This is now the fourth time that protein phosphorylation has been the focus of a NATO Advanced Study Institute. The first meeting with the topic "Signal Trans duction and Protein Phosphorylation" was held on the island of Spezai, Greece, in September 1986. The second one took place in Chateau La Londe, France, in September 1989 on "Cellular Regulation by Protein Phosphorylation", the third one on " Tyrosine Phosphorylation/Dephosphorylation and Downstream Signaling" was in September 1992 in Maratea, Italy. The titles of these books clearly mirror the developments that have taken place in the last decade. Beginning with the recognition that protein phosphorylation is at the center of signaling -clearly established in 1990 -it became apparent that many cellular processes are regulated by this mode. A new focus then emerged when it was recognized that growth factors are bound to corresponding receptors trigger protein tyrosine phosphorylation which controls cell prolifera tion. This was the topic of the third meeting in this series. It is now evident that further progress depends on understanding the three dimensional structure of the proteins involved. It goes without saying, for example, that understanding the location of proteins by adaptor proteins is only possible on the basis of the three dimensional protein structure. Therefore, the fourth meeting in this series concentrated on the protein structure of signaling molecules as well as on the elucidation of the principles of protein domain interactions.

Since the full functionality of any given protein can only be understood in terms of its interaction with other, often regulatory proteins, this unique reference source covers all relevant protein domains, including SH2, SH3, PDZ, WW, PTB, EH, PH and PX. Its user-oriented concept combines broad coverage with easy retrieval of essential information, and includes a special section on Web-based tools and databases covering protein modules and functional peptide motifs. Essential for the study of protein-protein interactions in vivo or in silico, and a prerequisite for successful functional proteomics studies. With a prologue by Sir Tom Blundell.

Since the first TRP ion channel was discovered in Drosophila melanogaster in 1989, the progress made in this area of signaling research has yielded findings that offer the potential to dramatically impact human health and wellness. Involved in gateway activity for all five of our senses, TRP channels have been shown to respond to a wide range of st

This book illustrates the importance and significance of the molecular (physical and chemical) and evolutionary (gene fusion) principles of protein-protein and domain-domain interactions towards the understanding of cell division, disease mechanism and target definition in drug discovery. It describes the complex issues associated with this phenomenon using cutting edge advancement in Bioinformatics and Bioinformation Discovery. The chapters provide current information pertaining to the types of protein-protein complexes (homodimers, heterodimers, multimer complexes) in context with various specific and sensitive biological functions. The significance of such complex formation in human biology in the light of molecular evolution is also highlighted using several examples. The chapters also describe recent advancements on the molecular principles of protein-protein interaction with reference to evolution towards target identification in drug discovery. Finally, the book also elucidates a comprehensive yet a representative description of a large number of challenges associated with the molecular interaction of proteins.

Biotechnology can be defined as the manipulation of biological process, systems, and organisms in the production of various products. With applications in a number of fields such as biomedical, chemical, mechanical, and civil engineering, research on the development of biologically inspired materials is essential to further advancement. Biotechnology: Concepts, Methodologies, Tools, and Applications is a vital reference source for the latest research findings on the application of biotechnology in medicine, engineering, agriculture, food production, and other areas. It also examines the economic impacts of biotechnology use. Highlighting a range of topics such as pharmacogenomics, biomedical engineering, and bioinformatics, this multi-volume book is ideally designed for engineers, pharmacists, medical professionals, practitioners, academicians, and researchers interested in the applications of biotechnology.

The biological interactions of living organisms, and protein-protein interactions in particular, are astonishingly diverse. This comprehensive book provides a broad, thorough and multidisciplinary coverage of its field. It integrates different approaches from bioinformatics, biochemistry, computational analysis and systems biology to offer the reader a comprehensive global view of the diverse data on protein-protein interactions and protein interaction networks.

Protein chains are generally long and consist of multiple domains. Domains are the basic elements of protein structures that can exist, evolve, and function independently. The accurate and reliable identification of protein domains and their interactions has very important impacts in several protein research areas. The accurate prediction of protein domains is a fundamental stage in both experimental and computational proteomics. The knowledge of domains is an initial stage of protein tertiary structure prediction which can give insight into the way in which proteins work. The knowledge of domains is also useful in classifying proteins, understanding their structures, functions and evolution, and predicting proteinprotein interactions (PPI). However, predicting structural domains within proteins is a challenging task in computational biology. A promising direction of domain prediction is detecting inter-domain linkers and then predicting the reigns of the protein sequence in which the structural domains are located accordingly. Protein-protein interactions occur at almost every level of cell function. The identification of interaction among proteins and their associated domains provide a global picture of cellular functions and biological processes. It is also an essential step in the construction of PPI networks for human and other organisms. PPI prediction has been considered as a promising alternative to the traditional drug design techniques. The identification of possible viral-host protein interactions can lead to a better understanding of infection mechanisms and, in turn, to the development of several medication drugs and treatment optimization. In this work, a compact and accurate approach for inter-domain linker prediction is developed based solely on protein primary structure information. Then, inter-domain linker knowledge is used in predicting structural domains and detecting PPI. The research work in this dissertation can be summarized in three main contributions. The first contribution is predicting protein inter-domain linker regions by introducing the concept of amino acid compositional index and refining the prediction by using the Simulated Annealing optimization technique. The second contribution is identifying structural domains based on inter-domain linker knowledge. The inter-domain linker knowledge, represented by the compositional index, is enhanced by the incorporation of biological knowledge, represented by amino acid physiochemical properties, to develop a well-optimized Random Forest classifier for predicting novel domains and inter-domain linkers. In the third contribution, the domain information knowledge is utilized to predict protein-protein interactions. This is achieved by characterizing structural domains within protein sequences, analyzing their interactions, and predicting protein interactions based on their interacting domains. The experimental studies and the higher accuracy achieved is a valid argument in favor of the proposed framework.

Often considered the workhorse of the cellular machinery, proteins are responsible for functions ranging from molecular motors to signaling. The broad recognition of their involvement in all cellular processes has led to focused efforts to predict their functions from sequences, and if available, from their structures. An overview of current resear