Polypharmacology: Principles and Methodologies

Description

There is a growing interest in unmet needs for the development of a new discipline in drug discovery and in university education on polypharmacology. However, there has not been a book with the comprehensive compilation of basic knowledge and advanced methodology that is needed. This book aims to meet the needs making Polypharmacology a new sub-discipline of Pharmacology, not only being a hot area of pharmacological research and education but also a new paradigm for drug discovery. It contains the contents covering the entire scope of Polypharmacology including systemic in-depth exposition of basic knowledge, novel concepts, innovative technologies, and translational and clinical applications by showcasing state-of-the-art strategies and step-by-step instructions of cutting-edge methods. The contents of this book targets broad readerships including scientists in pharmacology research and drug development, and university teachers and graduates in medical school or school of pharmacy. Preface Acknowledgement Contents About the Authors 1: Basics of Polypharmacology 1.1 The Concept and Definition of Polypharmacology 1.2 The Historical Account of Polypharmacology 1.2.1 Traditional Pharmacology: The “Natural Multicomponents Medicine” 1.2.2 Modern Pharmacology—Single-Target Drugs (STD): The “Single Agent on Single Target for Single Disease” Strategy 1.2.3 Modern Polypharmacology v1.0—Combination Drug Therapy (CDT): The “Multiple Agents on Multiple Targets for Single Disease” Strategy 1.2.4 Modern Polypharmacology v2.0—Fixed-Dose Combination (FDC): The “Single Pill with Multiple Agents on Multiple Targets for Single Disease” Strategy 1.2.5 Modern Polypharmacology v3.0—Multitarget Drugs (MTD): The “Single Agent on Multiple Targets for Single Disease” Strategy 1.2.6 Modern Polypharmacology v3.1—Multitarget Drugs (MTD): The “Single Agent on Multiple Targets for Multiple Diseases” Strategy (MTD-MD) 1.3 The Principles of Polypharmacology 1.3.1 Designed Multitargeticity Is the Core of Polypharmacology 1.3.2 Designed Polyspecificity Is the Essence of Polypharmacology 1.3.3 Polypharmacology Is Network-Based Pharmacology 1.3.4 Polypharmacology Is Constellation-Directed Pharmacology 1.3.5 Holistic and Integrative Approach Is the Future of Polypharmacology 1.4 The Mission and Task of Polypharmacology 1.4.1 Multitarget Drug Discovery—Rational Design of New Drugs 1.4.2 Drug Repurposing—Rediscovery of Old Drugs for New Uses 1.4.3 Identifying Drug Promiscuity—Predicting Off-Target Effects 1.4.4 Characterizing Drug Interactions 1.4.5 Elucidating Polypharmacodynamics and Polypharmacokinetics 1.4.6 Delineating Mechanisms of Action of Polypharmacological Therapeutics 1.5 Opportunities and Challenges of Polypharmacology 1.5.1 Improved Drug Efficacy 1.5.2 Enhanced Drug Potency 1.5.3 Increased Drug Safety 1.5.4 Targeting Complex Disorders 1.5.5 Mitigating Drug Resistance 1.6 Polypharmacology and Network Pharmacology 1.6.1 Network Construction and Pragmatic Network Model 1.6.2 Network Analysis and Visualization 1.6.3 Data Collection and Network Validation 1.7 Epigenetic Polypharmacology References 2: Strategies of Polypharmacology 2.1 CDT Strategy—The “Combination” Strategy 2.1.1 Concept of CDT 2.1.2 Basic Requirement for CDT 2.1.2.1 Multitargeting with Complementary Mechanisms 2.1.2.2 Nonoverlapping Toxicity 2.1.2.3 Pharmacokinetics Comparability or Physicochemical Compatibility 2.1.2.4 Minimizing the Number of Combining Drugs 2.1.3 Strengths of CDT 2.1.3.1 Minimizing Compensatory Effect Due to Redundancies in Signaling Networks 2.1.3.2 Creating Synergistic Actions 2.1.3.3 Combination of Infinite Number of Therapeutical Agents 2.1.3.4 Multiple Options of Combination 2.1.3.5 Offering the Possibility of Personalized Treatment 2.1.3.6 Minimizing Drug Toxicity or Side Effects 2.1.3.7 Mitigating Drug Resistance 2.1.4 Limitations of CDT 2.1.4.1 Poor Patient Compliance 2.1.4.2 Possible Different Bioavailability 2.1.4.3 Disturbing Drug Interactions 2.1.4.4 Complicating Drug Development Process 2.1.4.5 Lengthening Drug Approval Procedure 2.1.5 Types of CDT 2.1.5.1 Classification Based on Chronological Order of Drug Administration 2.1.5.2 Classification Based on the Design of Drug Combination 2.1.5.3 Classification Based on the Number of Combining Drugs 2.2 FDC Strategy—The “Admixture” Strategy 2.2.1 Concept of FDC 2.2.2 Basic Requirement for FDC 2.2.3 Strengths of FDC 2.2.3.1 Improved Medication Compliance 2.2.3.2 Greater Disease Control 2.2.3.3 Better Tolerability and Safety 2.2.3.4 Increased Cost-Effectiveness 2.2.3.5 Simplifying Drug Regimes 2.2.4 Limitations of FDC 2.2.4.1 Difficulty in Titration of Doses 2.2.4.2 Impact of Drug Intolerance and Side Effects 2.2.4.3 Undesirable Drug Interactions 2.2.4.4 Incompatible Pharmacokinetics 2.2.4.5 Physician Acceptability 2.2.4.6 Pharmaceutical/Formulation Issues 2.2.5 Types of FDC 2.2.5.1 Rationally Designed FDC 2.2.5.2 Partly Designed FDC 2.3 MTD Strategy—The “Integration” Strategy 2.3.1 Concept of MTD 2.3.2 Basic Requirement for MTD 2.3.2.1 Choosing the Right Combination of Targets 2.3.2.2 Balancing Activities Toward Targets 2.3.2.3 Excluding Undesired Targets 2.3.3 Strengths of MTD 2.3.3.1 Optimized Therapeutic Efficacy and Improved Safety Profile 2.3.3.2 Lack of Drug Interactions 2.3.3.3 Predictable Pharmacokinetics 2.3.3.4 Less Prone to Drug Resistance 2.3.3.5 Simplified Therapeutic Regimens 2.3.3.6 Simplified Regulatory Requirements 2.3.3.7 Providing Unprecedented Opportunities for Drug Discovery 2.3.4 Limitations of MTD 2.3.4.1 Challenges of Validating Target Combinations 2.3.4.2 Difficulties in Optimizing Multiple Structure-Activity Relationships 2.3.4.3 Requiring More Advanced Technologies 2.3.5 Types of MTD 2.3.5.1 