Molecular drug properties: measurement and prediction
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| Sprache: | English |
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Weinheim
WILEY-VCH
2008
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| Ausgabe: | 1. Aufl. |
| Schriftenreihe: | Methods and principles in medicinal chemistry
37 |
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| Online-Zugang: | Inhaltstext Inhaltsverzeichnis |
| Beschreibung: | XXX, 471 S. Ill., graph. Darst. 240 mm x 170 mm |
| ISBN: | 9783527317554 3527317554 |
Internformat
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| 245 | 1 | 0 | |a Molecular drug properties |b measurement and prediction |c ed. by Raimund Mannhold |
| 250 | |a 1. Aufl. | ||
| 264 | 1 | |a Weinheim |b WILEY-VCH |c 2008 | |
| 300 | |a XXX, 471 S. |b Ill., graph. Darst. |c 240 mm x 170 mm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a Methods and principles in medicinal chemistry |v 37 | |
| 650 | 4 | |a Chemistry, Pharmaceutical |x methods | |
| 650 | 4 | |a Drug development | |
| 650 | 4 | |a Drugs |x Structure-activity relationships | |
| 650 | 4 | |a Models, Molecular | |
| 650 | 4 | |a Pharmaceutical Preparations |x metabolism | |
| 650 | 4 | |a Pharmacokinetics | |
| 650 | 0 | 7 | |a Pharmakokinetik |0 (DE-588)4115557-9 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Arzneimittelentwicklung |0 (DE-588)4143176-5 |2 gnd |9 rswk-swf |
| 655 | 7 | |0 (DE-588)4143413-4 |a Aufsatzsammlung |2 gnd-content | |
| 689 | 0 | 0 | |a Arzneimittelentwicklung |0 (DE-588)4143176-5 |D s |
| 689 | 0 | 1 | |a Pharmakokinetik |0 (DE-588)4115557-9 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Mannhold, Raimund |4 edt | |
| 830 | 0 | |a Methods and principles in medicinal chemistry |v 37 |w (DE-604)BV035418617 |9 37 | |
| 856 | 4 | 2 | |q text/html |u http://deposit.dnb.de/cgi-bin/dokserv?id=2945638&prov=M&dok_var=1&dok_ext=htm |3 Inhaltstext |
| 856 | 4 | 2 | |m HBZ Datenaustausch |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015755204&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-015755204 | |
Datensatz im Suchindex
| _version_ | 1805089281469841408 |
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| adam_text |
VII
Contents
List of Contributors XIX
Preface XXIII
A Personal Foreword XXV
I Introduction
1 A Fresh Look at Molecular Structure and Properties 3
Bernard Testa, Giulio Vistoli, and Alessandro Pedretti
1.1 Introduction 3
1.2 Core Features: The Molecular "Genotype" 5
1.2.1 The Argument 5
1.2.2 Encoding the Molecular "Genotype" 6
1.3 Observable and Computable Properties: The Molecular "Phenotype" 6
1.3.1 Overview 6
1.3.2 Equilibria 8
1.3.3 Stereoelectronic Features 9
1.3.4 Recognition Forces and Molecular Interaction Fields (MIFs) 9
1.3.5 Macroscopic Properties 9
1.4 Molecular Properties and their Adaptability: The Property Space of
Molecular Entities 10
1.4.1 Overview 10
1.4.2 The Versatile Behavior of Acetylcholine 11
1.4.3 The Carnosine Carnosinase Complex 15
1.4.4 Property Space and Dynamic QSAR Analyses 19
1.5 Conclusions 21
2 Physicochemical Properties in Drug Profiling 25
Han van de Waterbeemd
2.1 Introduction 26
2.2 Physicochemical Properties and Pharmacokinetics 28
2.2.1 DMPK 28
2.2.2 lipophilicity Permeability Absorption 28
Molecular Drug Properties. Measurement and Prediction. R. Mannhold (Ed.)
