Sapna jain dabade (8 resultados)

Condición: New.

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 188 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book presents an integrated computational approach for antifungal drug discovery targeting N-myristoyltransferase (NMT) in Candida albicans, a promising therapeutic target against antifungal resistance. It highlights the application of computer-aided drug design (CADD) techniques, particularly QSAR modeling using Genetic Algorithm-Stepwise Multiple Linear Regression (GA-SMLR) and molecular docking studies, to identify and optimize novel NMT inhibitors. The study evaluates bisamidine, coumarin, and triazole derivatives, revealing key molecular descriptors, structural features, and binding interactions responsible for antifungal activity. Rigorous internal and external validation ensures the statistical robustness and predictive reliability of the QSAR models. By combining structure-activity relationships with protein-ligand interaction analysis, the book provides valuable insights into rational drug design, lead optimization, and antifungal therapeutic development. It serves as a practical resource for researchers and students in medicinal chemistry, pharmaceutical sciences, computational biology, and antifungal drug discovery. …

Paperback. Condición: new. Paperback. The book presents an integrated computational approach for antifungal drug discovery targeting N-myristoyltransferase (NMT) in Candida albicans, a promising therapeutic target against antifungal resistance. It highlights the application of computer-aided drug design (CADD) techniques, particularly QSAR modeling using Genetic Algorithm-Stepwise Multiple Linear Regression (GA-SMLR) and molecular docking studies, to identify and optimize novel NMT inhibitors. The study evaluates bisamidine, coumarin, and triazole derivatives, revealing key molecular descriptors, structural features, and binding interactions responsible for antifungal activity. Rigorous internal and external validation ensures the statistical robustness and predictive reliability of the QSAR models. By combining structure-activity relationships with protein-ligand interaction analysis, the book provides valuable insights into rational drug design, lead optimization, and antifungal therapeutic development. It serves as a practical resource for researchers and students in medicinal chemistry, pharmaceutical sciences, computational biology, and antifungal drug discovery. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Taschenbuch. Condición: Neu. Computer-Aided Antifungal Drug Design | Potential N-Myristoyltransferase (NMT) Inhibitors of Candida albicans | Sapna Jain Dabade (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630121810 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book presents an integrated computational approach for antifungal drug discovery targeting N-myristoyltransferase (NMT) in Candida albicans, a promising therapeutic target against antifungal resistance. It highlights the application of computer-aided drug design (CADD) techniques, particularly QSAR modeling using Genetic Algorithm-Stepwise Multiple Linear Regression (GA-SMLR) and molecular docking studies, to identify and optimize novel NMT inhibitors. The study evaluates bisamidine, coumarin, and triazole derivatives, revealing key molecular descriptors, structural features, and binding interactions responsible for antifungal activity. Rigorous internal and external validation ensures the statistical robustness and predictive reliability of the QSAR models. By combining structure-activity relationships with protein-ligand interaction analysis, the book provides valuable insights into rational drug design, lead optimization, and antifungal therapeutic development. It serves as a practical resource for researchers and students in medicinal chemistry, pharmaceutical sciences, computational biology, and antifungal drug discovery. 188 pp. Englisch. …