Publisher's Synopsis
There are many methods to investigate protein-protein interactions. Each of the approaches has its own strengths and weaknesses, especially with regard to the sensitivity and specificity of the method. A high sensitivity means that many of the interactions that occur in reality are detected by the screen. A high specificity indicates that most of the interactions detected by the screen are occurring in reality. Protein-protein interaction plays key role in predicting the protein function of target protein and drug ability of molecules. The majority of genes and proteins realize resulting phenotype functions as a set of interactions. The in vitro and in vivo methods like affinity purification, Y2H (yeast 2 hybrid), TAP (tandem affinity purification), and so forth have their own limitations like cost, time, and so forth, and the resultant data sets are noisy and have more false positives to annotate the function of drug molecules. Thus, in silico methods which include sequence-based approaches, structure-based approaches, chromosome proximity, gene fusion, in silico 2 hybrid, phylogenetic tree, phylogenetic profile, and gene expression-based approaches were developed. Elucidation of protein interaction networks also contributes greatly to the analysis of signal transduction pathways. Recent developments have also led to the construction of networks having all the protein-protein interactions using computational methods for signaling pathways and protein complex identification in specific diseases. The function and activity of a protein are often modulated by other proteins with which it interacts. This book named Recent Approaches of Protein Interactions is intended as a practical guide to the analysis of such protein-protein interactions. We discuss biochemical methods such as protein affinity chromatography, affinity blotting, coimmunoprecipitation, and cross-linking; molecular biological methods such as protein probing, the two-hybrid system, and phage display: and genetic methods such as the isolation of extragenic suppressors, synthetic mutants, and unlinked non complementing mutants. This book describes how binding affinities can be evaluated by techniques including protein affinity chromatography, sedimentation, gel filtration, fluorescence methods, solid-phase sampling of equilibrium solutions, and surface plasmon resonance. Protein-protein interactions (PPIs) handle a wide range of biological processes, including cell-to-cell interactions and metabolic and developmental control. Protein-protein interaction is becoming one of the major objectives of system biology. Noncovalent contacts between the residue side chains are the basis for protein folding, protein assembly, and PPI. These contacts induce a variety of interactions and associations among the proteins. Based on their contrasting structural and functional characteristics, PPIs can be classified in several ways. On the basis of their interaction surface, they may be homo- or heterooligomeric; as judged by their stability, they may be obligate or nonobligate; as measured by their persistence, they may be transient or permanent. A given PPI may be a combination of these three specific pairs. The transient interactions would form signaling pathways while permanent interactions will form a stable protein complex. Uncovering protein-protein interaction information helps in the identification of drug targets. Studies have shown that proteins with larger number of interactions (hubs) can include families of enzymes, transcription factors, and intrinsically disordered proteins, among others. However, PPIs involve more heterogeneous processes and the scope of their regulation is large. For more accurate understanding of their importance in the cell, one has to identify various interactions and determine the aftermath of the interactions. In recent years, PPI data have been enhanced by guaranteed high-throughput experimental methods, such as two-hybrid systems, mass spectrometry, phage display, and protein chip technology. Comprehensive PPI networks have been built from these experimental resources. However, the voluminous nature of PPI data is imposing a challenge to laboratory validation. Computational analysis of PPI networks is increasingly becoming a mandatory tool to understand the functions of unexplored proteins. At present, protein-protein interaction (PPI) is one of the key topics for the development and progress of modern system's biology. There are many methods to investigate protein-protein interactions. Each of the approaches has its own strengths and weaknesses, especially with regard to the sensitivity and specificity of the method. A high sensitivity means that many of the interactions that occur in reality are detected by the screen. A high specificity indicates that most of the interactions detected by the screen are occurring in reality. Protein-protein interaction plays key role in predicting the protein function of target protein and drug ability of molecules. The majority of genes and proteins realize resulting phenotype functions as a set of interactions. The in vitro and in vivo methods like affinity purification, Y2H (yeast 2 hybrid), TAP (tandem affinity purification), and so forth have their own limitations like cost, time, and so forth, and the resultant data sets are noisy and have more false positives to annotate the function of drug molecules. Thus, in silico methods which include sequence-based approaches, structure-based approaches, chromosome proximity, gene fusion, in silico 2 hybrid, phylogenetic tree, phylogenetic profile, and gene expression-based approaches were developed. Elucidation of protein interaction networks also contributes greatly to the analysis of signal transduction pathways. Recent developments have also led to the construction of networks having all the protein-protein interactions using computational methods for signaling pathways and protein complex identification in specific diseases. The function and activity of a protein are often modulated by other proteins with which it interacts. This book named Recent Approaches of Protein Interactions is intended as a practical guide to the analysis of such protein-protein interactions. We discuss biochemical methods such as protein affinity chromatography, affinity blotting, coimmunoprecipitation, and cross-linking; molecular biological methods such as protein probing, the two-hybrid system, and phage display: and genetic methods such as the isolation of extragenic suppressors, synthetic mutants, and unlinked non complementing mutants. This book describes how binding affinities can be evaluated by techniques including protein affinity chromatography, sedimentation, gel filtration, fluorescence methods, solid-phase sampling of equilibrium solutions, and surface plasmon resonance. Protein-protein interactions (PPIs) handle a wide range of biological processes, including cell-to-cell interactions and metabolic and developmental control. Protein-protein interaction is becoming one of the major objectives of system biology. Noncovalent contacts between the residue side chains are the basis for protein folding, protein assembly, and PPI. These contacts induce a variety of interactions and associations among the proteins. Based on their contrasting structural and functional characteristics, PPIs can be classified in several ways. On the basis of their interaction surface, they may be homo- or heterooligomeric; as judged by their stability, they may be obligate or nonobligate; as measured by their persistence, they may be transient or permanent. A given PPI may be a combination of these three specific pairs. The transient interactions would form signaling pathways while permanent interactions will form a stable protein complex. Uncovering protein-protein interaction information helps in the identification of drug targets. Studies have shown that proteins with larger number of interactions (hubs) can include families of enzymes, transcription factors, and intrinsically disordered proteins, among others. However, PPIs involve more heterogeneous processes and the scope of their regulation is large. For more accurate understanding of their importance in the cell, one has to identify various interactions and determine the aftermath of the interactions. In recent years, PPI data have been enhanced by guaranteed high-throughput experimental methods, such as two-hybrid systems, mass spectrometry, phage display, and protein chip technology. Comprehensive PPI networks have been built from these experimental resources. However, the voluminous nature of PPI data is imposing a challenge to laboratory validation. Computational analysis of PPI networks is increasingly becoming a mandatory tool to understand the functions of unexplored proteins. At present, protein-protein interaction (PPI) is one of the key topics for the development and progress of modern system's biology. There are many methods to investigate protein-protein interactions. Each of the approaches has its own strengths and weaknesses, especially with regard to the sensitivity and specificity of the method. A high sensitivity means that many of the interactions that occur in reality are detected by the screen. A high specificity indicates that most of the interactions detected by the screen are occurring in reality. Protein-protein interaction plays key role in predicting the protein function of target protein and drug ability of molecules. The majority of genes and proteins realize resulting phenotype functions as a set of interactions. The in vitro and in vivo methods like affinity purification, Y2H (yeast 2 hybrid), TAP (tandem affinity purification), and so forth have their own limitations like cost, time, and so forth, and the resultant data sets are noisy and have more false positives to annotate the function of drug molecules. Thus, in silico methods which include sequence-based approaches, structure-
