Computational Neuropharmacology

Bhupendra Prajapati, PhD, is a professor in the Department of Pharmaceutics, Shree S.K. Patel College of Pharmaceutical Education and Research, Ganpat University, Gujarat, India, with over 20 years of research and teaching experience. He has published over 100 research and review papers in national and international journals and 20 book chapters, edited three books, and serves as an editor and reviewer of several journals. In addition to this work, he has published two Indian patents and has three applications under evaluation. Alok Tripathi, PhD, is a professor and the Head of the Department of Pharmacology, Era College of Pharmacy, Era University, Gujarat, India, with over 14 years of teaching and research experience. He has published 40 research papers in various national and international journals, five book chapters, and one book and serves as a reviewer and editorial board member for several international journals. His research focuses on diabetes and its complications, drug interaction, and neurodegenerative disorders. Rishabha Malviya, PhD, is an associate professor in the Department of Pharmacy, School of Medical and Allied Sciences, Galgotias University, India, with over 12 years of research and teaching experience. He has published 28 books and over 150 research papers in national and international journals and has been granted 10 patents, with an additional 40 under review. His research interests include formulation optimization, nanoformulation, targeted drug delivery, artificial intelligence in healthcare, and characterization of natural polymers as pharmaceutical excipients. Lucy Mohapatra, PhD, is an assistant professor in the Department of Pharmacology, Amity Institute of Pharmacy, Amity University Uttar Pradesh, India, with eight years of teaching and research experience. She has published over 17 research papers in various national and international journals, five book chapters, and four patents and serves as a reviewer and editorial board member for several journals. Her research interests include metabolic disorders, mitochondrial disorders, pharmacology, and pathophysiology.

• Foreword xixPreface xxiPart 1: Fundamentals of Computational Neuropharmacology 11 Basic Principles of Computational Neuropharmacology: Neuroscience Meeting Pharmacology 3Lucy Mohapatra, Alok S. Tripathi, Deepak Mishra, Alka and Sambit Kumar ParidaAbbreviations 41.1 Introduction 51.2 Basics of Computational Neuropharmacology 61.3 Multiple Aspects of Computational Neuropharmacology 111.4 Recent Developments in Computational Neuropharmacology 181.5 Limitations of Computational Neuropharmacology 211.6 Conclusion 22References 222 Neuropharmacology in the Molecular Epoch 31Neelakanta Sarvashiva Kiran, Chandrashekar Yashaswini and Bhupendra G. PrajapatiList of Abbreviations 322.1 Introduction 332.2 History of Neuropharmacology 342.3 Neurochemical Interactions 352.4 Molecular Pharmacology of Neuronal Receptors 372.5 Neuropharmacological Drugs 462.6 Impact of Biotechnology of Neuropharmacology 502.7 Future Research and Perspectives 552.8 Conclusion 56Acknowledgments 57References 573 Basics of Theoretical Neuroscience 67Anil P. Dewani, Deepak S. Mohale, Alok S. Tripathi and Naheed Waseem A. SheikhList of Abbreviations 673.1 Introduction 683.2 Properties of Neurons and Neuronal Signaling 703.3 Recording Neuronal Responses 723.4 Neural Encoding and Neuronal Decoding 743.5 Neuronal Network Models 763.6 Learning and Synaptic Plasticity 783.7 Conclusion 79References 804 In Silico Modeling of Drug–Receptor Interactions for Rational Drug Design in Neuropharmacology 87Princy Shrivastav, Bhupendra Prajapati, Chandni Chandarana and Parixit PrajapatiAbbreviations 884.1 Introduction 884.2 Drug–Receptor Interactions 934.3 In Silico Methods for Modeling Drug–Receptor Interactions 1014.4 Applications of In Silico Modeling in Neuropharmacology 1154.5 Case Studies 1164.6 Conclusion 120References 1215 Computational Attitudes in Counselling Psychology 127Bharat Mishra, Farha Deeba Khan, Archita Tiwari and Anitta JosephList of Abbreviations 1285.1 Introduction 1295.2 Theoretical Foundations of Computational Attitude 1395.3 Empirical Evidence and Efficacy of Computational Counselling 1495.4 Ethical and Legal Considerations 1535.5 Future Directions and Possibilities 1535.6 Conclusion 154References 1546 Computational Psychiatry: Addressing the Gap Between Pathophysiology and Psychopathology 159Jignasha Derasari Pandya and Bhupendra PrajapatiList of Abbreviations 1606.1 Introduction 1606.2 Roadmap of Conventional to Modern Evolution Towards Mental (Psychological) Illness 1656.3 Pathophysiology of Mental Illness 1676.4 Psychopathology 1746.5 Computational Psychiatry (CP) 1826.6 Computational Psychiatry: An Advanced Version Links Pathology and Psychopathology 1916.7 Conclusion 193References 1937 Computational Neuropharmacology in Psychiatry 207Amol D. Gholap, Pankaj R. Khuspe, Deepak K. Bharati, Sagar R. Pardeshi, Mohammad Dabeer Ahmad, ABM Sharif Hossain, Bhupendra G. Prajapati and