Multi-scale approaches in drug discovery : from empirical knowledge to in silico experiments and back /

Drug discovery is an expensive, time-consuming process and the modern drug discovery community is constantly challenged not only with discovering novel bioactive agents to combat resistance from known diseases and fight against new ones, but to do so in a way that is economically effective. Advances...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Speck-Planche, Alejandro (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam, Netherlands : Elsevier, 2017.
Temas:
Drug development.
Drug Discovery
M�edicaments > D�eveloppement.
MEDICAL > Pharmacology.
Drug development
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 3.2.1. Creation of the Data Set and Calculation of the Molecular Descriptors3.2.2. Creation of the mtk-QSBER Model; 3.3. RESULTS AND DISCUSSION; 3.3.1. mtk-QSBER Model; 3.3.2. Molecular Descriptors and Their Meanings From a Physicochemical Point of View; 3.3.3. Contribution of Fragments to Multiple Biological Effects; 3.3.4. In Silico Design and Screening of Potentially Efficient and Safe Anti-HIV Molecules; 3.4. CONCLUSIONS; ACKNOWLEDGMENTS; REFERENCES; 4
  • Alkaloids From the Family Menispermaceae: A New Source of Compounds Selective for [beta]-Adrenergic Receptors; 4.1. INTRODUCTION.
  • 1.5. DETERMINATION OF HEAT CAPACITY CHANGES [delta]CP1.6. THE ACCURACY AND RELEVANCE OF ISOTHERMAL TITRATION CALORIMETRY DATA; 1.7. PROTEIN-LIGAND COMPLEX FORMATION: WHAT CAN THERMODYNAMIC DATA TELL ABOUT A GOOD STARTING POINT FOR OPTIMIZATION; 1.8. OPTIMIZATION: GO FOR ENTHALPY OR ENTROPY; 1.9. WHAT DOES AN H-BOND OR A LIPOPHILIC CONTACT CONTRIBUTE; 1.10. PAIN IN THE NECK: H-BONDS AND LIPOPHILIC CONTACTS ARE MUTUALLY DEPENDENT; 1.11. HARDLY AVOIDABLE: ENTHALPY/ENTROPY COMPENSATION; 1.12. WATER AND ITS IMPACT ON THE THERMODYNAMIC SIGNATURE.
  • Front Cover; Multi-Scale Approaches in Drug Discovery; Multi-Scale Approaches in Drug Discovery: From Synthetic Methodologies and Biological; Copyright; Contents; Contributors; 1
  • Profiling Drug Binding by Thermodynamics: Key to Understanding; 1.1. THERMODYNAMICS: A CRITERION TO PROFILE PROTEIN-LIGAND BINDING; 1.2. QUANTIFYING BINDING AFFINITY IN PROTEIN-LIGAND COMPLEX FORMATION; 1.3. METHOD OF CHOICE TO ACCESS THERMODYNAMIC DATA: ISOTHERMAL TITRATION CALORIMETRY; 1.4. ISOTHERMAL TITRATION CALORIMETRY VERSUS VAN'T HOFF DATA TO ACCESS THERMODYNAMIC PROPERTIES.
  • 1.13. IMPACT OF SURFACE WATER MOLECULES ON THE THERMODYNAMIC SIGNATURE OF PROTEIN-LIGAND COMPLEXES1.14. CONCLUSION; REFERENCES; 2
  • Machine Learning Approach to Predict Enzyme Subclasses; 2.1. INTRODUCTION; 2.2. MATERIAL AND METHODS; 2.2.1. Background for Enzyme Subclasses Prediction; 2.2.2. Computational Model; 2.2.2.1. Input Parameters; 2.2.2.2. Data Set; 2.2.2.3. Multitarget QSAR Statistical Method; 2.3. RESULTS; 2.4. DISCUSSION; 2.5. CONCLUSIONS; ACKNOWLEDGMENTS; REFERENCES; 3
  • Multitasking Model for Computer-Aided Design and ; 3.1. INTRODUCTION; 3.2. MATERIALS AND METHODS.

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