Copyright © 2008 Wiley VCH Verlag GmbH Co. KGaA, Weinheim
ISBN: 978 3 527 31755 4
VIII I Contents
2.2.3 Estimation of Volume of Distribution from Physical Chemistry 30
2.2.4 PPB and Physicochemical Properties 30
2.3 Dissolution and Solubility 30
2.3.1 Calculated Solubility 32
2.4 Ionization (pKa) 32
2.4.1 Calculated pKa 33
2.5 Molecular Size and Shape 33
2.5.1 Calculated Size Descriptors 33
2.6 H bonding 34
2.6.1 Calculated H bonding descriptors 34
2.7 Lipophilicity 35
2.7.1 Calculated log P and log D 37
2.8 Permeability 37
2.8.1 Artificial Membranes and PAMPA 37
2.8.1.1 7n Silico PAMPA 39
2.8.2 IAM, Immobilized Liposome Chromatography (ILC), Micellar
Electrokinetic Chromatography (MEKC) and Biopartitioning Micellar
Chromatography (BMC) 39
2.8.3 Liposome Partitioning 39
2.8.4 Biosensors 40
2.9 Amphiphilicity 40
2.10 Drug like Properties 40
2.11 Computation versus Measurement of Physicochemical Properties 42
2.11.1 QSAR Modeling 42
2.11.2 In Combo: Using the Best of two Worlds 42
2.12 Outlook 43
II Electronic Properties and H Bonding
3 Drug Ionization and Physicochemical Profiling 55
Alex Avdeef
3.1 Introduction 55
3.1.1 Absorption, the Henderson Hasselbalch Equation and the pH partition
Hypothesis 56
3.1.2 "Shift in the pK/ 57
3.2 Accurate Determination of Ionization Constants 58
3.2.1 Definitions Activity versus Concentration Thermodynamic Scales 58
3.2.2 Potentiometric Method 60
3.2.3 pH Scales 60
3.2.4 Cosolvent Methods 60
3.2.5 Recent Improvements in the Potentiometric Method Applied to
Sparingly Soluble Drugs 61
3.2.6 Spectrophotometric Measurements 61
3.2.7 Use of Buffers in UV Spectrophotometry 62
3.2.8 pKa Prediction Methods and Software 63
Contents IX
3.2.9 Tabulations of Ionization Constants 63
3.3 "Octanol" and "Membrane" pKa in Partition Coefficients
Measurement 63
3.3.1 Definitions 64
3.3.2 Shape of the LogDoct pH Lipophilicity Profiles 65
3.3.3 The "diff3 4" Approximation in logDoct pH Profiles for Monoprotic
Molecules 66
3.3.4 Liposome Water Partitioning and the "diff\ 2" Approximation in
log DMEM pH Profiles for Monoprotic Molecules 67
3.4 "Gibbs" and Other "Apparent" pKa in Solubility Measurement 68
3.4.1 Interpretation of Measured Solubility of Ionizable Drug Like
Compounds can be Difficult 68
3.4.2 Simple Henderson Hasselbalch Equations 68
3.4.3 Gibbs' pKa and the "sdiff3 4" Approximation 69
3.4.4 Aggregation Equations and "Shift in the pKa" Analysis 72
3.5 "Flux" and other "Apparent" pfQ in Permeability
Measurement 74
3.5.1 Correcting Permeability for the ABL Effect by the pKaLUX
Method 74
3.5.2 Membrane Rate Limiting Transport (Hydrophilic Molecules) 76
3.5.3 Water Layer Rate Limiting Transport (Lipophilic Molecules) 77
3.5.4 Ionic species Transport in PAMPA 77
3.6 Conclusions 78
4 Electrotopological State Indices 85
Ovidiu Ivanciuc
4.1 Introduction 86
4.2 E state Indices 87
4.2.1 Molecular Graph Representation of Chemical Structures 87
4.2.2 The Randic Kier Hall Molecular Connectivity Indices 88
4.2.3 The E state Index 89
4.2.4 Hydrogen Intrinsic State 90
4.2.5 Bond E state Indices 90
4.2.6 E state 3D Field 91
4.2.7 Atom type E state Indices 93
4.2.8 Other E state Indices 91
4.3 Application of E State Indices in Medicinal Chemistry 92
