{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":2,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":39,"n_cols":5,"rows_kept":39,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[2,4,2,5],[3,2,3,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[9,2,9,3],[12,2,12,3],[13,2,13,3],[15,2,15,3],[15,4,15,5],[16,2,16,3],[16,4,16,5],[17,2,17,3],[19,2,19,3],[21,2,21,3],[22,2,22,3],[23,2,23,3],[24,2,24,3],[25,2,25,3],[27,2,27,3],[28,2,28,3],[31,2,31,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910356660303321"]
[null,null,"Autore",null,"Ballestrero, Maria Vittoria"]
[null,null,"Titolo",null,"Diritto del lavoro / Maria Vittoria Ballestrero, Gisella De Simone ; con la collaborazione di Marco Novella"]
[null,null,"Pubbl/distr/stampa",null,"Torino, : Giappichelli, c 2019"]
[null,null,"ISBN",null,"978-88-921-3095-1"]
[null,null,"Edizione",null,"[4. ed. riveduta e aggiornata (settembre 2019)]"]
[null,null,"Descrizione fisica",null,"XXIV, 698 p. ; 24 cm"]
[null,null,"Locazione",null,"DECBC"]
[{"$nulls":4},"DDRC"]
[null,null,"Collocazione",null,"GRDDL110A"]
[{"$nulls":4},"A-I-177"]
[{"$nulls":4},"GRDDL110B"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNINA9910831048503321"]
[null,null,"Titolo",null,"Open Access Databases and Datasets for Drug Discovery / / edited by Antoine Daina, Michael Przewosny, and Vincent Zoete"]
[null,null,"Pubbl/distr/stampa",null,"Weinheim, Germany : , : Wiley-VCH, , [2024]"]
[{"$nulls":4},"©2024"]
[null,null,"ISBN",null,"3-527-83049-9"]
[{"$nulls":4},"3-527-83047-2"]
[null,null,"Edizione",null,"[First edition.]"]
[null,null,"Descrizione fisica",null,"1 online resource (348 pages)"]
[null,null,"Collana",null,"Methods and Principles in Medicinal Chemistry Series"]
[null,null,"Disciplina",null,"615.19"]
[null,null,"Soggetti",null,"Drugs - Design - Data processing"]
[{"$nulls":4},"Drug development - Data processing"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Cover -- Title Page -- Copyright -- Contents -- Series Editors Preface -- Raimund Mannhold - A Personal Obituary from the Series Editors -- A Personal Foreword -- Chapter 1 Open Access Databases and Datasets for Computer‐Aided Drug Design. A Short List Used in the Molecular Modelling Group of the SIB -- References -- Part I Small Molecules -- Chapter 2 PubChem: A Large‐Scale Public Chemical Database for Drug Discovery -- 2.1 Introduction -- 2.2 Data Content and Organization -- 2.3 Tools and Services -- 2.3.1 PubChem Search -- 2.3.2 Summary Pages -- 2.3.3 Literature Knowledge Panel -- 2.3.4 2D and 3D Neighbors -- 2.3.5 Classification Browser -- 2.3.6 Identifier Exchange Service -- 2.3.7 Programmatic Access -- 2.3.8 PubChem FTP Site and PubChemRDF -- 2.4 Drug‐ and Lead‐Likeness of PubChem Compounds -- 2.5 Bioactivity Data in PubChem -- 2.6 Comparison with Other Databases -- 2.7 Use of PubChem Data for Drug Discovery -- 2.8 Summary -- Acknowledgments -- References -- Chapter 3 DrugBank Online: A How‐to Guide -- 3.1 Introduction -- 3.2 DrugBank -- 3.2.1 Overview of DrugBank -- 3.2.2 DrugBank Datasets -- 3.2.2.1 Drug Cards: An Overview and Navigation Guide -- 3.2.2.2 Identification -- 3.2.2.3 Pharmacology -- 3.2.2.4 Categories -- 3.2.2.5 Properties -- 3.2.2.6 Targets, Enzymes, Carriers, and Transporters -- 3.2.2.7 References -- 3.3 Protocols -- 3.3.1 General Workflows -- 3.3.1.1 Using DrugBank Online's Search Functionality -- 3.3.1.2 Using DrugBank Online's Advanced Search Functionality -- 3.3.1.3 Browsing "]
[{"$nulls":4},"Drugs Using DrugBank Online's Drug Categories -- 3.3.2 Identifying Chemicals and Relevant Sequences -- 3.3.2.1 Searching Using Chemical Structure Search -- 3.3.2.2 Using Sequence Search to Find Similar Targets -- 3.3.3 Extracting DrugBank Datasets for ML -- 3.4 Research Using DrugBank -- 3.5 Discussion and Conclusions -- References."]
