Special Protein Molecules Computational Identification

This book is a printed edition of the Special Issue "Special Protein Molecules Computational Identification" that was published in IJMS

Special Protein Molecules Computational Identification.

Proteins are large and intricate molecules that perform a variety of vital functions in the human body. They are crucial for the structure, control and function of the body's organs and tissues, while carrying out the majority of the work inside the cells. They are composed of a large number of smaller components known as amino acids that are linked with each other in lengthy chains. The search for novel protein molecules can be time consuming in case of certain proteins, such as enzymes, anticancer peptides, cytokines, G protein-coupled receptors, cell-penetrating peptides and cancerlectins. Understanding the function of proteins requires the computational identification of special protein molecules. Bioinformatics is a vital part of protein analysis, including structure analysis, sequence analysis and evolution analysis. This book contains some path-breaking studies on proteins. It aims to shed light on the computational approaches and bioinformatics analysis of proteins. As this field is emerging at a rapid pace, the contents of this book will help the readers understand the modern concepts and applications of the subject.

This work covers the impact of computational structural biology on protein structure prediction methods, macromolecular function and protein design, and key methods in drug discovery. It also addresses the computational challenges of experimental approaches in structural biology.

This book is indexed in Chemical Abstracts ServiceThe interactions of proteins with other molecules are important in many cellular activities. Investigations have been carried out to understand the recognition mechanism, identify the binding sites, analyze the the binding affinity of complexes, and study the influence of mutations on diseases. Protein interactions are also crucial in structure-based drug design.This book covers computational analysis of protein-protein, protein-nucleic acid and protein-ligand interactions and their applications. It provides up-to-date information and the latest developments from experts in the field, using illustrations to explain the key concepts and applications. This volume can serve as a single source on comparative studies of proteins interacting with proteins/DNAs/RNAs/carbohydrates and small molecules.

A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology. Providing a broad coverage of the field, the authors cover fundamental and technical information on these techniques and approaches, as well as discussing their related problems. The text consists of twenty nine chapters, organized into seven parts: Pattern Recognition in Sequences, Pattern Recognition in Secondary Structures, Pattern Recognition in Tertiary Structures, Pattern Recognition in Quaternary Structures, Pattern Recognition in Microarrays, Pattern Recognition in Phylogenetic Trees, and Pattern Recognition in Biological Networks. Surveys the development of techniques and approaches on pattern recognition in biomolecular data Discusses pattern recognition in primary, secondary, tertiary and quaternary structures, as well as microarrays, phylogenetic trees and biological networks Includes case studies and examples to further illustrate the concepts discussed in the book Pattern Recognition in Computational Molecular Biology: Techniques and Approaches is a reference for practitioners and professional researches in Computer Science, Life Science, and Mathematics. This book also serves as a supplementary reading for graduate students and young researches interested in Computational Molecular Biology.

This text offers in-depth perspectives on every aspect of protein structure identification, assessment, characterization, and utilization, for a clear understanding of the diversity of protein shapes, variations in protein function, and structure-based drug design. The authors cover numerous high-throughput technologies as well as computational methods to study protein structures and residues. A valuable reference, this book reflects current trends in the effort to solve new structures arising from genome initiatives, details methods to detect and identify errors in the prediction of protein structural models, and outlines challenges in the conversion of routine processes into high-throughput platforms.