4.3.1 Prediction of Aqueous Solubility 93
4.3.2 QSAR Models 93
4.3.3 Absorption, Distribution, Metabolism, Excretion and Toxicity
(ADMET) 96
4.3.4 Mutagenicity and Carcinogenicity 100
4.3.5 Anticancer Compounds 102
4.3.6 Virtual Screening of Chemical Libraries 103
4.4 Conclusions and Outlook 105
X Contents
5 Polar Surface Area 111
Peter Ertl
5.1 I ntroduction 111
5.2 Application of PSA for Prediction of Drug Transport
Properties 113
5.2.1 Intestinal Absorption 114
5.2.2 Blood Brain Barrier Penetration 115
5.2.3 Other Drug Characteristics 117
5.3 Application of PSA in Virtual Screening 117
5.4 Calculation of P SA 119
5.5 Correlation of PSA with other Molecular Descriptors 121
5.6 Conclusions 123
6 H bonding Parameterization in Quantitative Structure Activity
Relationships and Drug Design 127
Oleg Raevsky
6.1 Introduction 128
6.2 Two dimensional H bond Descriptors 129
6.2.1 Indirect H bond Descriptors 129
6.2.2 Indicator Variables 131
6.2.3 Two dimensional Thermodynamics Descriptors 131
6.3 Three dimensional H bond Descriptors 134
6.3.1 Surface H bond Descriptors 134
6.3.2 SYBYL H bond Parameters 136
6.3.3 Distance H bond Potentials 236
6.4 Application of H bond Descriptors in QSAR Studies and Drug
Design 142
6.4.1 Solubility and Partitioning of Chemicals in Water Solvent Gas
Systems 143
6.4.2 Permeability and Absorption in Humans 145
6.4.3 Classification of Pharmacokinetic Properties in Computer aided
Selection of Useful Compounds 147
6.4.4 Chemical Interactions with Biological Targets 148
6.4.5 Aquatic Toxicity 149
6.5 Conclusions 149
III Conformations
7 Three dimensional Structure Generation 257
Jens Sadowski
7.1 Introduction 257
7.2 Problem Description 260
7.2.1 Computational Requirements 260
7.2.2 General Problems 262
7.2.3 What 3D Structures Do You Need? 262
Contents XI
7.3 Concepts 163
7.3.1 Classification of Strategies 163
7.3.2 Standard Values 164
7.3.3 Fragments 166
7.3.4 Rules 169
7.3.5 Quality Control 173
7.3.6 Comparison of 3D Structures 174
7.4 Practical Aspects 175
7.4.1 Brief Overview and Evaluation of Available Software 175
7.4.2 Practical Recommendations 178
7.5 Conclusions 180
8 Exploiting Ligand Conformations in Drug Design 183
Jonas Bostrom and Andrew Grant
8.1 Introduction 183
8.1.1 Molecular Geometry and Energy Minimizations 184
8.1.2 Conformational Analysis Techniques 185
8.1.2.1 The Relevance of the Input Structure 186
8.1.3 Software 186
8.2 Generating Relevant Conformational Ensembles 187
8.2.1 Conformational Energy Cutoffs 187
8.2.1.1 Thermodynamics of Ligand Binding 188
8.2.1.2 Methods and Computational Procedure 188
8.2.1.3 Calculated Conformational Energy Cutoff Values 190
8.2.1.4 Importance of Using Solvation Models 190
8.2.2 Diverse or Low Energy Conformational Ensembles? 192
8.2.2.1 Methods and Computational Procedure 193
8.2.2.2 Reproducing Bioactive Conformations Using Different Duplicate
Removal Values 194
8.2.3 Combinatorial Explosion in Conformational Analysis 195
8.2.3.1 Representing a Conformational Ensemble by a Single
Conformation 196
8.3 Using Conformational Effects in Drug Design 198
8.3.1 Conformational Restriction 198
8.3.2 Shape Based Scaffold Hopping 200
8.4 Conclusions 202