[{"$nulls":4},"Chapter 4 Bioisosteric Replacement for Drug Discovery Supported by the SwissBioisostere Database -- 4.1 Introduction -- 4.1.1 Concept of Isosterism and Bioisosterism -- 4.1.2 Classical vs. Non‐classical Bioisostere and Further Molecular Replacements -- 4.1.3 Bioisosteric Replacement in Drug Discovery -- 4.2 Construction and Dissemination of SwissBioisostere -- 4.2.1 Intention and Requirements -- 4.2.2 Bioactivity Data -- 4.2.3 Nonsupervised Matched Molecular Pair Analysis -- 4.2.4 Database -- 4.2.5 Web Interface -- 4.3 Content of SwissBioisostere -- 4.3.1 Global Content -- 4.3.2 Biological and Chemical Contexts -- 4.3.3 Fragment Shape Diversity -- 4.4 Usage of SwissBioisostere -- 4.4.1 Website Usage -- 4.4.2 Most Frequent Requests -- 4.4.3 Examples Related to Drug Discovery -- 4.4.3.1 Use Cases -- 4.4.3.2 Replacing Unwanted Chemical Groups -- 4.4.3.3 Optimization of Passive Absorption and Blood-Brain Barrier Diffusion -- 4.4.3.4 Reduction of Flexibility -- 4.4.3.5 Reduction of Aromaticity/Escape from Flatland -- 4.5 Conclusive Remarks -- Acknowledgment -- References -- Part II Macromolecular Targets and Diseases -- Chapter 5 The Protein Data Bank (PDB) and Macromolecular Structure Data Supporting Computer‐Aided Drug Design -- 5.1 Introduction -- 5.2 Small Molecule Data in Protein Data Bank (PDB) Entries -- 5.2.1 What Data are in the PDB Archive? -- 5.2.2 Definition of Small Molecules in OneDep -- 5.3 Small Molecule Dictionaries -- 5.3.1 wwPDB Chemical Component Dictionary (CCD) -- 5.3.2 The Peptide Reference Dictionary -- 5.4 Additional Ligand Annotations in the PDB Archive -- 5.4.1 Linkage Information -- 5.4.2 Carbohydrates -- 5.5 Validation of Ligands in the Worldwide Protein Data Bank (wwPDB) -- 5.5.1 Various Criteria and Software Used for Validating Ligand in Validation Reports -- 5.5.2 Identification of Ligand of Interest (LOI)."]
[{"$nulls":4},"5.5.3 Geometric and Conformational Validation -- 5.5.4 Ligand Fit to Experimental Electron Density Validation -- 5.5.5 Accessing wwPDB Validation Reports from PDBe Entry Pages -- 5.5.6 Other Planned Improvements to Enhance Ligand Validation -- 5.6 PDBe Tools for Ligand Analysis -- 5.6.1 Ligand Interactions -- 5.6.1.1 Classifying Ligand Interactions -- 5.6.1.2 Data Availability -- 5.6.2 Ligand Environment Component -- 5.6.3 Chemistry Process and FTP -- 5.6.4 PDBeChem Pages -- 5.7 Ligand‐Related Annotations in the PDBe‐KB -- 5.7.1 Introduction to PDBe‐KB -- 5.7.2 Data Access Mechanisms for Ligand‐Related Annotations -- 5.7.3 Ligand‐Related Annotations on the Aggregated Views of Proteins -- 5.8 Case Study: Using PDB Data to Support Drug Discovery -- 5.9 Conclusions and Outlook -- 5.9.1 Upcoming Features and Improvements -- References -- Chapter 6 The SWISS‐MODEL Repository of 3D Protein Structures and Models -- 6.1 Introduction -- 6.2 SMR Database Content and Model Providers -- 6.2.1 PDB -- 6.2.2 SWISS‐MODEL -- 6.2.3 AlphaFold Database -- 6.2.4 ModelArchive -- 6.3 Protein Feature Annotation and Cross‐References to Computational Resources -- 6.3.1 Structural Features, Ligands, and Oligomers -- 6.3.2 SWISS‐MODEL associated tools -- 6.3.3 Web and API Access -- 6.4 Quality Estimates and Benchmarking -- 6.5 Binding Site Conformational States -- 6.6 SMR and Computer‐Aided Structure‐based Drug Design -- 6.7 Conclusion and Outlook -- References -- Chapter 7 PDB‐REDO in Computational‐Aided Drug Design (CADD) -- 7.1 "]
[{"$nulls":4},"History and Concepts -- 7.1.1 X‐ray Structure Models -- 7.1.2 PDB‐REDO Development -- 7.1.2.1 First Uniformity -- 7.1.2.2 Automatic Rebuilding of Protein Backbone and Side Chains -- 7.1.2.3 Automated Model Completion Approaches -- 7.1.2.4 Systematic Integration of Structural Knowledge -- 7.1.2.5 Overview of PDB‐REDO Pipeline."]
