LEADER 00921nam0 2200301 450 001 9910356660303321 005 20210205183223.0 010 $a978-88-921-3095-1 100 $a20191219d2019----km y0itay50 ba 101 0 $aita 102 $aIT 105 $ay 001yy 200 1 $aDiritto del lavoro$fMaria Vittoria Ballestrero, Gisella De Simone$gcon la collaborazione di Marco Novella 205 $a4. ed. riveduta e aggiornata (settembre 2019) 210 $aTorino$cGiappichelli$dc 2019 215 $aXXIV, 698 p.$d24 cm 700 1$aBallestrero$bMaria Vittoria$0480579 701 1$aDe Simone,$bGisella$0147062 702 1$aNovella,$bMarco 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a9910356660303321 952 $aGRDDL110A$b2665$fDECBC 952 $aA-I-177$fDDRC 952 $aGRDDL110B$b2666$fDECBC 959 $aDECBC 996 $aDiritto del lavoro$9825983 997 $aUNINA LEADER 01354cam a2200301 i 4500 001 991001031659707536 005 20020502182643.0 008 980310s1996 it 001 0 ita 020 $a8872870895 035 $ab11453916-39ule_inst 035 $aPRUMB53780$9ExL 040 $aScuola per assistenti sociali$bita 082 0 $a364.45 245 00$aCriminologia, psichiatria forense e psicologia giudiziaria :$bscritti in memoria di Franco Ferracuti /$ca cura di Vincenzo Mastronardi ; consulente redazionale e traduzione [di] Mirella Garutti Ferracuti 260 $aRoma :$bA. Delfino medicina scienze,$c1996 300 $a529 p. ;$c24 cm 500 $aSul front.: Facoltà medica dell'Università di Roma La Sapienza 650 4$aCriminologia 700 1 $a Mastronardi, Vincenzo 700 1 $aFerracuti Garutti, Mirella 700 1 $aFerracuti, Franco 907 $a.b11453916$b02-04-14$c01-07-02 912 $a991001031659707536 945 $aLE024 DIR PEN VII 14$g1$i2024000006860$lle021$nex DUSS$o-$pE0.00$q-$rl$s- $t0$u3$v0$w3$x0$y.i11640674$z01-07-02 945 $aLE027 364.45 MAS01.01$g1$i2027000100552$lle027$og$pE15.00$q-$rl$sm $t0$u1$v0$w1$x0$y.i14122728$z07-09-05 996 $aCRIMINOLOGIA psichiatria forense e psicologia giudiziaria$9626727 997 $aUNISALENTO 998 $ale021$ale027$b01-01-98$cm$da $e-$fita$git $h0$i1 LEADER 01031nam a22002651i 4500 001 991003765669707536 005 20040607105331.0 008 040802s1987 uik|||||||||||||||||eng 020 $a0521357357 035 $ab13124924-39ule_inst 035 $aARCHE-107753$9ExL 040 $aBiblioteca Interfacoltà$bita$cA.t.i. Arché s.c.r.l. Pandora Sicilia s.r.l. 082 04$a194 245 00$aContemporary French philosophy /$cedited by A. Phillips Griffiths 260 $aCambridge :$bCambridge University Press,$cc1987 300 $aV, 232 p. ;$c24 cm 440 0$aRoyal Institute of philosophy lecture series ;$v21 650 4$aFilosofia$zFrancia$ySec.20. 700 1 $aGriffiths, Allen Phillips 907 $a.b13124924$b02-04-14$c05-08-04 912 $a991003765669707536 945 $aLE002 SP 100.I/021$g1$i2002000357731$lle002$nC. 1$o-$pE0.00$q-$rl$so $t0$u0$v0$w0$x0$y.i13760695$z05-08-04 996 $aContemporary French philosophy$9308595 997 $aUNISALENTO 998 $ale002$b05-08-04$cm$da $e-$feng$guik$h0$i1 LEADER 10813nam 2200541 450 001 9910831048503321 005 20240105184057.0 010 $a3-527-83049-9 010 $a3-527-83047-2 035 $a(CKB)28285519600041 035 $a(MiAaPQ)EBC30752950 035 $a(Au-PeEL)EBL30752950 035 $a(EXLCZ)9928285519600041 100 $a20231007d2024 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aOpen Access Databases and Datasets for Drug Discovery /$fedited by Antoine Daina, Michael Przewosny, and Vincent Zoete 205 $aFirst edition. 210 1$aWeinheim, Germany :$cWiley-VCH,$d[2024] 210 4$d©2024 215 $a1 online resource (348 pages) 225 1 $aMethods and Principles in Medicinal Chemistry Series 311 $a9783527348398 320 $aIncludes bibliographical references and index. 327 $aCover -- 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 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. 327 $aChapter 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). 327 $a5.5.3 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 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. 327 $a7.2 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. 327 $a8.3.1.2 List Analysis -- 8.3.1.3 Downloading Data -- 8.3.1.4 Variations on this Use Case -- 8.3.2 Characterizing a Novel Chemical Compound -- 8.3.2.1 Finding Predicted Targets -- 8.3.2.2 Analyzing Similar Ligands -- 8.3.2.3 Ligand Details Pages -- 8.3.2.4 Variations on this Use Case -- 8.3.3 Investigating Diseases -- 8.4 Discussion -- Funding -- References -- Part III Users' Points of View -- Chapter 9 Mining for Bioactive Molecules in Open Databases -- 9.1 Introduction -- 9.2 Main Tools for Virtual Screening -- 9.2.1 ADMET and PAINS Filtering -- 9.2.2 Protein-Ligand Docking -- 9.2.3 Pharmacophore Search -- 9.2.4 Shape/Electrostatic Similarity -- 9.2.5 Protein?Structure Databases -- 9.2.6 The Protein Data Bank -- 9.2.7 The PDB?REDO Databank -- 9.2.8 The SWISS?MODEL Repository -- 9.2.9 The AlphaFold Protein Structure Database -- 9.3 Validating Binding Site and Ligand Coordinates in Three?Dimensional Protein Complexes -- 9.4 Databases for Searching New Drugs -- 9.4.1 COCONUT -- 9.4.2 GDBs -- 9.4.3 ZINC20 -- 9.5 Databases of Bioactive Molecules -- 9.5.1 The BindingDB Database -- 9.5.2 PubChem -- 9.5.3 ChEMBL -- 9.6 Databases of Inactive/Decoy Molecules -- 9.6.1 Collecting Experimentally Inactive Compounds from PubChem -- 9.6.2 Collecting Presumed Inactive Compounds from Decoy Databases -- 9.6.3 Building Custom?Based Decoy Sets -- 9.7 Main Metrics for Evaluating the Success of a Virtual Screening -- 9.8 Concluding Remarks -- References -- Chapter 10 Open Access Databases - An Industrial View -- 10.1 Academic vs. Industrial Research -- 10.2 Scaffold?Hopping -- 10.3 Virtual?Screening -- References -- Index -- EULA. 410 0$aMethods and principles in medicinal chemistry. 606 $aDrugs$xDesign$xData processing 606 $aDrug development$xData processing 615 0$aDrugs$xDesign$xData processing. 615 0$aDrug development$xData processing. 676 $a615.19 702 $aDaina$b Antoine 702 $aPrzewosny$b Michael 702 $aZoete$b Vincent 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910831048503321 996 $aOpen Access Databases and Datasets for Drug Discovery$94121656 997 $aUNINA