9 Conformational Analysis of Drugs by Nuclear Magnetic Resonance
Spectroscopy 207
Burkhard Luy, Andreas Frank, and Horst Kessler
9.1 Introduction 208
9.2 NMR Parameters for Conformational Analysis 211
9.2.1 NOE/ROE 211
9.2.2 Residual Dipolar Couplings (RDCs) 217
9.2.2.1 Dipolar Interaction 218
XII I Contents
9.2.2.2 Alignment Media 219
9.2.2.3 Measurement of RDCs 221
9.2.2.4 Structural Interpretation of RDCs 222
9.2.3 Other Anisotropic NMR Parameters 225
9.2.3.1 Residual Quadrupolar Coupling (RQCs) 225
9.2.3.2 Residual Chemical Shift Anisotropy (RCSA) 225
9.2.3.3 Pseudo Contact Shift (PCS) 226
9.2.4 Scalar Coupling Constants (J couplings) 226
9.2.5 Cross Correlated Relaxation (CCR) 229
9.3 Conformation Bound to the Receptor 230
9.3.1 Ligand Conformation 232
9.3.1.1 Exchange transferred NOE (etNOE) 232
9.3.1.2 Exchange transferred RDCs (etRDCs) 233
9.3.1.3 Exchange transferred PCS (etPCS) 234
9.3.1.4 Exchange transferred CCR (etCCR) 234
9.3.2 Ligand receptor Binding Surface 235
9.3.2.1 STD Spectroscopy 235
9.3.2.2 Paramagnetic Relaxation Enhancement (PRE) 235
9.4 Refinement of Conformations by Computational Methods 236
9.4.1 Distance Geometry (DG) 237
9.4.1.1 Distance Matrices 238
9.4.1.2 Metrization 238
9.4.1.3 Embedding 238
9.4.2 Molecular Dynamics (MD) 239
9.4.2.1 Preparation of an MD Simulation 239
9.4.2.2 MD Simulations in vacuo 240
9.4.2.3 Ensemble and Time averaged Distance Restraints 241
9.4.2.4 Restrained MD (rMD) 241
9.4.2.5 Free MD (fMD) 242
9.4.2.6 Simulated Annealing (SA) 243
9.4.3 Conclusions 243
IV Solubility
10 Drug Solubility in Water and Dimethylsulfoxide 257
Christopher Lipinski
10.1 Introduction 257
10.2 Water Solubility 258
10.2.1 Where does Drug Poor Water Solubility Come From? 258
10.2.2 Water Solubility is Multifactorial 259
10.2.3 Water Solubility and Oral Absorption 259
10.2.4 Importance and Guidelines 260
10.2.5 Intestinal Fluid Solubility 261
10.3 Early Discovery Water Solubility and Biological Testing 261
10.3.1 HTS Application 261
Contents I XIII
10.3.2 Improving HTS Assay Quality 262
10.4 Water Solubility Measurement Technology 263
10.4.1 Discovery stage Water Solubility Advantages 263
10.4.2 Discovery stage Water Solubility Limitations 264
10.4.3 In Vivo Dosing Application 264
10.4.4 In Vivo SAR to Guide Chemistry 264
10.4.5 Discovery Solubility Assay Endpoint Detection 265
10.4.6 Advantages of Out of solution Detection 265
10.4.7 Limitations of Out of solution Detection 265
10.5 Compound Ionization Properties 266
10.5.1 Acids 267
10.5.2 Importance and Measurement 267
10.5.3 Bases 268
10.5.4 Importance and Measurement 268
10.5.5 Neutral Compounds 269
10.5.6 Importance and Measurement 269
10.5.7 Zwitterions 270
10.5.8 Importance and Measurement 270
10.6 Compound Solid state Properties 270
10.6.1 Solid state Properties and Water Solubility 270
10.6.2 Amorphous 271
10.6.3 Crystalline 272
10.6.4 Salt Forms 272
10.6.5 Ostwald's Rules 272
10.6.6 Isolation Procedure Changes 273
10.6.7 Greaseballs 273
10.6.8 Properties 273
10.6.9 Measuring and Fixing Solubility 273
10.6.10 Brickdust 274
10.6.11 Properties 274
10.6.12 Measuring and Fixing Solubility 274
10.6.13 Preformulation Technology in Early Discovery 275
10.6.14 Discovery Development Interface Water Solubility 275
