LEADER 01110nam 2200397 450 001 9910466849903321 005 20200122084625.0 010 $a83-65776-22-7 035 $a(CKB)4100000004823305 035 $a(MiAaPQ)EBC5407721 035 $a(Au-PeEL)EBL5407721 035 $a(CaPaEBR)ebr11569963 035 $a(OCoLC)1037272466 035 $a(EXLCZ)994100000004823305 100 $a20200122d2017 uy 0 101 0 $apol 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aJak wam sie podoba /$fWilliam Shakespeare ; tlumaczenie Leon Ulrich 210 1$aWarszawa :$cWydawnictwo Ktoczyta.pl,$d2017. 215 $a1 online resource (129 pages) 606 $aInfatuation 608 $aElectronic books. 615 0$aInfatuation. 676 $a863.64 700 $aShakespeare$b William$f1564-1616,$0132200 702 $aUlrich$b Leon 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910466849903321 996 $aJak wam sie podoba$92042504 997 $aUNINA LEADER 05680nam 2200697Ia 450 001 9911019886503321 005 20200520144314.0 010 $a9786612010354 010 $a9781282010352 010 $a1282010352 010 $a9783527613083 010 $a3527613080 010 $a9783527613090 010 $a3527613099 035 $a(CKB)1000000000552467 035 $a(EBL)481394 035 $a(SSID)ssj0000267790 035 $a(PQKBManifestationID)11239598 035 $a(PQKBTitleCode)TC0000267790 035 $a(PQKBWorkID)10211956 035 $a(PQKB)10072221 035 $a(MiAaPQ)EBC481394 035 $a(OCoLC)214282307 035 $a(Perlego)2788382 035 $a(EXLCZ)991000000000552467 100 $a20010103d2000 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aVirtual screening for bioactive molecules /$fedited by Hans-Joachim Bohm and Gisbert Schneider 210 $aWeinheim ;$aNew York $cWiley-VCH$dc2000 215 $a1 online resource (327 p.) 225 1 $aMethods and principles in medicinal chemistry ;$v10 300 $aDescription based upon print version of record. 311 08$a9783527301539 311 08$a3527301534 320 $aIncludes bibliographical references and index. 327 $aVirtual Screening for Bioactive Molecules; Preface; A Personal Foreword; Contents; List of Contributors; Prologue; 1 High-Throughput Screening and Virtual Screening: Entry Points to Drug Discovery; 1.1 Introduction; 1.2 Miniaturization and Detection Strategies; 1.2.1 Screening Plate Format and Fluidics; 1.2.2 Detection Strategies; 1.2.3 Cell-Based Reporter Gene Assays; 1.2.4 Fluorescence Correlation Spectroscopy .; 1.2.5 Microchip Fabrication; 1.2.6 Remarks and Summary; 1.3 Compound Libraries; 1.4 Multi-Dimensional Optimization: Qualifying HTS Lead Candidates; 1.5 Conclusions; References 327 $a2 Library Filtering Systems and Prediction of Drug-Like Properties2.1 Introduction; 2.2 Simple Counting Methods to Predict Drug-Likeness; 2.3 Functional Group Filters; 2.4 "Chemistry Space" Methods; 2.5 Examination of Building Blocks in Known Drugs; 2.6 Other Methods; 2.7 Conclusions and Future Directions; References; 3 Prediction of Physicochemical Properties; 3.1 Introduction; 3.2 Prediction of Lipophilicity; 3.2.1 Fragment-Based Methods; 3.2.2 Methods Based on Molecular Properties; 3.2.3 Predictive Ability of Existing Techniques; 3.2.4 Other Solvent Systems; 3.2.5 Effect of Ionization 327 $a3.3 Prediction of Solubility3.3.1 Fragmental Approaches; 3.3.2 Property-Based Methods; 3.3.3 Conclusions; 3.4 Prediction of pKa; 3.4.1 Fragment-Based Methods; 3.4.2 Methods Based on Molecular Properties; 3.4.3 Conclusions; 3.5 Prediction of Protein Binding; 3.6 Conclusions; References; 4 Descriptor-Based Similarity Measures for Screening Chemical Databases; 4.1 Introduction; 4.2 Fragment-Based Similarity Searching; 4.3 Association and Distance Coefficients for Similarity Searching; 4.4 Structural Representations for Similarity Searching; 4.4.1 Descriptor Selection; 4.4.2 Descriptor Encoding 327 $a4.5 ConclusionsReferences; 5 Modelling Structure-Activity Relationships; 5.1 Introduction; 5.2 Hansch Analysis; 5.3 3-D QSAR; 5.4 Alignment-Free 3-D Descriptors; 5.5 Topological Descriptors; 5.6 Pharmacophores and Pharmacophoric Keys; 5.7 Conclusions; 5.8 Appendix - Statistical Techniques in QSAR and Pattern Recognition; 5.8.1 Data Reduction and Display; 5.8.1.1 Principal Component Analysis; 5.8.1.2 Non-Linear Mapping; 5.8.1.3 Neural Networks; 5.8.2 Regression Techniques; 5.8.2.1 Multiple Linear Regression; 5.8.2.2 Principal Component Regression and Partial Least Squares 327 $a5.8.3 Classification Techniques5.8.3.1 Linear Discriminant Analysis; 5.8.3.2 Soft Independent Modelling of Class Analogy; 5.8.3.3 Recursive Partitioning; References; 6 Database Profiling by Neural Networks; 6.1 "Drug-Likeness": A General Compound Property?; 6.2 Methods and Programs; 6.2.1 Databases; 6.2.2 Descriptors; 6.2.3 Classification Tools; 6.2.4 Complete Algorithm; 6.3 Applications; 6.3.1 Drug-Likeness and a Recipe for a Computational Filter; 6.3.2 Crop Protection Compounds; 6.3.3 Virtual High-Throughput Screens; 6.3.4 Optimization of Combinatorial Libraries; 6.4 Conclusions; References 327 $a7 Pharmacophore Pattern Application in Virtual Screening. Library Design and QSAR 330 $aRecent progress in high-throughput screening, combinatorial chemistry and molecular biology has radically changed the approach to drug discovery in the pharmaceutical industry. New challenges in synthesis result in new analytical methods. At present, typically 100,000 to one million molecules have to be tested within a short period and, therefore, highly effective screening methods are necessary for today's researchers - preparing and characterizing one compound after another belongs to the past. 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