Classification Based on the Design of Drugs 2.3.5.2 Classification Based on the Disease Pathway 2.3.5.3 Classification Based on the Origins of Drugs 2.3.5.4 Classification Based on the Mechanisms of Action 2.3.5.5 Classification Based on Approaches of Drug Discovery References 3: Polypharmacology in Clinical Applications—Anticancer Polypharmacology 3.1 Pharmacological Therapy of Cancer 3.1.1 Chemotherapeutic Agents 3.1.1.1 DNA Alkylating Agents 3.1.1.2 Antimetabolites 3.1.1.3 Antimitotic Drugs 3.1.1.4 Topoisomerase Inhibitors 3.1.1.5 Monoclonal Antibody Drugs—Targeted Cancer Therapy 3.1.1.6 Mitotic Inhibitors 3.1.1.7 Protein Kinase Inhibitors 3.1.2 Hormone Therapy/Endocrine Therapy (ET) 3.1.2.1 Breast Cancer 3.1.2.2 Prostate Cancer 3.1.2.3 Endometrial Cancer 3.1.2.4 Adrenal Cancer 3.1.3 Immunological Agents 3.1.4 Targeted Cancer Therapies 3.1.4.1 Hormone Therapies 3.1.4.2 Signal Transduction Inhibitors 3.1.4.3 Gene Expression Modulators 3.1.4.4 Apoptosis Inducers 3.1.4.5 Angiogenesis Inhibitors 3.1.4.6 Immunotherapies 3.1.4.7 Monoclonal Antibodies 3.2 CDT in Anticancer Therapy 3.2.1 CDT in Lung Cancer 3.2.1.1 Taxane-Platinum Combinations 3.2.1.2 VEGFR/PDGFR Dual Inhibitor Combinations 3.2.1.3 VEGFR/EGFR Dual Inhibitor Combinations 3.2.1.4 VEGFR/FGFR Dual Inhibition 3.2.1.5 VEGFR/PDGFR/FGFR Triple-Target Inhibition 3.2.2 CDT in Colorectal Cancer 3.2.2.1 CDT Cytotoxic Therapy (Chemotherapy) 3.2.2.2 CDT Targeted Therapy 3.2.3 CDT in Hepatocellular Carcinoma 3.2.3.1 Anti-PD-L1/Anti–VEGF Combination: Atezolizumab/Bevacizumab Combination 3.2.3.2 Anti-PD-L1/Anti-VEGFR2 Combinations 3.2.3.3 Anti-PD-L1/Tyrosine Kinase Inhibitor Combination: Pembrolizumab/Lenvatinib Combination 3.2.4 CDT in Stomach Cancer 3.2.4.1 Platinum/Fluoropyrimidine Combinations 3.2.5 CDT in Female Breast Cancer 3.2.5.1 Chemotherapeutics Combinations 3.2.5.2 Hormonal/Endocrine Therapeutics Combinations 3.2.5.3 Immunotherapeutics Combinations 3.2.5.4 Combinations of Muscarinic Acetylcholine Receptor Agonists with Other Classes of Anti-BC Drugs 3.2.6 Potential Combinations of Oncolytic Virotherapy and Chemotherapy for Cancer Treatment in the Future 3.3 FDC in Anticancer Therapy 3.3.1 FDC in Lung Cancer 3.3.1.1 Pioglitazone/Metformin FDC 3.3.1.2 Erlotinib/Pertuzumab FDC 3.3.2 FDC in Stomach Cancer 3.3.2.1 Dual Combinations of S-1 FDC with Other Agents 3.3.2.2 Triple Combination of S-1 FDC with Docetaxel and Cisplatin 3.3.3 FDC in Female Breast Cancer 3.3.3.1 Pertuzumab/Trastuzumab FDC 3.4 MTD in Anticancer Therapy 3.4.1 Multitargeted Tyrosine Kinase Inhibitors (MT-TKIs) as Anticancer MTDs 3.4.1.1 Vandetanib 3.4.1.2 Sunitinib 3.4.1.3 Axitinib 3.4.1.4 Sorafenib 3.4.1.5 Vatalanib 3.4.1.6 Cediranib 3.4.1.7 Motesanib 3.4.1.8 Pazopanib 3.4.1.9 Linifanib 3.4.1.10 Tesevatinib 3.4.1.11 Brivanib 3.4.1.12 Nintedanib 3.4.1.13 Lenvatinib 3.4.2 Multitargeting HDAC Inhibitors as Anticancer MTDs 3.4.2.1 HDAC Inhibitor Hybrids 3.4.2.2 HDAC Inhibitor─Kinase Inhibitor Hybrids References 4: Polypharmacology in Clinical Applications: Cardiovascular Polypharmacology 4.1 CDT in the Treatment of CVD 4.1.1 CDT in Hypertension 4.1.1.1 Antihypertensives 4.1.1.2 Combination Therapy of Hypertension 4.1.1.3 Principles of Antihypertensive Combination 4.1.1.4 Initial Combination Therapy (ICT) 4.1.1.5 Combination Therapy of Pulmonary Arterial Hypertension (PAH) 4.1.2 CDT in Hyperlipidemia 4.1.2.1 Hypolipidemic Drugs 4.1.2.2 Combination Therapy of Hyperlipidemia 4.1.2.3 Limitations of Combination Therapy 4.1.3 CDT in Coronary Artery Disease (CAD) 4.1.3.1 Drug Treatment of CAD 4.1.3.2 Combination Therapy 4.1.4 CDT in Heart Failure (HF) 4.1.4.1 Drugs for HF Treatment 4.1.4.2 Combination Therapy of HF 4.1.5 CDT in Cardiac Arrhythmia 4.1.5.1 Antiarrhythmic Drug (AAD) Treatment of Cardiac Arrhythmia 4.1.5.2 Combination AAD Therapy 4.1.5.3 Principles of Combination AAD Therapy 4.1.6 CDT in Stroke 4.1.6.1 Prevention and Treatment of Acute Stroke 4.1.6.2 Recovery Medications After Stroke 4.1.6.3 Combination Treatment of Stroke 4.2 FDC in the Treatment of CVD 4.2.1 FDC in Hypertension 4.2.2 FDC in Hyperlipidemia 4.2.2.1 Rosuvastatin/Ezetimibe FDC 4.2.2.2 Simvastatin/Ezetimibe FDC 4.2.2.3 Simvastatin/Niacin FDC 4.2.2.4 Lovastatin/Niacin FDC 4.2.2.5 Ezetimibe/Simvastatin FDC Plus Extended-Release Niacin 4.2.3 FDC in Coronary Artery Disease (CAD) 4.2.3.1 Pacemaker Channel Blocker (PCB)/β-Blocker FDC 4.2.3.2 ACEI/CCB FDC 4.2.3.3 β-Blocker/ARB/Diuretic FDC 4.2.3.4 Dual Antiplatelet Agent FDC 4.2.3.5 Statin/Antihypertensive FDC Plus Aspirin Combination 4.2.3.6 Statin/β-Blocker/Diuretic/ACEI FDC plus Aspirin Combination 4.2.4 FDC in Heart Failure (HF) 4.2.5 FDC in Stroke 4.2.5.1 Dual Antiplatelet Drug FDC (Aspirin/Dipyridamole) for Stroke 4.2.5.2 ARB/Diuretic FDC (Losartan/Hydrochlorothiazide) for Stroke 4.2.5.3 Anticoagulant/Antiplatelet FDC (Warfarin/Aspirin) for Stroke 4.3 MTD in the Treatment of CVD 4.3.1 MTD in Hypertension 4.3.2 MTD in Cardiac Arrhythmia 4.3.2.1 Amiodarone as a MTD Antiarrhythmic 4.3.2.2 Dronedarone as an MTD Antiarrhythmic 4.3.2.3 Vernakalant as a MTD Antiarrhythmic 4.3.2.4 Ranolazine as a MTD Antiarrhythmic 4.3.2.5 NIP-14 as a MTD Antiarrhythmic 4.3.2.6 Other MTD Antiarrhythmics References 5: Polypharmacology in Clinical Applications: Metabolic Disease Polypharmacology 5.1 CDT for Metabolic Disease 5.1.1 CDT in Diabetes Mellitus (DM) 5.1.1.1 Basics of Diabetic Mellitus (DM) 5.1.1.2 Medications for T1DM 5.1.1.3 Medications for T2DM: Hypoglycemic Agents 5.1.1.4 Combination Therapy of T2DM 5.1.2 CDT in Obesity 5.1.2.1 Basics of Obesity 5.1.2.2 Pharmacological Treatment of Obesity 5.1.2.3 Combination Therapies for Obesity 5.2 FDC for the Treatment of Metabolic Disease 5.2.1 FDC in Diabetes Mellitus (DM) 5.2.1.1 Sitagliptin/Metformin FDC for T2DM 5.2.1.2 Empagliflozin/Metformin