Bioinformatics techniques for drug discovery applications for complex diseases / Aman Chandra Kaushik, Ajay Kumar, Shiv Bharadwaj, Ravi Chaudhary, Shakti Sahi.

Author/creator Kaushik, Aman Chandra
Format Electronic
Publication InfoCham, Switzerland : Springer, [2018]
Descriptionxi, 57 pages : illustrations ; 24 cm
Supplemental ContentFull text available from Springer Books
Supplemental ContentFull text available from Springer Nature - Springer Computer Science eBooks 2018 English International
Subjects
Drug Discovery
Computational Biology--methods.

Other author/creatorKumar, Ajay (Mechanical engineer)
Other author/creatorBharadwaj, Shiv.
Other author/creatorChaudhary, Ravi.
Other author/creatorSahi, Shakti.
SeriesSpringerBriefs in computer science, 2191-5768
SpringerBriefs in computer science. 2191-5768
Contents Intro; Preface; Contents; About the Authors; 1 Brief Introduction; 1.1 Brief Evolutionary History of In Silico Approaches; 1.2 Computational Drug Discovery and Design; 1.3 Epigenetics: Beyond the Sequence; 1.4 Histones Modification; References; 2 Ligand-Based Approach for In-silico Drug Designing; 2.1 Introduction; 2.2 Molecular Descriptors; 2.2.1 2D QSAR Descriptors; 2.2.2 3D QSAR Descriptors; 2.2.3 Multidimensional QSAR; 2.3 Constitutional Descriptors; 2.4 Quantitative Structure-Activity Relationships; 2.5 Molecular Fingerprint and Similarity Searches; 2.6 Similarity Searches in LB-CADD.
Contents 2.7 Similarity Networks and off Target Predictions2.8 Fingerprint Extensions; 2.9 Computational Methods for Biomolecular Docking; References; 3 Structure-Based Approach for In-silico Drug Designing; 3.1 Introduction; 3.2 Protein Docking; 3.2.1 Protein-Protein Docking; 3.2.2 Protein-Ligand Docking; References; 4 Three-Dimensional (3D) Pharmacophore Modelling-Based Drug Designing by Computational Technique; 4.1 Introduction; 4.1.1 Pharmacophore Model; References; 5 Molecular Dynamics Simulation Approach to Investigate Dynamic Behaviour of System Through the Application of Newtonian Mechanics.
Contents 5.1 Introduction5.2 Molecular Dynamics Simulations; 5.3 Monte Carlo Research with Metropolis Criterion; References; 6 Receptor Thermodynamics of Ligand-Receptor or Ligand-Enzyme Association; 6.1 Introduction; 6.2 Database Searching; 6.2.1 De Novo Drug Design; 6.3 State-of-the-Art Free Energy Calculations; References; 7 Thermodynamic Cycles and Their Application in Protein Targets; 7.1 Introduction; 7.2 Protein Targets and Applications; 7.3 4-Hydroxyphenylpyruvate Dioxygenase (HPPD); 7.4 Oligopeptide-Binding Protein a (OppA); References; 8 Genomics and Proteomics Using Computational Biology.
Contents 8.1 Introduction8.2 Peptide Identification; 8.3 De Novo and Hybrid Algorithms; 8.4 Sequence Database Search Algorithms; 8.5 Scoring of Peptide Identifications; 8.6 Peptide-Spectrum Match Scores and Common Thresholds; 8.7 Fundamentals of Gene Transcription and Translation; 8.8 Genome Sequencing; 8.9 Definition of Genome Annotation; 8.10 Genome Annotation Strategies; 8.11 Proteogenomics; References.
Abstract The application of bioinformatics approaches in drug design involves an interdisciplinary array of sophisticated techniques and software tools to elucidate hidden or complex biological data. This work reviews the latest bioinformatics approaches used for drug discovery. The text covers ligand-based and structure-based approaches for computer-aided drug design, 3D pharmacophore modeling, molecular dynamics simulation, the thermodynamics of ligand-receptor and ligand-enzyme association, thermodynamic characterization and optimization, and techniques for computational genomics and proteomics.
Bibliography noteIncludes bibliographical references.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2018932352
ISBN9783319757315 (alk. paper)
ISBN3319757318 (alk. paper)
ISBN(electronic bk.)
ISBN(electronic bk.)

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