Cover -- RIVER PUBLISHERS SERIES IN RESEARCHAND BUSINESS CHRONICLES: BIOTECHNOLOGYAND MEDICINE -- Title Page -- Copyright -- Contents -- Series Note -- Preface -- Acknowledgements -- List of Figures -- List of Tables -- 1. Drug Discovery: Diseases, Drugs and Targets -- 1.1 Introduction -- 1.2 Drug Discovery -- 1.2.1 Phase 1 Clinical Trial: Perform initial human testing in a small group of healthy volunteers -- 1.2.2 Phase 2 Clinical Trial:Test in a small group of patients -- 1.2.3 Phase 3 Clinical Trial:Test in a large group of patients to show safety and efficacy -- 1.3 Drug and Targets -- 1.3.1 Drugs/target and Targets/drug -- 1.4 Disease Genes - Targets and Drugs -- 1.5 Conclusions -- References -- 2. Target Identification and Validation in Microbial Genomes -- 2.1 Introduction -- 2.2 Strategies for Target Identification in Silico -- 2.2.1 Essential genes -- 2.2.2 Conserved genes -- 2.2.3 Disordered proteins -- 2.2.4 Load point & Choke points, and FBA -- 2.2.5 Virulence proteins -- 2.2.6 In vitro experiments -- 2.2.7 Overlapping genes/proteins -- 2.2.8 Fusion proteins -- 2.2.9 Hub proteins and networks -- 2.2.10 Membrane proteins, uncharcterised essential genes, species specific genes as targets -- 2.2.11 Structural genomics -- 2.2.12 Selectivity -- 2.2.13 Target prioritization in completely sequenced Pseudomonas aeruginosa genomes -- 2.2.14 Genomes/Conserved proteins/Non-human homologs -- 2.2.15 Disordered regions and Virulent factors -- 2.2.16 Identification of unique enzymes in unique and shared pathways -- 2.2.17 Comparison of unique enzymes to essential gene data -- 2.2.18 Choke points -- 2.2.19 FBA -- 2.2.20 Mutagenesis -- 2.3 Conclusions -- References -- 3. A Prioritization Analysis of Disease Association by Data-mining of Functional Annotation of Human Genes -- 3.1 Introduction -- 3.1.1 Genetics underlying disease.

3.1.2 The era of genomics -- 3.1.3 Genes and their function -- 3.1.4 Disease gene prioritization -- 3.1.5 Beyond genes - functional annotation of the entire genome -- 3.2 Definition of a Gene -- 3.3 Data-Mining Functional Annotation -- 3.4 Experimental Sources of Functional Annotation -- 3.5 Inferred Functional Annotation Through Sequence Similarity -- 3.6 High Throughput Candidate Disease Gene Prioritization Through Semantic Discovery -- 3.6.1 The BioOntological Relationship Graph (BORG) Semantic Database -- 3.6.2 Mining the BORG Database Through Semantic Querying -- 3.6.2.1 Ontology seeded queries -- 3.6.2.2 Annotation retrieval -- 3.6.2.3 Path-based transitive association queries -- 3.7 Conclusions -- References -- 4. Genomics-Guided Discovery of Novel Therapeutics of Actinobacterial Origin -- 4.1 Introduction -- 4.2 Alternative Culturing Methodologies for Diversification of Microbial Natural Products -- 4.2.1 Exploring naive ecosystems for sample collections -- 4.2.2 Acknowledging significance of microbial symbiosis -- 4.2.3 Culture independent sampling approaches -- 4.2.4 Manipulating culture conditions for maximizing natural product biosynthesis by cultured microorganisms -- 4.2.5 Microbial co-culturing for improved synthesis of natural products -- 4.3 Genetics/Genomics-Guided-Approaches for Diversification of Microbial Natural Products -- 4.3.1 Hetrologous expression of environmental DNA -- 4.3.2 Whole genome sequencing and data mining -- 4.3.3 Genome scanning with genome sequence tags -- 4.3.4 Homology-guided metagenomic screening -- 4.3.5 Genomics-guided induction of cryptic gene clusters -- 4.3.5.1 Ribosome engineering -- 4.3.5.2 Modulating dasR activity -- 4.3.6 Genomics-guided combinatorial biosynthesis of novel microbial natural products -- 4.4 Conclusions -- References -- 5. Chemogenomics Approach to Computer Aided Drug Discovery.