FDC for T2DM 5.2.1.3 Empagliflozin/Linagliptin FDC for T2DM 5.2.1.4 Canagliflozin/Metformin FDC for T2DM 5.2.1.5 Linagliptin/Metformin FDC for T2DM 5.2.1.6 Pioglitazone/Metformin FDC for T2DM 5.2.1.7 Dapagliflozin/Saxagliptin FDC for T2DM 5.2.1.8 Pioglitazone/Glimepiride FDC for T2DM 5.2.1.9 Ertugliflozin/Metformin FDC for T2DM 5.2.1.10 Acarbose/Metformin FDC for T2DM 5.2.1.11 Insulin Degludec/Liraglutide FDC for T2DM 5.2.1.12 Saxagliptin/Metformin FDC for T2DM 5.2.1.13 Dapagliflozin/Metformin FDC for T2DM 5.2.2 FDC in Obesity 5.2.2.1 Naltrexone/Bupropion FDC for Obesity 5.2.2.2 Phentermine IR/Topiramate ER FDC for Obesity 5.2.2.3 Orlistat/Acarbose FDC for Obesity 5.2.2.4 D-Norpseudoephedrine/Tri-iodothyronine/Atropine/Aloin/Diazepam FDC for Obesity 5.3 MTD for the Treatment of Metabolic Disease 5.3.1 MTD in Diabetes Mellitus (DM) 5.3.1.1 PPARα/γ Dual Agonists as MTD Drugs for T2DM 5.3.1.2 PPAR Pan-agonists as MTD Drugs for T2DM 5.3.1.3 GLP-1/Glucagon Dual Agonists as MTD Drugs for T2DM 5.3.1.4 GLP-1/GIP Dual Agonists as MTD Drugs for T2DM 5.3.2 MTD in Obesity References 6: Polypharmacology in Clinical Applications: Neurological Polypharmacology 6.1 Basics of Neurological Disorders 6.2 CDT in Neurological Disease 6.2.1 CDT in Alzheimer’s Disease (AD) 6.2.1.1 Basics of Alzheimer’s Disease (AD) 6.2.1.2 Drug Treatments in Alzheimer’s Disease 6.2.1.3 Combination Drug Therapy of Alzheimer’s Disease 6.2.2 CDT in Parkinson’s Disease (PD) 6.2.2.1 Basics of Parkinson’s Disease (PD) 6.2.2.2 Drug Treatments in PD 6.2.2.3 Combination Drug Therapy in Parkinson’s Disease 6.2.3 CDT in Epilepsy 6.2.3.1 Basics of Epilepsy 6.2.3.2 Drug Treatments in Epilepsy 6.2.3.3 Combination Drug Therapy in Epilepsy 6.2.4 CDT in Multiple Sclerosis (MS) 6.2.4.1 Basics of Multiple Sclerosis (MS) 6.2.4.2 Drug Treatments in Multiple Sclerosis (MS) 6.2.4.3 Combination Drug Therapy in Multiple Sclerosis (MS) 6.2.5 CDT in Schizophrenia 6.2.5.1 Basics of Schizophrenia 6.2.5.2 Drug Treatment of Schizophrenia 6.2.5.3 Combination Drug Therapy of Schizophrenia 6.3 FDC in Neurological Disease 6.3.1 FDC in Alzheimer’s Disease (AD) 6.3.1.1 Memantine ER/Donepezil FDC for AD 6.3.1.2 Memantine/Rivastigmine FDC for AD 6.3.2 FDC in Parkinson’s Disease (PD) 6.3.2.1 Melevodopa/Carbidopa FDC for PD 6.3.2.2 Levodopa/Carbidopa/Entacapone FDC for PD 6.3.3 FDC in Schizophrenia 6.4 MTD in Neurological Disease 6.4.1 MTD in Alzheimer’s Disease (AD) 6.4.1.1 Tacrine-Adamantanes Hybrids 6.4.1.2 Galantamine-Memantine Hybrids 6.4.1.3 Aminoadamantane-Carbazole/Tetrahydrocarbazole Hybrids 6.4.1.4 Memantine-Ferulic Acid Hybrids 6.4.1.5 Memantine-Glutathione/Lipoic Acid Hybrids 6.4.1.6 Amantadine-Propargylamine Hybrids 6.4.1.7 Memantine-Polyamine Conjugates 6.4.1.8 H2S-Releasing Memantine Prodrug 6.4.2 MTD in Parkinson’s Disease (PD) 6.4.2.1 Safinamide as a MTD for PK 6.4.2.2 Ladostigil as a MTD for PK 6.4.2.3 Iron Chelator-Radical Scavenging Drugs (M30) as MTDs for PD 6.4.3 MTD in Epilepsy and Seizures 6.4.3.1 Antiepileptic Drugs (AEDs) as MTDs for Epilepsy 6.4.3.2 Antiseizure Medications as MTDs for Seizures 6.4.4 MTD in Schizophrenia 6.4.4.1 Antipsychotic Agents as MTDs for Schizophrenia 6.4.4.2 Psychoactive Drugs as MTDs for Schizophrenia References 7: Polypharmacology in Clinical Applications: Respiratory Polypharmacology 7.1 Respiratory Disease and Pharmacological Treatment 7.1.1 Basics of Respiratory Disease (RD) 7.1.1.1 Airway Diseases 7.1.1.2 Airway Diseases, Lung Tissue Diseases 7.1.1.3 Airway Diseases, Lung Circulation Diseases 7.1.2 Drug Therapy of Pulmonary Disease 7.1.2.1 Airway Diseases, Categories of Therapeutic Agents for PD Treatment 7.1.2.2 Airway Diseases, Major Respiratory Diseases and the Current Drug Therapies 7.2 CDT in Respiratory Disease 7.2.1 CDT for the Treatment of Chronic Obstructive Pulmonary Disease (COPD) 7.2.2 CDT for the Treatment of Pulmonary Tuberculosis (PTB) 7.2.3 CDT for COVID-19 7.2.3.1 Novel Antibody Drugs 7.2.3.2 Novel Protease Inhibitor: PF-07321332/Nirmatrelvir/Paxlovid 7.2.3.3 Novel Viral Replication Inhibitor: Molnupiravir 7.2.3.4 Drug Repositioning 7.3 FDC in Respiratory Disease 7.3.1 FDC for the Treatment of COPD 7.3.1.1 LAMA/LABA Dual Combination 7.3.1.2 LAMA/ICS or LABA/ICS Dual Combination 7.3.1.3 LAMA/LABA/ICS Triple Combination 7.3.2 FDC for the Treatment of Pulmonary Tuberculosis (TB) 7.4 MTD in Respiratory Disease 7.4.1 Multitarget Tyrosine Kinase Inhibitors as MTD Therapeutics for RD 7.4.2 Natural Products as MTD Therapeutics for RD 7.4.3 Oligonucleotides as Sequence-Based MTD Epi-drugs for RD 7.4.4 Drug Repositioning of MTDs for RD References 8: Polypharmacology in Clinical Applications: Gastrointestinal Polypharmacology 8.1 Gastrointestinal Disease 8.1.1 Basics of Gastrointestinal Disease (GI Disease) 8.1.1.1 Oral Disease 8.1.1.2 Esophageal Disease 8.1.1.3 Gastric Disease 8.1.1.4 Intestinal Disease 8.1.1.5 Accessory Digestive Gland Disease 8.1.1.6 Gut Microbiota 8.1.2 Pharmacological Therapy of GI Disease 8.1.2.1 Agents Affecting Gastrointestinal Motility 8.1.2.2 Antiemetics 8.1.2.3 Gastric Acid-Reducing Agents and Antacids 8.1.2.4 Antibiotics Used for Gastrointestinal Infections 8.1.2.5 Anti-inflammatory Drugs for Inflammatory Bowel Disease 8.1.2.6 Immunosuppressive Agents for Inflammatory Bowel Disease 8.1.2.7 Bile Acid Sequestrants 8.1.2.8 Gut Microbiota-Maintaining Supplements 8.2 CDT in GI Disease 8.2.1 H2 Receptor Antagonist/Alginic Acid CDT for Esophageal Reflux Disease 8.2.2 H2 Receptor Antagonist/Multiple Medications CDT for Esophageal Reflux Disease 8.3 FDC in GI Disease 8.3.1 Daclatasvir/Sofosbuvir/Ribavirin FDC for the Treatment of HCV 8.3.2 Sofosbuvir/Velpatasvir/Ribavirin FDC for the Treatment of HCV 8.3.3 Daclatasvir/Sofosbuvir FDC for the Treatment of HCV-HIV Coinfection 8.4 MTD in GI Disease