Therapeutic Protein Targets for Drug Discovery and Clinical Evaluation: Bio-crystallography and Drug Design

Contents
Preface
Acknowledgments
Foreword
1 Structural and Functional Aspects of the Macrolide Efflux Transporter, MacB — A Tripartite ABC Transporter
1. Introduction
1.1. Tripartite Efflux Transporter
1.2. ABC Transporter
2. Substrates of MacAB-TolC System
3. Structure
3.1. Crystal Structure of MacB
3.2. Cryo-EM Structure of MacAB-TolC Tripartite Complex
3.3. Structural Comparison Between MacB Structures
4. Molecular Mechanism of Substrate Translocation
Appendix Measurement of MIC
References
2 Pro-inflammatory Secretory Phospholipase A2 Enzyme: Evaluation of Hydrophobic and Antioxidant Properties of Inhibitors
1. Introduction
2. Structure of sPLA2 Enzyme
3. Catalytic Mechanism
4. sPLA2 Enzyme Assay
5. sPLA2s as Mediators of Inflammation
6. Hydrophobic sPLA2 Inhibitors with Antioxidant Activity as Anti-inflammatory Molecules
Acknowledgments
References
3 Exploring the Shock and Kill Strategy to Eradicate Latent HIV-1 Infection
1. Introduction
2. Molecular Basis of Understanding the Shock and Kill Approach
3. Shock and Kill Strategy
4. HIV-1 TAT Protein
4.1. Structural Features and Functions
4.2. TAT-mediated HIV-1 transcription
5. LRAs
5.1. Histone Post-translational Modification Modulators
5.2. Non-histone Chromatin Modulators
5.3. NF-κB Stimulators
5.4. TLR Agonists
5.5. Extracellular Stimulators
5.6. Miscellaneous
6. Concluding Remarks
Acknowledgment
References
4 Therapeutic Target Identification and Evaluation using Machine Learning
1. Introduction
2. Brief Background to Machine Learning and Deep Learning
3. ML in Drug Target Identification
4. ML in Protein Structure Modeling
5. ML in Protein Binding Site Discovery
6. Challenges
7. Conclusion and Future Direction
References
5 Proteases as Therapeutic Targets: A Structural Biology Perspective
1. Introduction
1.1. Protease Substrate Specificity
2. Role of Different Proteases in Host–pathogen Interaction
2.1. Human Proteases
2.2. Plant Proteases
2.3. Bacterial Proteases
2.4. Viral Proteases
3. Importance of Protease Inhibitors
4. Protease–protease Inhibitor Interactions
4.1. Cell Envelop Proteinases (ScpC-AEBSF)
4.2. Human Neutrophil Elastase — Ecotin
4.3. Thrombin–CrSPI
4.4. Subtilisin–CrSPI (Domains 1 and 2)
5. Summary
References
6 In silico Approaches for Understanding Antimicrobial Resistance in Bacterial Pathogens
1. Introduction
2. Mechanism of Action of Antibiotics
3. In silico Techniques to Understand the Mechanism of AMR
3.1. Computing Non-covalent Interactions
3.1.1. Cation–π interactions
3.1.2. Non-conventional interactions (C–H···π interactions, N–H···π interactions, C–H···O interactions)
3.2. Computing Environmental Preferences
3.2.1. Secondary structure
3.2.2. Solvent accessibility
3.2.3. Inter-residue contacts
3.2.4. Conservation patterns
3.2.5. Stabilization centers
3.3. Computational Modeling
3.3.1. Template identification and sequence homology
3.3.2. Model building
3.3.3. Refinement modeling
3.3.4. Loop modeling
3.3.5. Side chain modeling
3.3.6. Model validation
3.4. Molecular Docking
3.5. Virtual Screening
3.6. Pharmacophore Modeling
3.7. Molecular Dynamics
3.8. QSAR Studies
3.9. Systems Biology Approaches
4. Revealing the Mechanism of AMR by in silico Methods: Classical Examples
4.1. Penicillin-binding Proteins and β-lactamases
4.2. ampC
4.3. Metallo-β-lactamase
4.4. OXA β-lactamase
4.5. Carbapenamase
4.6. Enterococcus Faecalis
4.7. Staphylococcus Aureus
4.8. Klebsiella Pneumoniae
4.9. Mycobacterium Tuberculosis
4.10. Pseudomonas Aeruginosa
4.11. Salmonella Enterica Serovar Typhi
5. In silico Approaches to Design Antiviral Compounds
5.1. Dengue Viruses
5.2. Hepatitis C Virus
5.3. SARS-CoV-2 (Novel Corona Virus)
6. In silico Approaches to Design Anti-Plasmodium Falciparum Compounds
7. Conclusion
Acknowledgments
Funding Statement
References
7 An Integrative Approach to Explore Potent Therapeutic Protein Targets in Multidrug-resistant Nosocomial Pathogen Acinetobacter Baumannii
1. Introduction
2. Protein Crystallography in Structural Analysis of Therapeutic Targets in Acinetobacter baumannii
2.1. Molecular Recognition of Protein and Structure-based Drug Discovery
2.2. Mechanism of Action and Catalysis of Enzymes
2.3. Relating 3D Protein Structure to Thermodynamics of Ligand Binding
3. In vitro and in vivo Functional and Molecular Characterization of Drug Targets in Acinetobacter Baumannii
3.1. Proteomic Profiling of Biofilm-associated Protein Targets
3.2. Proteomic Analysis of QS-dependent Proteins
3.3. Characterization of Virulence and Drug-resistance-Associated Proteins
4. Computational Multi-omics Approach Toward Identification of Drug Targets in Acinetobacter Baumannii
4.1. Comparative Proteomic and Subtractive Genomic Analysis to Identify Drug Targets
