Computational Methods in Drug Discovery and Repurposing for Cancer Therapy

Computational Methods in Drug Discovery and Repurposing for Cancer Therapy provides knowledge about on-going research as well as computational approaches for drug discovery and repurposing for cancer therapy. It also provides detailed descriptions about target molecules, pathways and their inhibitors for easy understanding and applicability. The book discusses tools and techniques such as integrated bioinformatics approaches, systems biology tools, molecular docking, computational chemistry, artificial intelligence, machine learning, structure-based virtual screening, biomarkers, and transcriptome; those are discussed in the context of different cancer types, such as colon, glioblastoma, endometrial, retinoblastoma, among others. It is a valuable resource for researchers, students and member of the biomedical and medical fields who want to learn more about the use of computational modeling to better tailor the treatment for cancer patients. Discusses in silico remodeling of effective phytochemical compounds for discovering improved anti-cancer agents for substantial/significant cancer therapy Covers potential tools of bioinformatics that are applied towards discovering new targets by drug repurposing and strategies to cure different types of cancers Demonstrates the significance of computational and artificial intelligence approaches in anticancer drug discovery Explores how these various advances can be integrated into a precision and personalized medicine approach that can eventually enhance patient care INDICE: 1. Computational approaches for anti-cancer drug design 2. Molecular modeling approach in cancer drug therapy 3. Discovery of anticancer therapeutics: Computational chemistry and artificial intelligence assisted approach 4. Artificial intelligence in oncological therapies 5. Approach of artificial intelligence in colorectal cancer and in precision medicine 6. Artificial intelligence in breast cancer: An opportunity for early diagnosis 7. Quantitative structure- activity relationship and its application to cancer therapy 8. Structure-based virtual screening strategy for the identification of novel great wall kinase inhibitors 9. Strategies for Drug Repurposing 10. Principles of computational drug designing and drug repurposing - an algorithmic approach 11. Drug discovery and repositioning for glioblastoma multiforme and low-grade astrocytic tumours 12. Repurposing of phytocompounds-derived novel bioactive compounds possessing promising anti-cancer and cancer therapeutic efficacy through molecular docking, MD simulation and drug-likeness/ADMET studies 13. Old drugs and new opportunities - Drug repurposing in colon cancer prevention 14. Repurposing cardiac glycosides as potent immune System modulators in cancer therapy 15. Systems biology tools for the identification of potential drug targets and biological markers effective for cancer therapeutics 16. Role of Human Body Fluid Biomarkers in Liver Cancer: A systematic review 17. Study on biomarkers in endometrial cancer using transcriptome data: A machine learning approach 18. Multifaceted functions of PIWI/piRNA complex in cancer and as a therapeutic target for retinoblastoma 19. Emerging role of biosimilars: Focus on bevacizumab and hepatocellular carcinoma 20. Integrated computational approaches to aid precision medicine for cancer therapy: Present scenario and future prospects

• ISBN: 978-0-443-15280-1
• Editorial: Academic Press
• Encuadernacion: Rústica
• Fecha Publicación: 01/03/2023
• Nº Volúmenes: 1
• Idioma: Inglés