References 9: Polypharmacology in Clinical Applications: Renal Polypharmacology 9.1 Basics of Renal Diseases and Therapy 9.1.1 Renal Disease 9.1.2 Types of Renal Diseases 9.1.2.1 Chronic Kidney Disease (CKD) 9.1.2.2 Kidney Failure 9.1.2.3 Acute Renal Failure (ARF) 9.1.2.4 Polycystic Kidney Disease (PKD) 9.1.2.5 Drug-Induced Nephrotoxicity (DNT) 9.1.2.6 Other Kidney Diseases 9.1.3 Pharmacological Therapy of Renal Diseases 9.1.3.1 Blood Pressure Medicine 9.1.3.2 Erythropoiesis-Stimulating Agents (ESAs) 9.1.3.3 Iron Supplements 9.1.3.4 Phosphate Binders 9.1.3.5 Potassium Binders 9.1.3.6 Calcium and Vitamin D 9.2 CDT for Renal Disease 9.2.1 CDT in Chronic Kidney Disease (CKD) 9.2.1.1 Dual RAS Inhibition: ACEI/ARB Combinations 9.2.1.2 RAS Inhibitor/ARB Combinations 9.2.1.3 Mechanisms for the Efficacy of Combinational Therapy 9.2.2 CDT in Diabetic Kidney Disease (DKD) 9.2.2.1 SGLT2 Inhibitor/ACEI or ARB Combination 9.2.2.2 SGLT2 Inhibitor/DPP-4 Inhibitor Combination 9.2.2.3 SGLT2 Inhibitor/GLP1-RA Combination 9.2.2.4 SGLT2 Inhibitor/MRA Combination 9.2.3 CDT in Hypertensive Kidney Disease (HKD) 9.2.4 CDT in Polycystic Kidney Disease (PKD) 9.2.5 CDT in Drug-Induced Nephrotoxicity (DNT) 9.3 FDC Drugs for Renal Disease 9.3.1 FDC in Chronic Kidney Disease (CKD) 9.3.2 FDC in Diabetic Kidney Disease (DKD) 9.3.3 FDC in Hypertensive Kidney Disease (HKD) 9.4 MTD Drugs for Renal Disease References 10: Polypharmacology in Clinical Applications: Anti-infection Polypharmacology 10.1 Basics of Infectious Diseases 10.1.1 Emerging Infectious Diseases (EIDs) 10.1.1.1 Zoonotic Diseases 10.1.1.2 Vector-Borne Diseases 10.1.2 Neglected Infectious Diseases (NIDs) 10.1.3 Treatment of Infectious Diseases 10.1.3.1 Antibiotics 10.1.3.2 Antivirals 10.1.3.3 Antifungals 10.1.3.4 Antiparasitics 10.2 CDT for Infectious Diseases 10.2.1 CDT in Bacterial Infection 10.2.1.1 Synergistic Compound Combinations 10.2.1.2 Potentiative Compound Combinations 10.2.2 CDT in Viral Infection 10.2.3 CDT in Chagas Disease (CD) 10.3 FDC for Infectious Diseases 10.3.1 FDC in Bacterial Infection 10.3.2 FDC in Viral Infection 10.3.3 FDC in Chagas Disease (CD) 10.4 MTD for Infectious Diseases 10.4.1 MTD in Bacterial Infection 10.4.1.1 Naturally Occurring Multitarget Antibiotics 10.4.1.2 Artificially Synthesized Multitarget Antibiotics 10.4.1.3 Multitargets in the Same Pathway 10.4.1.4 Multitargets in Different Pathways 10.4.1.5 Designer Dual-Target Compounds 10.4.1.6 Multifunctional Compounds 10.4.2 MTD Drugs in Viral Infection 10.4.2.1 MTD Drugs in Anti-HIV-1/HSV-2 Therapy 10.4.2.2 MTD Drugs in Anti-HIV-1/HCV-2 Therapy 10.4.2.3 MTD Strategy in Anti-SARS-CoV-2 Drug Discovery References 11: Polypharmacology in Clinical Applications—Anti-inflammation Polypharmacology 11.1 Anti-Inflammatory Medication 11.1.1 Basics of Inflammation 11.1.1.1 What Is Inflammation? 11.1.1.2 Acute vs. Chronic Inflammation 11.1.1.3 Inflammation vs. Infection 11.1.1.4 Inflammation and Pain 11.1.2 Causes and Consequences of Inflammation 11.1.2.1 Stimuli Causing Inflammation 11.1.2.2 Symptoms of Inflammation 11.1.2.3 Conditions Linked to Chronic Inflammation 11.1.3 Treatment for Chronic Inflammation 11.1.4 Inflammation and Polypharmacology 11.1.4.1 Cyclooxygenases (COX-1/2) 11.1.4.2 Lipoxygenase (5-LOX) 11.1.4.3 Soluble Epoxide Hydrolase (sEH) 11.1.4.4 Microsomal Prostaglandin E Synthase-1 (mPGES-1) 11.1.4.5 Leukotriene A4 Hydrolase (LTA4H) 11.1.4.6 Thromboxane 2 Synthase (TXA2) Synthase 11.1.4.7 11β-Hydroxysteroid Dehydrogenase Type 1 (11β-HSD1) 11.1.4.8 Fatty Acid Amide Hydrolase (FAAH) 11.1.4.9 CC Chemokine Ligand 5 (CCL5) and CC Chemokine Receptor 5 (CCR5) 11.2 CDT Anti-Inflammatory Drugs 11.3 FDC Anti-inflammatory Drugs 11.4 MTD Anti-inflammatory Drugs 11.4.1 COX/5-LOX Dual Inhibitors as MTD Drugs for Inflammation 11.4.1.1 Redox Inhibitors 11.4.1.2 Iron Chelators 11.4.1.3 Nonredox, Nonchelators 11.4.2 COX/sEH Dual Inhibitors 11.4.3 LOX/sEH Dual Inhibitors 11.4.4 Dual Inhibitors of Enzymes Downstream the COX or LOX Pathways as MTD Drugs for Inflammation 11.4.4.1 5-LOX and mPGES-1 Dual Inhibitors 11.4.4.2 COX-2 and LTA4H Dual Inhibitors 11.4.4.3 5-LOX and TXA2 Synthase Dual Inhibitors 11.4.5 Dual Inhibitors Targeting Enzymes Downstream in the CYP Pathway and Enzymes Outside ARA Cascade 11.4.5.1 sEH/11β-HSD1 Dual Inhibitors 11.4.5.2 Sorafenib 11.4.6 FAAH/COX Dual Inhibitors as MTD Drugs for Inflammation 11.4.7 CCR5 Antagonist and mu Opioid Receptor (MOR) Agonist 11.4.8 Benzimidazoles as a Scaffold of MTD Drugs for Inflammation References 12: Polypharmacology in Drug Design and Discovery—Basis for Rational Design of Multitarget Drugs 12.1 Sequenced-Based Strategy for Designing Epigenetic MTDs (Epi-MTDs) 12.1.1 Epigenetic Polypharmacology 12.1.1.1 Epigenetics 12.1.1.2 Epigenetic Drugs (Epi-Drugs) 12.1.1.3 Multitarget Epigenetic Drugs (Epi-MTDs) 12.1.2 RNA Sequence-Based Strategy for Designing Epi-MTDs 12.1.2.1 Endogenous RNAs as Epi-MTDs 12.1.2.2 Rationally Designed RNA Fragments as Epi-MTDs 12.1.3 DNA Sequence-Based Strategy for Designing Epi-MTDs 12.1.3.1 Multitarget Antisense Oligodeoxynucleotides (MT-asODN) 12.1.3.2 Complex Decoy Oligodeoxynucleotides (cdODN) 12.1.4 Protein/Peptide Sequence-Based Strategy for Designing Epi-MTDs 12.1.4.1 Decoy Oligodeoxynucleotides (dODNs) 12.1.4.2 RNA-Binding Protein (RBP)/Ribonucleoprotein (RNP) 12.1.4.3 Decoy Peptides (DPs) and Cell-Penetrating Peptides (CPPs) 12.2 Sequenced-Based Strategy for Designing Gene Therapy MTDs 12.2.1 Single-Stranded Oligodeoxynucleotides (ssODNs) 12.2.2 Chimeric RNA/DNA Oligonucleotides (RDOs) 12.2.3 Small DNA Fragments (SDFs)/Small Fragment Homologous Replacement (SFHR) 12.2.4 Triplex-Forming Oligodeoxynucleotides (TFOs) 12.2.5 Triplex-Forming Peptide Nucleic Acids (PNAs) 12.2.6 Adeno-Associated Virus Vectors 12.3 