Md. FaiyazuddinList of Abbreviations 2087.1 Introduction 2087.2 Need for Computational Neuropharmacology in Psychiatry 2097.3 Data-Driven Computational Approaches in Psychiatry 2117.4 Role of Diagnostic Classification 2127.5 Machine Learning and Diagnostic Precision 2137.6 The Challenges of Treatment Response Prediction 2147.7 Future Implications and Ethical Considerations 2167.8 Machine Learning for Informed Decisions 2177.9 Network Analysis: Unraveling Symptom Dynamics 2187.10 Theory-Driven Computational Approaches: Integrating Knowledge and Data 2217.11 Biophysically Realistic Neural Network Models: Bridging the Gap Between Biology and Computation 2227.12 Bayesian Models 2257.13 Combining Data-Driven and Theory-Driven Computational Approaches 2267.14 Conclusion 228References 229Part 2: Clinical Aspects of Computational Neuropharmacology 2458 Computational Attitudes to Drug Discovery in Neurohumoral Transmission and Signal Transduction 247Lucy Mohapatra, Alok S. Tripathi, Deepak Mishra, Alka, Sambit Kumar Parida and Bhupendra Gopalbhai PrajapatiAbbreviations 2488.1 Introduction 2488.2 Neurohumoral Transmission and Signal Transduction 2508.3 Computational Approach in Creating Neurohumoral and Synaptic Models 2578.4 Primitive Computational Models 2618.5 Conclusion 263References 2649 Computational Attitude to Drug Discovery in Parkinson’s Disease 271Chitra Vellapandian, Ankul Singh S., Swathi Suresh and Bhupendra PrajapatiList of Abbreviations 2729.1 Introduction 2739.2 PD and Drug Development 2759.3 Animal Models and Translational Discovery 2769.4 Pathophysiology 2789.5 Validated Biomarkers 2799.6 Computational Drug Discovery 2829.7 Outcomes From Gene Ontology and KEGG Analysis 2849.8 Conclusion 299Acknowledgments 300References 30010 Computational Attitudes to Drug Discovery in Epilepsy 313Shama Mujawar, Aarohi Deshpande, Avni Bhambure, Shreyash Kolhe and Bhupendra PrajapatiList of Abbreviations 31410.1 Introduction 31410.2 Traditional Drug Discovery Approaches for Epilepsy 31510.3 Computer Simulations in Understanding and Optimizing Drug Efficacy 31910.4 Development of Computational Models 32110.5 Computational Models for Predicting Effects on Seizure Activity 32310.6 Data Integration and Analysis in Epilepsy Research 32510.7 Challenges and Future Directions 32810.8 Conclusion 330Acknowledgments 331References 33111 Computational Attitudes to Drug Discovery in Alzheimer’s Disease 335Shubhrat Maheshwari, Aditya Singh, Amita Verma, Juber Akhtar, Jigna B. Prajapati, Sudarshan Singh and Bhupendra PrajapatiList of Abbreviations 33611.1 Introduction 33611.2 Alzheimer’s Disease 33911.3 Computational Attitudes to Drug Discovery 34111.4 Applications of Computational Attitudes to Drug Development Process 34311.5 Conclusion 345References 34512 The Integration of Molecular Docking and Machine Learning in Drug Discovery for Neurological Disorders 349Aditya Singh, Shubhrat Maheshwari, Jigna B. Prajapati, Juber Akhtar, Syed Misbahul Hasan, Amita Verma, Sudarshan Singh and Bhupendra PrajapatiAbbreviations 35012.1 Introduction 35112.2 Neurodegenerative Disease 35512.3 Molecular Docking 35712.4 Machine Learning in Drug Discovery 36112.5 Random Forest 36612.6 Naïve Bayesian 36612.7 Support Vector Machine 36712.8 Conclusion 368References 36913 Computational Attitudes to Drug Discovery in Autism Spectrum Disorder 375Himani Nautiyal, Shubham Dwivedi, Silpi Chanda and Raj Kumar TiwariList of Abbreviations 37613.1 Introduction 37613.2 Clinical, Genetic, and Molecular Heterogeneity in Autism Spectrum Disorder 38713.3 The Necessity of Drug Discovery 39013.4 Computational Model for Drug Discovery 39113.5 Importance of Multiomics and Endophenotyping-Based Methods Toward Precision Medicine 39213.6 Network-Based Approach for Diseases/Drug Modeling 39313.7 Drug Repurposing Candidates for Treatment of ASD Using Bioinformatic Approaches 39513.8 Conclusion and Future Prospective 398Acknowledgment 398References 39914 Computational Approaches to Drug Discovery in Depression 409Kalpesh Ramdas Patil, Aman B. Upaganlawar, Akhil A. Nagar and Kuldeep U. BansodList of Abbreviations 41014.1 Introduction 41114.2 Types of Depressive Disorders 41114.3 Hypotheses and Pathways of Depression 41214.4 Receptors in Depression 41514.5 Computational Approaches to Depression 41714.6 Network Pharmacology of Depression 42614.7 Conclusion 429References 42915 Computational Attitudes to Drug Discovery in Anxiety 437Meenakshi Attri, Asha Raghav, Piyush Vatsha, Mohit Agrawal, Manmohan Singhal, Hema Chaudhary, Nalini Kanta Sahoo and Bhupendra PrajapatiList of Abbreviations 43815.1 Introduction 43915.2 Computational Approaches for Drug Discovery 43915.3 Ligand-Based Techniques 44315.4 Pharmacophore 44415.5 Structure-Based Methods for Screening 44715.6 Ai 44915.7 Machine Learning Algorithms for Anxiety Disorder Detection and Prediction 45015.8 A Review of the Literature on Machine Learning Approaches for Anxiety-Related Disorders 45315.9 Molecular Dynamic Simulation 45415.10 Future Prospective 46015.11 Conclusion 470References 471Index 483