology searching, and manual validation of spectra. This simplified method would allow greater use of de novo sequencing approaches and potentially greatly increase proteome coverage leading to the unearthing of valuable insights into protein biology, especially of organisms whose genomes have been recently sequenced or are poorly annotated.
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Network analysis methods are increasing in popularity. An approach commonly applied to analyze proteomics data involves the use of protein-protein interaction (PPI) networks to explore the systems-level cooperation between proteins identified in a study. ⋯ Here we describe a method for calculating robust empirical p-values for protein interaction networks. We also provide a worked example with python code demonstrating the implementation of this methodology.
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The protocol herein describes a robust and proven method for the measurement of pseudokinase-ligand interaction using a fluorescence-based thermal shift assay (TSA). Pseudokinases are kinase-like proteins that have recently emerged as crucial regulatory modules of signal transduction pathways and may well represent a novel class of drug targets. However, unlike kinases, the regulatory activity of pseudokinases is mainly conferred through protein-protein interactions. ⋯ Ligand binding to a protein is known to increase its thermal stability, which is reflected by a shift between the thermal denaturation curves of the unliganded protein and the liganded protein. Here, we illustrate the utility of the method with the pseudokinases, ErbB3/HER3, ILK, ROP5Bi, JAK1, JAK2, TYK2, MLKL, STRAD, TRIB1, VRK3, and ROR1. This method can also be used to determine optimal buffer conditions that may increase protein stability and can be tailored to other protein families.