Sequenced-Based Strategy for Designing Small-Molecule MTDs (SM-MTDs) 12.3.1 Small Molecules (SM) and Small-Molecule Drugs (SMDs) 12.3.2 Small-Molecule Modulators of RNAs as Epigenetic SM-MTDs 12.3.2.1 Advantages of Targeting RNAs for Disease Therapy 12.3.2.2 Structural Requirements of RNAs for Small-Molecule Targeting 12.3.2.3 Classes of RNA Targets 12.3.2.4 Challenges in the Discovery of RNA-Targeted Small-Molecule Drugs 12.3.3 Small-Molecule Modulators of DNAs as Gene-Therapy SM-MTDs 12.3.3.1 Covalent Interactions between SMDs and DNA 12.3.3.2 Noncovalent Interactions between SMDs and DNA 12.3.3.3 Forces Involved in DNA-Drug Recognition 12.4 Function-Based Strategy for Designing Epi-MTDs 12.4.1 Function-Based Epigenetic Targets 12.4.1.1 DNA Methylation Modifications as Epigenetic Targets 12.4.1.2 Histone Modifications as Epigenetic Targets 12.4.1.3 RNA Methylation Modifications as Epigenetic Targets 12.4.2 Chromatin-Targeted SMDs as Epi-MTDs 12.4.2.1 Epi-STDs in Clinical Use 12.4.2.2 Epi-CDTs in Clinical Use 12.4.2.3 Epi-MTDs in Development 12.5 Medicinal Chemistry-Based Strategy for Designing SM-MTDs 12.5.1 Multitarget Small-Molecule Drugs (SM-MTDs) 12.5.2 Privileged Scaffold-Based SM-MTDs 12.5.2.1 Chalcone 12.5.2.2 Chromanone 12.5.2.3 Coumarin 12.5.2.4 Benzisoxazole 12.5.2.5 Stilbene 12.5.3 Molecular Hybrid SM-MTDs 12.5.3.1 Cleavable Linker 12.5.3.2 Non-Cleavable Linker 12.5.3.3 Molecular Merge 12.5.4 Fragment-Based SM-MTDs 12.5.4.1 Identification of Druggable Targets for Fragments 12.5.4.2 Primary Screening of Fragments 12.5.4.3 Compound Optimization 12.6 Biopharmaceutical-Based Strategy for Designing Macromolecular MTDs (MM-MTDs) 12.6.1 Antibody 12.6.1.1 Antibody Mixture (AbMix) 12.6.1.2 Antibody–Antibody Conjugates (AACs) or Chimeric Antibodies 12.6.1.3 Antibody–Drug Conjugates (ADCs) 12.6.1.4 Antibody–siRNA Conjugates (ARCs) 12.6.2 Biologics 12.6.3 Polymeric Nanomedicines 12.6.4 Drug-Free Macromolecular Therapeutics (DFMT) 12.7 Natural Products for MTD Discovery 12.7.1 Reconstructing Drug–Target Network of Natural Products 12.7.1.1 General Drug Target Databases 12.7.1.2 Natural Products-Specific Drug Target Databases 12.7.2 Systems Biology Resources 12.7.2.1 Chemogenomics Resources 12.7.2.2 PPI Databases 12.7.3 Computational Approaches for Predicting New Targets of Natural Products 12.7.3.1 Target-Based Approaches 12.7.3.2 Ligand-Based Approaches 12.7.3.3 Chemogenomics-Based Approaches 12.7.3.4 Network-Based Approaches 12.7.3.5 Omics-Based Systems Biology Approaches 12.7.3.6 Performance Evaluation of Computational Models 12.7.4 Macromolecular Targets of Complex Natural Products 12.8 Drug Repurposing for MTD Discovery 12.8.1 Advantages and Challenges of Drug Repurposing in MTD Discovery 12.8.1.1 Strengths of Drug Repurposing Strategy in MTD Discovery 12.8.1.2 Challenges of Drug Repurposing Strategy in MTD Discovery 12.8.2 Basis for Drug Repurposing 12.8.2.1 Drug Promiscuity: The Theoretical Basis 12.8.2.2 Drug Data: The Technological Basis 12.8.2.3 Clinical Development Principles 12.8.3 Common Approaches for Drug Repurposing 12.8.3.1 Experimental Screening Approaches 12.8.3.2 In silico Repurposing Approaches 12.8.3.3 Combinatory Approaches References 13: Polypharmacology in Old Drug Rediscovery: Drug Repurposing 13.1 Drug Repurposing Approaches and Resources 13.1.1 Computational/In Silico Approaches 13.1.1.1 Knowledge-Based Methods 13.1.1.2 Signature-Based Methods 13.1.1.3 Targeted Mechanism-Based Methods 13.1.1.4 Network-Based Approaches 13.1.1.5 Text Mining-Based Approaches 13.1.1.6 Semantics-Based Approaches 13.1.2 Biological Experimental Screening Approaches 13.1.2.1 Target-Based Methods 13.1.2.2 Phenotypic Screening Methods 13.1.3 Mixed or Combinatory Approaches 13.1.4 Resources for Drug Repurposing 13.2 Drug Repurposing in Oncology 13.2.1 Repurposing Non-anticancer Drugs for Cancer Therapy 13.2.2 Repurposing of Approved Cardiovascular Drugs for Cancer Therapy 13.2.2.1 Blood Thinner Aspirin 13.2.2.2 β-Blockers 13.2.2.3 Antihypertensive ACE Inhibitors and ARBs 13.2.2.4 Cardiac Glycosides 13.2.2.5 Lipid-Lowering Drugs Statins 13.2.2.6 Antiarrhythmic Drug Lidocaine 13.2.3 Repurposing Antidiabetic Metformin for Cancer Therapy 13.3 Drug Repurposing in Cardiometabolic Disorders (CMDs) 13.3.1 Colchicine 13.3.2 Metformin 13.4 Drug Repurposing in Alzheimer’s Disease 13.5 Drug Repurposing for Rare and Orphan Diseases 13.6 Drug Repurposing for Neglected Tropical Diseases (NTDs) 13.7 Drug Repurposing in Coronavirus Disease 2019 (COVID-19) 13.7.1 The Drug Repurposing Approaches in Emergent Situations: COVID-19 13.7.1.1 Transcriptome-Based Drug Repurposing for COVID-19 13.7.1.2 Structure-Based Drug Repurposing for COVID-19 13.7.1.3 Systematic and Integrative Drug Repurposing for COVID-19 13.7.1.4 Network Pharmacology-Based Drug Repurposing for COVID-19 13.7.2 Examples of Repurposed Anticancer Drugs for COVID-19 13.7.3 Repurposing Colchicine for Anti-COVID-19 Therapy 13.8 Drug Repurposing from the Perspective of Pharmaceutical Industries 13.8.1 Drug Data Access 13.8.2 Clinical Development Principles for Drug Repurposing 13.8.3 Challenges and Opportunities in Drug Repurposing for Pharmaceutical Companies References 14: Polypharmacology in Predicting Drug Toxicity: Drug Promiscuity 14.1 The Connotations of Drug Promiscuity 14.1.1 The “Good” Side or “Angel Face” of Drug Promiscuity 14.1.2 The “Bad” Side or “Devil Face” of Drug Promiscuity 14.2 Predicting Drug Promiscuity and Associated Off-Target Effects 14.2.1 Using High-Throughput Screening Data for Drug Promiscuity 14.2.2 Computational Approaches for Drug Promiscuity 14.2.2.1 Quantitative Structure–Activity Relationships 14.2.2.2 Matched Molecular Pair Analysis for Drug Promiscuity 14.2.2.3 Chemical Structure Analysis for Drug Promiscuity 14.2.2.4 