Bioinformatics, Computational Chemistry and AI in Drug Innovation

Advances and Applications
1. Auflage 2026
ISBN: 978-1-032-73301-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 264 Seiten, Format (B × H): 210 mm x 280 mm, Gewicht: 453 g

This book comprehensively examines the applications of bioinformatics, computational chemistry and artificial intelligence in the field of drug discovery and innovation. It provides foundational insights into bioinformatics and its applications, from cutting-edge advancements in computational molecular phylogeny, structural bioinformatics, and metabolic computing to biological databases and data mining. Additionally, the book covers critical aspects of data storage, retrieval, database structure, and annotation, providing a robust foundation for understanding the complexities of biological data management. It discusses computational protein modeling, molecular docking, pharmacophore modeling, quantitative structure-activity relationships, and innovative approaches for drug target identification. The chapters explore protein-ligand interactions, molecular dynamics simulations, density function theory, and the strategic endeavor of drug repurposing. Towards the end, the book discusses Quality by Design (QbD) in drug formulation, artificial intelligence, and machine learning's transformative influence on drug discovery, computational tools for estimating pharmacokinetic parameters, and the conceptual underpinnings of computational genomics. This book will is useful for students, professionals and researchers in the fields of pharmaceutical Sciences, life sciences, pharmaceuticals, biotechnology and computational biology.

Key feature

· Discuses applications of bioinformatics, computational chemistry, and artificial intelligence in drug discovery and innovation

· Covers essential aspects of data storage, retrieval, database structure, and annotation for managing complex biological data.

· Reviews molecular docking, pharmacophore modeling, and quantitative structure-activity relationships for drug designing.

· Explores the transformative influence of artificial intelligence and machine learning in drug discovery.

· Emphasizes Quality by Design (QbD) principles, highlighting the importance of precision and quality in drug formulation design.

Zielgruppe

Academic, Postgraduate, and Professional Reference

Autoren/Hrsg.

Dixit, Anshuman

Kashaw, Sushil Kumar

Nema, Priyanshu

Agarwal, Shivangi

Fachgebiete

• Naturwissenschaften Chemie Chemie Allgemein Chemometrik, Chemoinformatik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Pharmakologie, Toxikologie
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie Medizinische Biotechnologie

Inhaltsverzeichnis

1 An Overview of Bioinformatics and Its Application 2 Structural Bioinformatics 3 Metabolic Computing 4 Biological Databases and Data mining 5 Data Storage and Retrieval, Database Structure and Annotation 6 Computational Protein Modelling, Refinement, Validation and its Application 7 Molecular Docking Guided Drug Design & Discovery 8 Pharmacophore Modeling: A Cornerstone of Modern Drug Design 9 Quantitative Structure Activity Relationship in Drug Design 10  Computational Approaches for Drug Target Identification 11 Protein-Ligand Interaction and Molecular Dynamic Simulation 12 Density Function theory and its applications 13 Drug Repurposing 14 Biodiversity, Ecological and Immuno-Informatics 15 Quality by Design in Drug Formulation Design 16 In Silico Designing of Vaccines: Methods, Tools, and Their Limitations 17 Artificial Intelligence and Machine Learning in Drug Discovery 18 Pharmacokinetic parameters estimation by computational tools19 Computational Genomics concept and its utilization

Über Autor(innen)