5. Other Possible Drug Targets Involved in Metabolic Pathways of Acinetobacter Baumannii
6. Conclusion
6.1. Summary
Acknowledgment
References
8 Peptides as Antiviral Drugs
1. Introduction
2. Mode of Action of Peptides Against Viruses
3. Techniques for Identification and Verification of Antiviral Peptides
3.1. Computational Approach
3.2. Biological Approach
3.3. Advanced Approach
4. AMPs
5. Action of Peptides Against Specific Viruses
5.1. Plant Peptide Against Herpes Simplex Virus
5.2. Plant Peptide Against Junin Virus
5.3. Plant Peptide Against Foot and Mouth Disease Virus
5.4. Plant Peptide Against HIV
5.5. Plant Peptide Against Poliovirus
6. Antiviral Peptides from Sources other than Plants
6.1. Bacterial Source
6.2. Algal Source
6.3. Fungal Source
6.4. Animal Source
7. Peptides Against SARS-CoV
8. Bioinformatics Studies on Antiviral Peptides
9. Cryptides
10. Conclusion
References
9 Designing a Multi-epitope Peptide-based Vaccine for Human Influenza A/H1N1Virus — An Immuno informatics Approach
1. Introduction
2. Materials and Methods
2.1. Sequence Retrieval
2.2. Prediction of Physiochemical Properties, Antigenicity, Allergenicity and Secondary Structure
2.3. T-cell Epitope Prediction
2.3.1. Cytotoxic T-cell epitope prediction
2.3.1.1. Epitope conservancy and immunogenicity prediction
2.3.1.2. Allele selection
2.3.1.3. Comparison with IEDB database
2.3.2. Helper T-cell (HTL) epitope prediction
2.4. Population Coverage
2.5. Three-dimensional (3D) Structure Design of the Epitope
2.6. Molecular Interaction of the MHC and Epitopes
2.7. B-cell Epitope Prediction
2.7.1. Linear/continuous B-cell epitope prediction
2.7.2. Structure prediction, refinement and validation
2.7.3. Conformational/discontinuous B-cell epitope prediction
2.8. Interferon (IFN)-g-inducing Epitopes
2.9. Designing of MEVC
2.10. Structure Prediction, Validation and Docking with the Receptor
2.11. Population Coverage of MEVC
2.12. Immune Simulations of Vaccine Construct
3. Results and Discussion
3.1. Sequence Retrieval and Prediction of Physiochemical Properties
3.2. Antigenicity and AllergenicityPrediction of the antigenicity represents
3.3. T cell Prediction
3.3.1. Cytotoxic T-cell epitope prediction
3.3.1.1. Allele selection
3.3.1.2. Comparison with IEDB database
3.3.2. HTL epitope prediction
3.4. Population Coverage of RMNYYWTLV Epitope
3.5. 3D Structure Design of the RMNYYWTLV Epitope and its Molecular Interaction with MHC I and II
3.6. Linear/continuous B-cell Epitope Prediction
3.7. Secondary and Tertiary Structure Prediction, Refinement and Validation
3.8. Conformational/discontinuous B-cell Epitope Prediction
3.9. IFN-g-inducing Epitopes
3.10. Designing of MEVC
3.10.1. Physiochemical properties, antigenicity and allergenicity of MEVC
3.10.2. Secondary and tertiary structure prediction and validation
3.10.3. Docking of MEVC with receptors
3.11. Population Coverage of MEVC
3.12. Immune Simulations of Vaccine Construct
4. Conclusion
Acknowledgment
References
10 Identification of Potent Inhibitors from Some Medicinally Important Plants for the Treatment Against Various Types of Cancers
1. Introduction
2. Types of Cancer
2.1. Carcinoma
2.2. Sarcoma
2.3. Leukemia
2.4. Lymphoma
2.5. Myeloma
3. Role of Nanoparticles Against Cancer
4. Anticancer Compounds from Plants
4.1. Phytochemical Compounds Against Breast Cancer
4.2. Phytochemical Compounds Against Pancreatic Cancer — In vitro Cell Line Studies
4.3. Phytochemical Compounds Against Brain Cancer
4.4. Phytochemical Compounds Against Skin Cancer
4.5 Anticancer Compounds from Marine Plants
5. Targets for Anticancer Drug Design
6. Conclusion
References
11 Missense Mutations in Fumarate Hydratase Leading to Cancer: Molecular Modeling and Molecular Dynamics Simulations of the Mutants
1. Introduction
2. Materials and Methods
2.1. Target Preparation
2.2. MD Simulations
3. Results and Discussion
3.1. MD Simulations of Wild-type FH and Three Mutant Forms of FH
3.2. Conformational Stability Analysis of Wild-type and Mutant forms of FH
3.3. Distance Analysis of Active Site Stabilizing Residues
4. Conclusion
References
12 Analysis of the Secondary Metabolites of Indigofera Aspalathoides DC Oil to Control Various Human Ailments
1. Introduction
1.1. The Siddha System of Medicines
1.1.1. The concept of disease etiology in the Siddha system of medicines
1.1.2. Diagnosis in the Siddha system of medicines
1.1.3. Medication and preparation in the Siddha system of medicines
1.2. Sivanar Vembu Kuzhi Thailam
2. Materials and Methods
2.1. Sample Collection
2.2. GC-MS Analysis of Sivanar Vembu Kuzhi Thailam
2.3. LC-MS Analysis of Sivanar Vembu Kuzhi Thailam
3. Results
3.1. GC-MS Analysis of Sivanar Vembu Kuzhi Thailam
3.2. LC-MS Analysis of Sivanar Vembu Kuzhi Thailam
4. Discussion
4.1. Biological Activities of Compounds Identified from Sivanar Vembu Kuzhi Thailam
5. Conclusion
Acknowledgment
References
Index