Structural Similarity Analysis for Drug Promiscuity 14.2.2.5 Chemical–Chemical and Protein–Chemical Interactions for Drug Promiscuity 14.2.2.6 Adverse Drug Event Network 14.2.2.7 Scaffold Analysis of SAR Profiles [Hu Y 2011] 14.2.3 Systems Biology Approaches for Drug Promiscuity 14.2.4 Chemical Systems Biology for Drug Promiscuity 14.3 Structure–Promiscuity Relationships of Therapeutic Compounds 14.3.1 The Concept of Drug Promiscuity Cliff 14.3.2 Identification of Promiscuity Cliff by Systematic Analysis 14.3.2.1 From Activity and Selectivity Cliffs to Promiscuity Cliffs 14.3.2.2 Systematic Analysis of Promiscuity Cliffs 14.3.3 Identification of Promiscuity Cliff by Machine Learning 14.3.3.1 Compound Pair-Based Promiscuity Predictions 14.3.3.2 Selection of Training and Test Set 14.3.3.3 Molecular Representation for Machine Learning 14.3.3.4 Prediction of Promiscuity Cliffs 14.3.3.5 Predicting Promiscuity Cliffs with Varying ΔPDs 14.3.3.6 Structure–Promiscuity Relationships 14.4 Big Data in Molecular Promiscuity Analysis 14.4.1 The Concept of Big Data 14.4.2 Big Data in Medicinal Chemistry 14.4.3 Big Data in Chemical Toxicology References 15: Polypharmacology and Natural Products 15.1 Natural Products and Polypharmacology 15.2 Systems Pharmacology and Network Pharmacology in NPs Polypharmacology 15.3 NPs as MTDs in Cancer Therapy 15.3.1 Flavonoids 15.3.1.1 Kaempferol 15.3.1.2 Curcumin 15.3.1.3 Quercetin 15.3.2 Isoflavonoid 15.3.2.1 Genistein 15.3.2.2 Naringenin (DB03467) 15.3.3 Non-flavonoid Polyphenol 15.3.3.1 Resveratrol 15.3.4 Other NPs 15.3.4.1 Disulfiram (DB00822) 15.3.4.2 Metformin (DB00331) 15.3.4.3 Epigallocatechin Gallate (EGCG) 15.3.4.4 Berberine 15.4 Resources and Tools for Systems/Network Pharmacology on NPs 15.4.1 Reconstructing Drug–Target Network of Natural Products 15.4.1.1 General Drug–Target Databases 15.4.1.2 Natural Product-Specific Resources 15.4.2 Systems Biology Resources 15.4.2.1 Chemogenomics Resources 15.4.2.2 PPI Databases 15.4.2.3 Cancer Genomics Resources 15.4.3 Computational Approaches for Predicting New Targets of NPs 15.4.3.1 Target-Based Approaches 15.4.3.2 Ligand-Based Approaches 15.4.3.3 Chemogenomics-Based Approaches 15.4.3.4 Network-Based Approaches 15.4.3.5 Omics-Based Systems Biology Approaches 15.4.4 Performance Evaluation of Computational Models References 16: Polypharmacology and Polypharmacokinetics 16.1 General Concept of Pharmacokinetics and Polypharmacokinetics 16.1.1 Basics of Pharmacokinetics (PK) 16.1.2 Differences Between Polypharmacokinetics and Regular Pharmacokinetics 16.2 Metabolomics Approach for Polypharmacokinetics 16.2.1 Basic Concept of Metabolomics 16.2.2 Metabolomics in Xenobiotic Intervention Study 16.2.3 Metabolomics-Based Strategy for Poly-PK Analysis 16.2.4 Other Metabolomics-Based Platforms for Poly-PK Analysis 16.3 Drug–Drug Interactions (DDIs) and Polypharmacokinetics References 17: General Process for Rational Design and Discovery of MTDs 17.1 General Process for Drug Discovery and Development 17.1.1 Step 1: Discovery and Development 17.1.1.1 Target Identification and Validation 17.1.1.2 Hit Identification and Validation 17.1.1.3 Lead Identification and Validation 17.1.1.4 Lead Optimization 17.1.1.5 Late-Stage Lead Optimization 17.1.1.6 Active Pharmaceutical Ingredients 17.1.2 Step 2: Preclinical Research 17.1.2.1 Determine ADME 17.1.2.2 Proof of Principle/Proof of Concept 17.1.2.3 In Vivo, In Vitro, and Ex Vivo Assays 17.1.2.4 In Silico Assays 17.1.2.5 Determine Drug Delivery Methods 17.1.2.6 Optimizing Formulation and Improving Bioavailability 17.1.3 Step 3: Clinical Development 17.1.3.1 Complexity of Study Design, Associated Cost, and Implementation Issues 17.1.3.2 Clinical Trials: Dose Escalation, Single Ascending, and Multiple Dose Studies 17.1.3.3 Biological Samples Collection, Storage, and Shipment 17.1.3.4 Pharmacodynamic (PD) Biomarkers 17.1.3.5 Pharmacokinetic Analysis 17.1.3.6 Bioanalytical Method Development and Validation 17.1.3.7 Drug (Analyte) and Metabolite Stability in Biological Samples 17.1.3.8 Blood, Plasma, Urine, and Feces Sample Analysis for Drug and Metabolites 17.1.3.9 Patient Protection: GCP, HIPAA, and Adverse Event Reporting 17.1.4 Step 4: FDA Review 17.1.4.1 Regulatory Approval Timeline 17.1.4.2 IND Application 17.1.4.3 NDA/ANDA/BLA Applications 17.1.4.4 Orphan Drug 17.1.4.5 Accelerated Approval 17.1.4.6 Reasons for Drug Failure 17.1.5 Step 5: Post-market Monitoring 17.2 Other Relevant Drug Development Concepts 17.2.1 Drug Master File 17.2.2 Drugs for Pediatric Use 17.2.3 Drugs for Veterinary Use 17.2.4 Small Molecule vs Biologics 17.2.5 Process Scale-Up Differences and Difficulties 17.3 Multitargets Identification and Validation (MT-IV) 17.3.1 Identification of Multiple Targets 17.3.1.1 Principles for Multitargets Selection 17.3.1.2 General Steps of Multitargets Identification (MT-I) 17.3.1.3 Multitargets Validation (MT-V) 17.3.1.4 An Example of MT-IV Procedures 17.3.1.5 An Example of MT-IV for Alzheimer’s Disease (AD) 17.3.2 Multitarget Lead Identification and Validation for MTDs References 18: General Strategies for Rational Design and Discovery of Multitarget Drugs 18.1 Target-Based Approach 18.1.1 Concept and Applicability of Target-Based Strategy in Drug Discovery 18.1.2 Assays for Validating Phenotype-Based Drug Discovery 18.1.2.1 Target-Based Screening 18.1.2.2 Target-Based Assays 18.2 Phenotype-Based Approach 18.2.1 Concept and Applicability of Phenotype-Based Strategy in Drug Discovery 18.2.2 Assays for Validating Phenotype-Based Drug Discovery 18.2.2.1 In Vivo Assays 18.2.2.2 Cell-Based (In Vitro) Assays 18.3 Sequence-Based Approach 18.4 Structure-Based Drug Design in Drug Discovery 18.4.1 Concept and Applicability of Structure-Based Strategy in Drug Discovery 18.4.2 Methods for Structure-Based