Prof. Sushil K. Kashaw is a Professor and Raman Postdoctoral Fellow in the Department of Pharmaceutical Sciences at Dr. H.S. Gour University (A Central University) in Sagar, M.P. He has previously served as an academic and executive council member of the university. Prof. Kashaw completed his B. Pharm (1998), M. Pharm (2000), and PhD (2009) from Dr. Harisingh Gour University. His professional experience includes research positions at the Central Drug Research Institute, Lucknow, where he worked as a CSIR-SRF, and at Wayne State University, Detroit, USA, where he held the position of Raman Postdoctoral Research Fellow. He has an impressive academic record, with 150 high-impact research papers, authored nine books, sixr book chapters, and the successful completion of five sponsored research projects, along with four granted patents. Prof. Kashaw has also delivered 45 invited lectures, chaired 30 scientific sessions, presented 40 papers at conferences, and developed 10 e-contents for CEC-MHRD. He has received several awards, including the Raman PDF, Outstanding Oral Presentation Award, Young Scientist Award by APP, Best Teacher Award in Pharm. Chemistry by APTI-M.P. branch, Research Excellence Award by the Institute of Scholars, and the Best Researcher Award by Nirali Publication in association with APTI, among others. Prof. Kashaw is a life member of numerous learned societies and has organized many training programs and conferences. His area of expertise lies in molecular modeling and medicinal chemistry.

Dr. Anshuman Dixit holds a master's degree in Pharmaceutical Chemistry from Dr. H. S. Gour University, Sagar, M.P, India, and earned his doctorate from the Central Drug Research Institute (CDRI) in 2007. Following this, he pursued postdoctoral research at the Center for Bioinformatics at the University of Kansas, Lawrence, USA, from 2007 to 2011. Currently, Dr. Dixit serves as a senior scientist at the Institute of Life Sciences in Bhubaneswar, Odisha, India. He boasts extensive research experience in drug discovery and bioinformatics and has a remarkable publication record, with over 90 peer-reviewed publications, 4 book chapters, and 2 international patents to his name. Dr. Dixit also contributes as an associate editor and editorial board member for various academic journals. His current research interests center around drug combinatorial strategies using AI, network pharmacology, and protein structure-function relationships.

Dr. Shivangi Agarwal currently serves as a Postdoctoral Associate at the University of Illinois at Chicago, USA, where her work primarily revolves around the analysis of Next Generation Sequencing data derived from various cancer types. She earned her Ph.D. in Computational Biology and Bioinformatics from the Department of Pharmaceutical Sciences at Dr. Harisingh Gour University, Sagar, M.P., under the guidance of Dr. Sushil K. Kashaw. Dr. Agarwal also holds a master's degree in Pharmaceutical Chemistry and was honored with a Gold Medal in 2014. Her academic achievements include twenty research publications and the publication of one book. She was granted the CSIR Foreign Travel Grant, enabling her to present her research at the FIP World Congress of Pharmacy and Pharmaceutical Sciences in the United Arab Emirates in 2019. In addition, she received the prestigious "Young Scientist Award" for an outstanding research paper during the 35th MP Young Scientist Congress held at Shri G.S. Institute of Technology and Science, Indore, in 2020. Dr. Agarwal's research interests encompass cancer genomics, computational biology and bioinformatics, as well as drug design and discovery.

Mr. Priyanshu Nema is a UGC-Research Scholar in the Department of Pharmaceutical Sciences at Dr. Harisingh Gour University (A Central University), Sagar, Madhya Pradesh. He completed his Bachelor of Pharmacy (B. Pharm) in 2020 and Master of Pharmacy (M. Pharm) in Pharmaceutical Chemistry in 2022 from the same institution. Currently pursuing his Ph.D. since 2022, Mr. Nema has demonstrated a strong academic and research background. He qualified national-level competitive exams, securing AIR 1517 in GPAT and AIR 1004 in NIPER JEE in 2020. His research interests include molecular modelling, drug design, medicinal chemistry, and in-silico studies focusing on diabetes-related targets. He is also proficient in protein modelling, computational biology, and bioinformatics. Mr. Nema has authored 12 high-impact research and review publications and contributed to 3 book chapters. He serves as an editor for a CRC Press Taylor & Francis Group book titled “Bioinformatics, Computational Chemistry and AI in Drug Innovation: Advances and Applications.” He has presented 15 oral and poster presentations at various national and international conferences. In recognition of his research potential, he was honored with the Young Research Scholar Award in December 2024 by the Association of Pharmacy Profession. His work reflects a deep commitment to excellence in pharmaceutical sciences and computational drug discovery.