5.1 Introduction -- 5.2 Description of Protein Ligand Spaces -- 5.2.1 Protein space -- 5.2.2 Ligand space -- 5.3 Applications -- 5.3.1 Target fishing -- 5.3.1.1 Similarity searching in chemical databases -- 5.3.1.2 Data-mining in annotated databases -- 5.3.1.3 Molecular docking -- 5.3.2 Prediction of The Bioprofiles of Drugs -- 5.3.3 Drug Repurposing -- 5.4 Conclusions -- References -- 6. Network Biology Methods for Drug Repositioning -- 6.1 Introduction -- 6.2 Principles of Drug Repositioning Strategies -- 6.2.1 Screening of Related but Heterogeneous Knowledgebases -- 6.2.2 Pharmacopeia Scanning -- 6.2.3 Phenotype-centric Screening -- 6.3 Computational Network Approaches for Drug Repositioning -- 6.4 Network Analysis Concepts -- 6.4.1 Measures of Node Centrality -- 6.4.1.1 Degree -- 6.4.1.2 Betweenness centrality -- 6.4.1.3 Closeness centrality -- 6.4.1.4 Eigenvector centrality -- 6.4.2 Shortest Path Length -- 6.4.3 Network Clustering Coefficient -- 6.4.4 Network Density -- 6.4.5 Sub-networks, Modules and Communities -- 6.5 Network Biomedicine -- 6.5.1 Case Studies -- 6.5.1.1 Mantra: mode of action by network analysis -- 6.5.1.2 Disease profiles and protein interactions mining -- 6.5.1.3 Heterogeneous network clustering -- 6.6 Conclusions -- References -- 7. Hypothesis Driven Multi-target Drug Design -- 7.1 Introduction -- 7.1.1 Molecular docking -- 7.1.1.1 Docking of proposed hybrid compounds at the ATP binding sites of GyrB/ParE -- 7.1.1.2 Docking of proposed hybrid compounds at the pterin binding site of DHPS -- 7.1.1.3 Docking of proposed hybrid compounds at the folate binding site of DHFR -- 7.1.2 Molecular dynamics simulations -- 7.2 Electronic Property Analyses of all the Designed Hybrid Compounds -- 7.3 In Silico Calculations of Physico-Chemical, Drug-Likeness and Toxicity Risk Analyses -- 7.4 Conclusions -- References.