Strategy in Drug Discovery 18.4.2.1 Molecular Docking 18.4.2.2 Inverse Molecular Docking 18.4.2.3 Binding-Site Structural Similarity (BsSS) 18.4.2.4 Structure-Based Virtual Screening 18.4.3 An Overview of SBDD Process 18.4.3.1 Target Protein and Binding-Site Identification 18.4.3.2 Virtual Screening: A Lead Identification Approach 18.4.3.3 De Novo Drug Design 18.4.3.4 Molecular Docking 18.4.3.5 Scoring Functions 18.5 Scaffold-Based Approach 18.5.1 Concept and Applicability of Scaffold-Based Strategy in Drug Discovery 18.5.2 Examples of Privileged Scaffolds 18.5.2.1 Conformationally Locked Methanocarba Nucleosides 18.5.2.2 N-Propargylamines 18.5.2.3 Quercetin 18.5.2.4 1,2-Benzisoxazole 18.5.2.5 Indazole 18.5.2.6 Imidazole 18.6 Pharmacophore-Based Approach 18.6.1 Concept and Applicability of Pharmacophore-Based Approach in Drug Discovery 18.6.2 Criteria for a Satisfactory Pharmacophore Model in Drug Discovery 18.6.2.1 Highlighting Functional Groups and Predictive Power 18.6.2.2 Perfect Stereochemical Complementarity Between a Ligand and a Protein Target 18.6.2.3 Distinguishing Between Agonists and Antagonists 18.6.2.4 Explaining Paradoxical Observations 18.6.2.5 Generation of New Chemical Entities 18.6.3 The Process for Developing a Pharmacophore Model 18.6.3.1 Select a Training Set of Ligands 18.6.3.2 Conformational Analysis 18.6.3.3 Molecular Superimposition 18.6.3.4 Abstraction 18.6.3.5 Validation 18.7 Fragment-Based Approach 18.7.1 Concept and Applicability of Fragment-Based Approach in Drug Discovery 18.7.2 Procedures of Fragment-Based Approach in Drug Discovery 18.7.2.1 Building Fragment Library 18.7.2.2 Performing Fragment Screening 18.7.2.3 Conducting Compound Optimization 18.8 Molecular Hybridization Approach 18.8.1 Concept and Applicability of Molecular Hybridization Approach in Drug Discovery 18.8.2 Classification of Molecular Hybrids 18.8.2.1 Conjugates 18.8.2.2 Cleavable Conjugates 18.8.2.3 Fused Hybrids 18.8.2.4 Merged Hybrids 18.8.3 Application of Molecular Hybrids 18.9 Activity-Based Proteomics Approach 18.9.1 Concept and Applicability of Activity-Based Proteomics Approach in Drug Discovery 18.9.2 Design of Activity-Based Probes for Drug Discovery 18.10 Omics-Based Approaches 18.10.1 Genomics in Drug Discovery 18.10.2 Transcriptomics in Drug Discovery 18.10.3 Proteomics in Drug Discovery 18.10.4 Metabolomics in Drug Discovery 18.10.5 Chemical Genomics or Chemogenomics 18.10.6 Microbiomics in Drug Discovery 18.10.7 Multi-omics in Drug Discovery 18.11 Network-Based Approach 18.11.1 Concept and Applicability of Network-Based Approach in Drug Discovery 18.11.2 Drug–Target Network 18.11.3 Disease–Drug Networks 18.12 Computation-Based Approaches 18.13 Similarity Approaches 18.13.1 Concept and Applicability of Ligand-Based Similarity Approach in Drug Discovery 18.13.2 Ligand-Based Interaction Fingerprint 18.13.3 Ligand-Based Similarity Ranking 18.13.4 Ligand-Based Virtual Screening 18.14 Label-Free Approach 18.14.1 Concept and Applicability of Label-Free Approach in Drug Discovery 18.14.2 Label-Free Techniques 18.14.2.1 Label-Free Biosensors 18.14.2.2 Label-Free Binding Techniques 18.14.2.3 Label-Free Cell Phenotypic Profiling 18.14.2.4 Label-Free Imaging Techniques 18.14.2.5 Label-Free Protein Quantification 18.15 Protein–Protein Interaction Approach 18.15.1 Concept and Applicability of Protein–Protein Interactions in Drug Discovery 18.15.2 Development of PPI Inhibitors 18.15.2.1 Small-Molecule Inhibitors of PPIs 18.15.2.2 Mimetics Targeting PPIs 18.15.2.3 Protein–Protein Docking 18.16 Big Data in Drug Discovery 18.17 Artificial Intelligence and Machine Learning in Drug Discovery 18.18 Deep Learning in Drug Design 18.19 Expression-Based Approaches References 19: Databases for Rational Design and Discovery of Multitarget Drugs 19.1 Information Spaces 19.1.1 Chemical Space 19.1.1.1 Theoretical Spaces 19.1.1.2 Empirical Spaces 19.1.2 Pharmacologic Space 19.1.3 Biological Space 19.1.4 Genomic Space 19.1.4.1 Genomic Data Production 19.1.4.2 Genomic Data Storage and Management 19.1.4.3 Genomic Data Analysis 19.1.4.4 Implementation of Genomic Data Insights to Build Products and Services 19.1.5 Chemogenomic Space 19.1.5.1 Basics of Chemogenomic Space 19.1.5.2 Approaches of Chemogenomic Space 19.1.5.3 Applications of Chemogenomic Space 19.2 Polypharmacology Databases 19.2.1 Polypharmacology Browser (PPB) 19.2.2 Polypharma 19.2.3 Computational Analysis of Novel Drug Repurposing Opportunities (CANDO) 19.2.4 QuartataWeb 19.2.5 SAMNet 19.2.6 Multiple Target Ligand Database (MTLD) 19.2.7 Multitarget Ligand Finder ePlatton 19.2.8 Promiscuous 2.0 19.2.9 The Drug Gene Pathway (DRUGPATH) for Mapping Polypharmacology 19.3 Pharmacology Databases 19.3.1 DrugBank 19.3.2 DGidb 19.3.3 The IUPHAR/BPS Guide to PHARMACOLOGY or IUPHAR Database (IUPHAR-DB) 19.4 Therapeutic Target Database 19.4.1 Therapeutic Target Database (TTD) 19.4.1.1 Validation of Primary Therapeutic Target 19.4.1.2 Mutation and Expression Profile of Target 19.4.1.3 Clinical Trial and Patent Protected Target 19.4.1.4 Regulator and Signaling Pathway of Target 19.4.2 Drug Target Commons (DTC) 19.4.3 Adverse Drug Reaction Classification System–Target Profile (ADReCS-Target) 19.5 Drug–Target Interaction Databases 19.5.1 BindingDB 19.5.2 SuperTarget 19.6 Genomic Databases 19.6.1 DisGeNET 19.6.2 Open Targets Platform (OTP) 19.6.3 Pharos 19.6.4 Comparative Toxicogenomics Database (CTD) 19.7 Protein Databases 19.7.1 Protein Data Bank (PDB) 19.7.2 Protein–Protein Interaction (PPI) Databases 19.7.3 Binding MOAD 19.7.4 Protein-Drug Interaction Database (PDID) 19.7.5 Protein Pharmacology Interaction Network (PhiN) 19.7.6 eMatchSite 19.8 Non-coding RNA Databases 19.8.1 MicroRNA Databases 19.8.1.1 MicroRNA Databases (Table 19.3a) 19.8.1.2 MicroRNA Target Gene