10.6.15 Thermodynamic Equilibrium Measurements 275
10.7 DMSO Solubility 276
10.7.1 Where Does Poor DMSO Solubility Come From? 277
10.7.2 DMSO Solubility is Multifactorial 277
10.7.3 DMSO Compared to Water Solubility 278
10.7.4 DMSO Compound Storage Stocks and Compound Integrity 278
10.7.5 DMSO Solubility and Precipitation 279
10.7.6 DMSO Water Content 279
10.7.7 Freeze Thaw Cycles 280
10.7.8 Fixing Precipitation 280
10.7.9 Short term End user Storage of DMSO Stocks 281
10.8 Conclusions 281
XIV Contents
11 Challenge of Drug Solubility Prediction 283
Andreas Klamt and Brian J Smith
11.1 Importance of Aqueous Drug Solubility 283
11.2 Thermodynamic States Relevant for Drug Solubility 285
11.3 Prediction of AGfus 290
11.4 Prediction of Liquid Solubility with COSMO RS 292
11.5 Prediction of Liquid Solubility with Molecular Dynamics (MD) and
Monte Carlo (MC) Methods 296
11.6 Group Group Interaction Methods 298
11.7 Nonlinear Character of Log Sw 298
11.8 QSPRs 301
11.9 Experimental Solubility Datasets 302
11.10 Atom Contribution Methods, Electrotopological State (E state) Indices
and GCMs 304
11.11 Three dimensional Geometry based Models 305
11.12 Conclusions and Outlook 306
V Lipophilicity
12 Lipophilicity: Chemical Nature and Biological Relevance 315
Giulia Caron and Giuseppe Ermondi
12.1 Chemical Nature of Lipophilicity 315
12.1.1 Chemical Concepts Required to Understand the Significance of
Lipophilicity 315
12.1.1.1 Molecular Charges and Dipoles 315
12.1.1.2 Intermolecular Forces 318
12.1.1.3 Solvation and Hydrophobic Effect 318
12.1.2 Lipophilicity Systems 320
12.1.3 Determination of Log P and Log D 322
12.1.4 Traditional Factorization of Lipophilicity (Only Valid for Neutral
Species) 322
12.1.5 General Factorization of Lipophilicity (Valid For
All Species) 324
12.2 Biological Relevance of Lipophilicity 325
12.2.1 Lipophilicity and Membrane Permeation 325
12.2.2 Lipophilicity and Receptor Affinity 326
12.2.3 Lipophilicity and the Control of Undesired Human Ether a go go
related Gene (hERG) Activity 327
12.3 Conclusions 328
13 Chromatographic Approaches for Measuring LogP 331
Sophie Mattel, Davy Guillarme, Yveline Henchoz, Alexandra Galland,
Jean Luc Veuthey, Serge Rudaz, and Pierre Alain Corrupt
13.1 Introduction 332
13.2 Lipophilicity Measurements by RPLC: Isocratic Conditions 332
13.2.1 Main Features of RPLC Approaches 333
Contents I XV
13.2.1.1 Principles of Lipophilicity Determination 333
13.2.1.2 Retention Factors Used as RPLC Lipophilicity Indices 333
13.2.2 Relation Between Logfcw and LogPoct Using Different Conventional
Stationary Phases 334
13.2.2.1 Conventional Apolar Stationary Phases 334
13.2.2.2 IAMs 336
13.2.3 Some Guidelines for the Selection of Adequate Experimental
Conditions 337
13.2.3.1 Organic Modifiers 337
13.2.3.2 Addition of 1 Octanol in the Mobile Phase 338
13.2.3.3 Column Length 338
13.2.4 Limitations of the Isocratic Approach for log P Estimation 339
13.3 Lipophilicity Measurements by RPLC: Gradient Approaches 339
13.3.1 Gradient Elution in RPLC 339
13.3.2 Significance of High performance Liquid Chromatography (HPLC)
Lipophilicity Indices 340
13.3.2.1 General Equations of Gradient Elution in HPLC 340
