In Silico Drug Design
Academic Press Inc (Verlag)
978-0-12-816125-8 (ISBN)
Dr. Kunal Roy is Professor & Ex-Head in the Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India (https://sites.google.com/site/kunalroyindia). He has been a recipient of Commonwealth Academic Staff Fellowship (University of Manchester, 2007) and Marie Curie International Incoming Fellowship (University of Manchester, 2013) and a former visiting scientist of Istituto di Ricerche Farmacologiche "Mario Negri" IRCCS, Milano. Italy. The field of his research interest is Quantitative Structure-Activity Relationship (QSAR) and Molecular Modeling with application in Drug Design, Property Modeling and Predictive Ecotoxicology. Dr. Roy has published more than 450 research articles (ORCID: http://orcid.org/0000-0003-4486-8074) in refereed journals (current SCOPUS h index 57; total citations to date more than 17500). He has also coauthored three QSAR-related books (Academic Press and Springer), edited thirteen QSAR books (Springer, Academic Press, and IGI Global), and published twenty five book chapters. Dr. Roy is the Co-Editor-in-Chief of Molecular Diversity (Springer Nature) and an Associate Editor of Computational and Structural Biotechnology Journal (Elsevier). Dr. Roy serves on the Editorial Boards of several International Journals including (1) European Journal of Medicinal Chemistry (Elsevier); (2) Journal of Molecular Graphics and Modelling (Elsevier); (3) Chemical Biology and Drug Design (Wiley); (4) Expert Opinion on Drug Discovery (Informa). Apart from this, Prof. Roy is a regular reviewer for QSAR papers in different journals. Prof. Roy has been a participant in the EU funded projects nanoBRIDGES and IONTOX apart from several national Government funded projects (UGC, AICTE, CSIR, ICMR, DBT, DAE). Prof. Roy has recently been placed in the list of the World's Top 2% science-wide author database (whole career data) (World rank 52 in the subfield of Medicinal & Biomolecular Chemistry) (Ioannidis, John P.A. (2025), "August 2025 data-update for "Updated science-wide author databases of standardized citation indicators", Elsevier Data Repository, V8, link: http://doi.org/10.17632/btchxktzyw.8).
Section 1. Introduction
1. Drug Repositioning: New Opportunities for Older Drugs
2. Computational Drug Design Methods – Current and Future Perspectives
Section 2. Theoretical Background and Methodologies
3. In Silico Drug Design Methods for Drug Repurposing
4. Computational Drug Repurposing for Neurodegenerative Diseases
5. Repurposed molecules: A New Hope in Tackling Neglected Infectious Diseases
6. Molecular Docking: A Structure-Based Approach for Drug Repurposing
7. Data Science Driven Drug Repurposing for Metabolic Disorders
8. Data-driven Systems Level Approaches for Drug Repurposing: Combating Drug Resistance in Priority Pathogens
9. In Silico Repurposing of Cell Cycle Modulators for Cancer Treatment
10. Proteochemometric Modeling for Drug Repositioning
11. Drug Repurposing from Transcriptome Data: Methods and Applications
12. Omics-driven Knowledge Based Discovery of Anthelmintic Targets and Drugs
13. Analysis of Chemical Spaces: Implications for Drug Repurposing
Section 3. Examples and Case Studies
14. Drug Repurposing in Search of Anti-Infectives: Need of the Hour in the Multi-Drug Resistance Era!
15. Application of In Silico Drug Repurposing in Infectious Diseases
16. In Silico Modeling of FDA-approved Drugs for Discovery of Anti-candida Agents: A Drug Repurposing Approach
17. In silico Modeling of FDA-approved Drugs for Discovery of Anticancer Agents: A Drug Repurposing Approach
18. Tackling Lung Cancer Drug Resistance using Integrated Drug Repurposing Strategy
19. In Silico Modeling of FDA-approved Drugs for Discovery of Anti-cancer Agents: A Drug Repurposing Approach
20. Drug Repurposing by Connectivity Mapping and Structural Modeling
21. In Silico Modeling of FDA-approved Drugs for Discovery of Therapies Against Neglected Diseases: A Drug Repurposing Approach
22. Ascorbic Acid is a Potential Inhibitor of Collagenases – In Silico and In Vitro Biological Studies
23. Bioinformatic Approaches for Repurposing and Repositioning Antibiotics, Antiprotozoals and
Antivirals
Section 4. Tools and databases
24. In Silico Databases and Tools for Drug Repurposing
25. An Overview of Computational Methods, Tools, Servers and Databases for Drug Repurposing
26. In silico Drug Repurposing for MDR Bacteria: Opportunities and Challenges
27. Drug Repositioning Strategies to Explore New Candidates Treating Prostate Cancer
28. PDID: Database of Experimental and Putative Drug Targets in Human Proteome
| Erscheinungsdatum | 02.03.2019 |
|---|---|
| Verlagsort | San Diego |
| Sprache | englisch |
| Maße | 191 x 235 mm |
| Gewicht | 1790 g |
| Themenwelt | Medizin / Pharmazie ► Medizinische Fachgebiete ► Pharmakologie / Pharmakotherapie |
| Medizin / Pharmazie ► Pharmazie | |
| Technik | |
| ISBN-10 | 0-12-816125-6 / 0128161256 |
| ISBN-13 | 978-0-12-816125-8 / 9780128161258 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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