Databases (Table 19.3b) 19.8.2 Long Non-coding RNA Databases (Table 19.4) 19.8.3 Circular RNA Databases (Table 19.5) 19.9 Human Disease Databases 19.9.1 MalaCards: The Human Disease Database 19.9.2 DisGeNET: A Database of Gene–Disease Associations 19.9.3 KEGG DISEASE Database 19.9.3.1 Disease Pathway Maps 19.9.3.2 Network Variation Maps 19.9.4 DNetDB: The Human Disease Network Database 19.9.5 HuVarBase: The Human Variant Database 19.9.6 ChEMBL-Neglected Tropical Disease (ChEMBL-NTD) 19.10 Biological Databases 19.10.1 Gene Ontology 19.10.2 KEGG: Kyoto Encyclopedia of Genes and Genomes 19.10.2.1 Systems Information 19.10.2.2 Genomic Information 19.10.2.3 Chemical Information 19.10.2.4 Health Information 19.10.3 PubChem’s BioAssay Database 19.11 Chemical Databases 19.11.1 PubChem 19.11.2 ChEMBL 19.11.3 STITCH 19.11.4 UniChem 19.11.5 ChemProt 19.11.6 ChemMapper 19.12 Prediction Programs 19.12.1 FastTargetPred Program 19.12.2 SEABED 19.12.3 LigBuilder V3 Drug Design Program 19.12.4 C-SPADE 19.12.5 DrugGenEx-Net (DGE-NET) References 20: Methods for Rational Design and Discovery of Multitarget Drugs 20.1 High-Throughput Screening Assays 20.1.1 Step 1: Assay Plate Preparation 20.1.2 Step 2: Reaction Observation 20.1.3 Step 3: Automation Systems 20.1.4 Step 4: Experimental Design and Data Analysis 20.1.4.1 Quality Control 20.1.4.2 Hit Selection 20.1.5 Techniques for Increased Throughput and Efficiency 20.1.6 PubChem BioAssay on HTS 20.2 Molecular Docking Methods 20.2.1 Molecular Docking 20.2.1.1 Docking Approaches 20.2.1.2 Mechanics of Docking 20.2.1.3 Docking Assessment 20.2.1.4 Applications 20.2.2 Inverse Docking 20.2.2.1 In Silico Screening 20.2.2.2 Cell Viability Assay 20.3 Target and Compound Similarity-Based Methods 20.3.1 3D Shape Similarity Methods 20.3.1.1 Atomic Distance-Based Descriptors 20.3.1.2 Atom-Centered Gaussian-Based Shape Similarity Methods 20.3.1.3 Surface-Based 3D Shape Similarity Comparison Methods 20.3.2 Application of Shape Similarity Methods in Drug Discovery 20.3.2.1 Application in Virtual Screening 20.3.2.2 Applications in Protein Structure Comparison 20.3.3 Similarity Ensemble Approach (SEA) 20.3.4 Bioactivity Profile Similarity Search 20.3.5 Binding-Site Similarity 20.4 X-Ray Crystallography 20.4.1 Basics of X-Ray Crystallography 20.4.2 Workflow of X-Ray Crystallography 20.4.2.1 Ligand Identification 20.4.2.2 Crystallizing the Target 20.4.2.3 Preparation of Crystals of Complexes 20.5 Machine Learning 20.5.1 Basics of Machine Learning Technologies 20.5.2 Machine Learning Methods to Drug Discovery 20.5.2.1 Support Vector Machines 20.5.2.2 Random Forest Algorithm 20.5.2.3 Multilayer Perception (MLP) 20.5.2.4 Deep Learning 20.5.3 ML in Drug Design Applications 20.5.3.1 Homology Modeling/Prediction of Protein Folding 20.5.3.2 Target Identification 20.6 Prediction of Protein Folding 20.6.1 Prediction of Protein–Protein Structure 20.6.1.1 Prophecy of Protein–Protein Interactions 20.6.1.2 Hit Discovery 20.7 Drug Repurposing 20.7.1 Virtual Screening 20.7.1.1 High-Throughput Virtual Screening and Scoring in Molecular Docking Techniques 20.7.1.2 Hit to Lead 20.8 QSAR Analysis 20.8.1 De Novo Drug Architecture 20.8.1.1 Lead Optimization 20.8.2 Toxicity 20.8.2.1 ML in e-Resources for Drug Discovery 20.9 Information Mining 20.9.1 Data Mining 20.9.2 Text Mining 20.9.3 Information-Mining Methods References 21: Exemplary Protocols of Rational Design of Multitarget Drugs 21.1 Creative Vector Analysis for Identifying MTDs 21.1.1 Step 1: Construction of an Experimental Training Set: Multi-kinase Ligands 21.1.2 Step 2: Construction of a Docking Training Set: Multi-kinase Ligands 21.1.3 Step 3: Construction of an Experimental Evaluation Set: DUD 21.1.4 Step 4: Virtual Library of Ligands for MS 21.1.4.1 Selection and Construction of the Virtual Library 21.1.4.2 Molecular Docking 21.1.4.3 Cheminformatics Analysis 21.1.5 Step 5: Construction of the Multitarget Index 21.1.5.1 Order of a Ligand 21.1.5.2 Force of a Ligand 21.1.5.3 Binding Capacity and Total Multitarget Capacity 21.1.5.4 Index Standardization, Definition, and Interpretation 21.1.5.5 A Second Multitarget Index 21.1.5.6 Defining of a Multitarget Ligand 21.1.5.7 Multitarget Potency and Selectivity 21.2 Systematic Assessment of Fragment Identification for Multitarget Drug Design 21.2.1 Step 1: Pre-evaluation of the Chemical Ligand Space of the Protein Targets 21.2.2 Step 2: Primary Screening of the Fragment Library 21.2.3 Step 3: Hit Validation 21.2.4 Step 4: Substructure Search to Validate Multitargeting Property 21.2.5 Important Notes from This Systematic Model Study 21.2.5.1 Fragment-Based Approaches Can Be Used for MTD Design 21.2.5.2 The Size of the Compounds Matters 21.2.5.3 The Size and the Composition of the Library Matters 21.2.5.4 The Screening Technology Matters 21.3 Scaffold-Based Molecular Hybrid Approaches for Rational Design of MTDs for Alzheimer’s Disease 21.3.1 Hydroquin: Benzenediol–Berberine Hybrids 21.3.2 Memoquin: Benzoquinone–Polyamine Hybrid 21.3.3 Curcumin 21.3.4 Tacrine 21.3.4.1 Tacrine–Benzylamino-3-Pyridyl Hybrid 21.3.4.2 Tacrine Dimer: Tacrine–Tacrine Hybrid 21.3.4.3 BW284c51 and Ambenonium: Tacrine Dimer–Chelating Group Hybrid 21.3.4.4 Tacrine Dimer–Cystamine Hybrid 21.3.4.5 Tacrine–Ferulic Acid Hybrid 21.3.4.6 Tacripyrines: Tacrine–Dihydropyridine Hybrid 21.3.4.7 Tacrine–Caffeic Acid Hybrids 21.3.4.8 Tacrine–Phenylthiazole Hybrids 21.3.5 Galanthamine–Memantine Hybrid 21.3.6 Bivalent Β–Carboline Derivatives 21.3.7 Benzofuran-Based Hybrid 21.3.8 AChE Inhibitor–MAO Inhibitor Hybrids 21.3.8.1 Donepezil–PF9601N Hybrid 21.3.8.2 Donepezil–N-(5benzyloxy-1-Methyl-1H-Indol-2-Yl)Methyl-N-Methylprop-2-Yn-1-Amine 21.3.8.3 Donepezil–Benzylidene–Indanone Pharmacophore Hybrid 21.3.9 Resveratrol–Catechol Pharmacophore References Index