8. Genomics in Vaccine Development -- 8.1 Introduction -- 8.2 Genomics in Vaccine Development -- 8.2.1 Characterization of Pathogens -- 8.2.2 Characterization of the Host Immune System -- 8.2.2.1 Personalized vaccines -- 8.3 Application -- 8.3.1 Host Diversity Characterization -- 8.3.2 Pathogen Diversity Characterization -- 8.3.3 Vaccine Target Prediction -- 8.3.3.1 T-cell epitopes -- 8.3.3.2 B-cell epitopes -- 8.3.4 Selection of Vaccine Targets -- 8.4 Reverse Vaccinology Pipeline for Viral Pathogens -- 8.4.1 Step 1: Pathogen and Host Characterization -- 8.4.2 Step 2: Cataloguing Potential Antigen -- 8.4.3 Step 3: Identification of Potential T-cell Epitopes -- 8.4.4 Step 4: Epitope Conservation Analysis -- 8.4.5 Step 5:Validation -- 8.5 Conclusions -- References -- 9. Toward the Computer-aided Discovery and Design of Epitope Ensemble Vaccines -- 9.1 Exordium -- 9.2 The Informatics of Epitology -- 9.3 Epitope Vaccines: Current Status -- 9.3.1 Alzheimer's Disease -- 9.3.2 HIV -- 9.3.3 Malaria -- 9.3.4 Cancer -- 9.3.5 Influenza -- 9.4 The in Silico Design of Epitope Ensemble Vaccines: A Critique -- 9.5 Conclusions -- References -- 10. Vaccine Discovery and Translation of New Vaccine Technology -- 10.1 Introduction -- 10.2 Classical Vaccinology Approaches -- 10.2.1 Live Attenuated and Inactivated Whole Organism Vaccines -- 10.2.2 "Subunit" and "extract" vaccine -- 10.3 Identification of New Vaccine Candidates through Innovative Genome Based Technologies -- 10.3.1 Reverse Vaccinology -- 10.3.2 Pan-genomic reverse vaccinology approach -- 10.3.3 Functional Genomics Approaches in Vaccine Development -- 10.4 Rational Design of Novel Vaccine Antigens Based on Integrated Genomic and Structural Information -- 10.4.1 Design of Chimeric Vaccine Components -- 10.4.2 Structural Vaccinology Approach to Design Novel Antigens -- 10.5 Conclusion and Future Perspectives.

References -- 11. Outer Membrane Proteins as Potential Candidate Vaccine Targets -- 11.1 Introduction -- 11.1.1 Outer Membrane Proteins -- 11.1.1.1 Lipoproteins -- 11.1.1.2 Integral membrane proteins -- 11.1.2 OM lipids -- 11.1.2.1 Phospholipids -- 11.1.2.2 Lipopolysaccharides (LPS) -- 11.1.3 OMP Biogenesis and Assembly -- 11.1.4 Lipoprotein Transport -- 11.2 Evaluation of Outer Membrane Proteins as Vaccine Candidates -- 11.2.1 OMP in Bacterial Pathogenesis and Virulence -- 11.2.2 Vaccines Against Intracellular and Extracellular Bacteria - Induction of Different Types of Protective Immunity -- 11.2.3 Leptospirosis -- 11.2.4 Porphyromonas gingivalis -- 11.2.5 Pseudomonas aeruginosa -- 11.2.6 Burkholderia pseudomallei -- 11.2.7 Neiserria meningitidis -- 11.2.8 Haemophilus influenzae -- 11.2.9 Ehrlichiosis -- 11.2.10 Brucella -- 11.3 Genomics and Functional Genomics in OMP-Based Vaccine Development -- 11.4 Conclusions -- References -- 12. Systems Biology Approaches to New Vaccine Development -- 12.1 Introduction -- 12.2 Systems Biology for Vaccine Development -- 12.2.1 Integration of Biological Data -- 12.2.2 Prediction of Vaccine Efficacy -- 12.2.3 Identification of Novel Immune Regulation Mechanisms -- 12.3 Technologies -- 12.3.1 Genomics -- 12.3.2 Proteomics -- 12.3.3 Bioinformatics -- 12.3.3.1 Databases -- 12.3.3.2 Tools -- 12.3.3.3 Computational models -- 12.4 Challenges -- 12.5 Examples -- 12.5.1 Yellow Fever Vaccine YF-17D -- 12.5.2 Seasonal Influenza Vaccine -- 12.5.3 Tuberculosis Vaccine -- 12.6 Conclusions -- References -- 13. Inhibition of Virulence Potential of Vibrio Cholerae by Herbal Compounds -- 13.1 Introduction -- 13.2 Microbiology of Vibrio Cheolrae -- 13.2.1 Mechanism of Infection -- 13.3 Global Status of Cholera -- 13.4 Introduction -- 13.4.1 Cholera Toxin -- 13.4.1.1 Structure and function -- 13.4.2 Toxin coregulated pilus (TCP).

13.4.3 Adhesin Factors (Accessory Colonization Factors).