00000cam a22000004i 4500 UP-99796217611709748 Buklod 20150814110944.0 a r |||| u| ta 150814s2014 xx d r |||| u| 9780128001684 (iLib)UPD-00247608011 DLC DSCI rda eng QP 551 A383 2014 Advances in protein chemistry and structural biology edited by Rossen Donev. Oxford, England Academic Press [2014] xi, 471 pages 24 cm text rdacontent unmediated rdamedia volume rdacarrier Front Cover; Advances in Protein Chemistry and Structural Biology; Copyright; Contents; Contributors; Chapter One: Bioinformatics Tools to Identify and Quantify Proteins Using Mass Spectrometry Data; 1. Introduction; 2. MS Data; 2.1. How MS generates data; 2.2. Tandem MS; 2.3. MS quantification techniques; 3. Protein Identification; 3.1. Bioinformatics tools for peptide identification; 3.1.1. De novo approach; 3.1.2. Database-searching approach; 3.1.3. Other approaches; 3.2. Bioinformatics tools for protein identification; 4. Protein Quantification; 4.1. Bioinformatics tools for ICAT data. 4.2. Bioinformatics tools for label-free data5. Conclusion; Acknowledgments; References; Chapter Two: Unraveling Oxidation-Induced Modifications in Proteins by Proteomics; 1. A Very Brief Introduction to Oxidative Stress and Redox Homeostasis; 2. Proteins as Targets of Oxidative Modification; 2.1. S-nitroso modifications of proteins; 2.2. Carbonylation; 2.3. Cysteine/disulfide oxidation: Cysteine-thiol chemistry and eletrophilic stress; 3. Redox Proteomics: The Comprehensive Study of Oxidation-Induced Protein Damage; 3.1. Technologies for redox proteomics screening. 3.1.1. Analysis of protein carbonylation/4-HNE adducts by MS3.1.2. Proteomics targeting the global thiol-cysteine state; 3.1.3. Nitrosoproteome approach for identifying S-nitrosoproteins; 4. The Use of Proteomics for Mapping the Redox Homeostasis Network: Lessons from Cancer Research; 5. Perspectives and Conclusions; References; Chapter Three: Role of Proteomics in Biomarker Discovery: Prognosis and Diagnosis of Neuropsychiatric Disorders; 1. Summary; 2. Commonly Used Methods for Proteome Characterization; 2.1. Two-dimensional gel electrophoresis and liquid chromatography. 2.2. Electrospray ionization, matrix-assisted laser desorption/ionization and surface-enhanced laser desorption/ionization2.3. In vitro chemical labeling; 2.3.1. Isotope-coded affinity tag; 2.3.2. Isobaric tag for relative and absolute quantitation; 2.4. In vivo metabolic labeling; 2.4.1. Stable isotope labeling with amino acids in cell culture; 2.4.2. 15N metabolic labeling; 3. Proteomics and Biomarker; 3.1. Peptide as biomarkers; 3.2. Posttranslational modifications as biomarkers; 4. Diagnosis of Neuropsychiatric Disorders; 4.1. Anxiety and depression; 4.2. Bipolar disorder. 4.3. Schizophrenia4.4. Alzheimer ́s disease; 5. Proteomics of Neuropsychiatric Disorders; 5.1. Depression and anxiety; 5.2. Schizophrenia; 5.3. Alzheimer disease; 5.4. Bipolar disorder; 6. Strength, Weakness, and Future Challenges: Biomarker Discovery; 7. Concluding Remarks; References; Chapter Four: On the Use of Knowledge-Based Potentials for the Evaluation of Models of Protein-Protein, Protein-DNA, and P ... ; 1. Introduction; 2. Knowledge-Based Potentials; 2.1. Split-statistical potentials; 3. Modeling of Protein Interactions Using Templates; 3.1. Models of binary complexes. Proteins Structure. Biochemistry. Proteins. Donev, Rossen editor. FO UPD DIMBB QP 551 A383 2014 Book