13.3.3 Determination of log kw from Gradient Experiments 341
13.3.3.1 From a Single Gradient Run 341
13.3.3.2 From Two Gradient Runs 341
13.3.3.3 With Optimization Software and Two Gradient Runs 342
13.3.4 Chromatographic Hydrophobicity Index (CHI) as a Measure of
Hydrophobicity 341
13.3.4.1 Experimental Determination of CHI 342
13.3.4.2 Advantages/Limitations of CHI 342
13.3.5 Experimental Conditions and Analysis of Results 343
13.3.5.1 Prediction of log P and Comparison of Lipophilicity Indices 343
13.3.6 Approaches to Improve Throughput 344
13.3.6.1 Fast Gradient Elution in RPLC 344
13.3.6.2 Use of MS Detection 345
13.3.7 Some Guidelines for a Typical Application of Gradient RPLC in
Physicochemical Profiling 346
13.3.7.1 A Careful Selection of Experimental Conditions 346
13.3.7.2 General Procedure for log fcw Determination 347
13.3.7.3 General Procedure for CHI Determination 347
13.4 Lipophilicity Measurements by Capillary Electrophoresis (CE) 347
13.4.1 MEKC 348
13.4.2 MEEKC 349
13.4.3 LEKC/VEKC 349
13.5 Supplementary Material 350
14 Prediction of LogP with Substructure based Methods 357
Raimund Mannhold and Claude Ostermann
14.1 Introduction 357
14.2 Fragmental Methods 358
XVI I Contents
14.2.1 I/System 359
14.2.2 KLOGP 361
14.2.3 KOWWIN 363
14.2.4 CLOGP 364
14.2.4.1 Fragmentation Rules 365
14.2.4.2 Structural Factors 365
14.2.4.3 Interaction Factors: Aliphatic Proximity 365
14.2.4.4 Interaction Factors: Electronic Effects through 7t Bonds 366
14.2.4.5 Interaction Factors: Special Ortho Effects 366
14.2.5 ACD/LogP 367
14.2.6 AB/LogP 368
14.3 Atom based Methods 371
14.3.1 Ghose Crippen Approach 371
14.3.2 XLOGP 373
14.4 Predictive Power of Substructure based Approaches 374
15 Prediction of Log P with Property based Methods 381
Igor V. Tetko and Gennadiy I. Poda
15.1 Introduction 381
15.2 Methods Based on 3D Structure Representation 382
15.2.1 Empirical Approaches 382
15.2.1.1 LSER 382
15.2.1.2 SLIPPER 383
15.2.1.3 SPARC 384
15.2.2 Methods Based on Quantum Chemical Semiempirical
Calculations 385
15.2.2.1 Correlation of Log Pwith Calculated Quantum Chemical
Parameters 385
15.2.2.2 QLOGP: Importance of Molecular Size 385
15.2.3 Approaches Based on Continuum Solvation Models 386
15.2.3.1 GBLOGP 386
15.2.3.2 COSMO RS (Full) Approach 387
15.2.3.3 COSMOfrag (Fragment based) Approach 388
15.2.3.4 Ab Initio Methods 388
15.2.3.5 QuantlogP 389
15.2.4 Models Based on MD Calculations 389
15.2.5 MLP Methods 390
15.2.5.1 Early Methods of MLP Calculations 390
15.2.5.2 Hydrophobic Interactions (HINT) 391
15.2.5.3 Calculated Lipophilicity Potential (CLIP) 391
15.2.6 Log P Prediction Using Lattice Energies 392
15.3 Methods Based on Topological Descriptors 392
15.3.1 MLOGP 392
15.3.2 Graph Molecular Connectivity 392
15.3.2.1 TLOGP 393
Contents I XVII
15.3.3 Methods Based on Electrotopological State (E state)
Descriptors 393
15.3.3.1 VLOGP 393
15.3.3.2 ALOGPS 394
15.3.3.3 CSlogP 394
15.3.3.4 A_S+logP 394
15.4 Prediction Power of Property based Approaches 394
15.4.1 Datasets Quality and Consistence 395
15.4.2 Background Models 395
15.4.3 Benchmarking Results 397
15.4.4 Pitfalls of the Benchmarking 397
15.4.4.1 Do We Compare Methods or Their Implementations? 397