[{"$nulls":4},"7.2 Structure Improvements by PDB‐REDO -- 7.2.1 Parametrization and Rebuilding Effects on Small Molecule Ligands -- 7.2.1.1 Re‐refinement Improves Ligand Conformation -- 7.2.1.2 Side Chain Rebuilding Improves Ligand Binding Sites -- 7.2.1.3 Histidine Flip and Improved Ligand Parameterization -- 7.2.2 Building of Protein Loops and Ligands into Protein Structure Models -- 7.2.2.1 Loop Building Completes a Binding Site Region -- 7.2.2.2 Loop Building Results in Improved Binding Sites -- 7.2.2.3 Building new Compounds into Density -- 7.2.3 Nucleic Acid Improvements by PDB‐REDO -- 7.2.4 Glycoprotein Structure Model Rebuilding -- 7.2.5 Metal Binding Sites -- 7.2.6 Limitations of the PDB‐REDO Databank -- 7.3 Access the PDB‐REDO Databank and Metadata -- 7.3.1 Downloading and Inspecting Individual PDB‐REDO Entries -- 7.3.2 Data Available in PDB‐REDO Entries -- 7.3.3 Usage of the Uniform and FAIR Validation Data -- 7.3.4 Creating Datasets from the PDB‐REDO Databank -- 7.3.5 Submitting Structure Models to the PDB‐REDO Pipeline -- 7.4 Conclusions -- Acknowledgments and Funding -- References -- Chapter 8 Pharos and TCRD: Informatics Tools for Illuminating Dark Targets -- 8.1 Introduction -- 8.2 Methods -- 8.2.1 Data Organization -- 8.2.1.1 Target Alignment -- 8.2.1.2 Disease Alignment -- 8.2.1.3 Ligand Alignment -- 8.2.1.4 Data and UI Updates -- 8.2.2 Programmatic Access and Data Download -- 8.2.3 UI Organization -- 8.2.3.1 List Pages -- 8.2.3.2 Details Pages -- 8.2.3.3 Search -- 8.2.3.4 Tutorials -- 8.2.4 Analysis Methods Within Pharos -- 8.2.4.1 Searching for Ligands -- 8.2.4.2 Finding Targets by Amino Acid Sequence -- 8.2.4.3 Finding Targets with Similar Annotations -- 8.2.4.4 Finding Targets with Predicted Activity -- 8.2.4.5 Enrichment Scores for Filter Values -- 8.3 Use Cases -- 8.3.1 Hypothesizing the Role of a Dark Target -- 8.3.1.1 Primary Documentation."]
[{"$nulls":4},"8.3.1.2 List Analysis -- 8.3.1.3 Downloading Data -- 8.3.1.4 Variations on this Use Case -- 8.3.2 Characterizing a Novel Chemical Compound -- 8.3.2.1 Finding Predicted Targets -- 8.3.2.2 Analyzing Similar Ligands -- 8.3.2.3 Ligand Details Pages -- 8.3.2.4 Variations on this Use Case -- 8.3.3 Investigating Diseases -- 8.4 Discussion -- Funding -- References -- Part III Users' Points of View -- Chapter 9 Mining for Bioactive Molecules in Open Databases -- 9.1 Introduction -- 9.2 Main Tools for Virtual Screening -- 9.2.1 ADMET and PAINS Filtering -- 9.2.2 Protein-Ligand Docking -- 9.2.3 Pharmacophore Search -- 9.2.4 Shape/Electrostatic Similarity -- 9.2.5 Protein‐Structure Databases -- 9.2.6 The Protein Data Bank -- 9.2.7 The PDB‐REDO Databank -- 9.2.8 The SWISS‐MODEL Repository -- 9.2.9 The AlphaFold Protein Structure Database -- 9.3 Validating Binding Site and Ligand Coordinates in Three‐Dimensional Protein Complexes -- 9.4 Databases for Searching New Drugs -- 9.4.1 COCONUT -- 9.4.2 GDBs -- 9.4.3 ZINC20 -- 9.5 Databases of Bioactive Molecules -- 9.5.1 The BindingDB Database -- 9.5.2 PubChem -- 9.5.3 ChEMBL -- 9.6 Databases of Inactive/Decoy Molecules -- 9.6.1 Collecting Experimentally Inactive Compounds from PubChem -- 9.6.2 Collecting Presumed Inactive Compounds from Decoy Databases -- 9.6.3 Building Custom‐Based Decoy Sets -- 9.7 Main Metrics for Evaluating the Success of a Virtual Screening -- 9.8 Concluding Remarks -- References -- Chapter 10 Open Access Databases - An Industrial View -- 10.1 Academic vs. Industrial Research -- 10.2 Scaffold‐Hopping -- 10.3 Virtual‐Screening -- "]
[{"$nulls":4},"References -- Index -- EULA."]