15.4.4.2 Overlap in the Training and Benchmarking Sets 399
15.4.4.3 Zwitterions 399
15.4.4.4 Tautomers and Aromaticity 400
15.5 Conclusions 401
16 The Good, the Bad and the Ugly of Distribution Coefficients: Current
Status, Views and Outlook 407
Franco Lombardo, Bernard Falter, Marina Shalaeva, Igor Tetko, and
Suzanne Tilton
16.1 Log D and Log P 408
16.1.1 Definitions and Equations 408
16.1.2 Is There Life After Octanol? 410
16.1.3 Log P or Log D? 412
16.1.4 ADME Applications 413
16.2 Issues and Automation in the Determination of Log D 414
16.2.1 Shake Flask Method 414
16.2.2 Potentiometric Method 415
16.2.3 Chromatographic Methods 416
16.2.4 Electrophoretic Methods 418
16.2.5 IAMs 419
16.2.6 Applications Perspective 419
16.3 pH partition Theory and Ion pairing 421
16.3.1 General Aspects and Foundation of the pH partition Theory 421
16.3.2 Ion pairing: In Vitro and In Vivo Implications 421
16.3.2.1 Ion pairing In Vitro 421
16.3.2.2 Ion pairing In Vivo 424
16.4 Computational Approaches 425
16.4.1 Methods to Predict Log D at Arbitrary pH 425
16.4.2 Methods to Predict Log D at Fixed pH 427
16.4.3 Issues and Needs 428
16.4.3.1 LogD Models in ADMET Prediction 428
16.4.3.2 Applicability Domain of Models 429
16.5 Some Concluding Remarks: The Good, the Bad and the Ugly 430
XVIII I Contents
VI Drug and Lead likeness
17 Properties Guiding Drug and Lead likeness 441
Sorel Muresan and Jens Sadowski
17.1 Introduction 441
17.2 Properties of Leads and Drugs 442
17.2.1 Simple Molecular Properties 442
17.2.2 Chemical Filters 445
17.2.3 Correlated Properties 446
17.2.4 Property Trends and Property Ranges 448
17.2.5 Ligand Efficiency 450
17.3 Drug likeness as a Classification Problem 453
Y7A Application Example: Compound Acquisition 455
17.5 Conclusions 457
Index 463 |
| adam_txt |
VII
Contents
List of Contributors XIX
Preface XXIII
A Personal Foreword XXV
I Introduction
1 A Fresh Look at Molecular Structure and Properties 3
Bernard Testa, Giulio Vistoli, and Alessandro Pedretti
1.1 Introduction 3
1.2 Core Features: The Molecular "Genotype" 5
1.2.1 The Argument 5
1.2.2 Encoding the Molecular "Genotype" 6
1.3 Observable and Computable Properties: The Molecular "Phenotype" 6
1.3.1 Overview 6
1.3.2 Equilibria 8
1.3.3 Stereoelectronic Features 9
1.3.4 Recognition Forces and Molecular Interaction Fields (MIFs) 9
1.3.5 Macroscopic Properties 9
1.4 Molecular Properties and their Adaptability: The Property Space of
Molecular Entities 10
1.4.1 Overview 10
1.4.2 The Versatile Behavior of Acetylcholine 11
1.4.3 The Carnosine Carnosinase Complex 15
1.4.4 Property Space and Dynamic QSAR Analyses 19
1.5 Conclusions 21
2 Physicochemical Properties in Drug Profiling 25
Han van de Waterbeemd
2.1 Introduction 26
2.2 Physicochemical Properties and Pharmacokinetics 28
2.2.1 DMPK 28
2.2.2 lipophilicity Permeability Absorption 28
Molecular Drug Properties. Measurement and Prediction. R. Mannhold (Ed.)
Copyright © 2008 Wiley VCH Verlag GmbH Co. KGaA, Weinheim
ISBN: 978 3 527 31755 4
VIII I Contents
2.2.3 Estimation of Volume of Distribution from Physical Chemistry 30
2.2.4 PPB and Physicochemical Properties 30
2.3 Dissolution and Solubility 30
2.3.1 Calculated Solubility 32
2.4 Ionization (pKa) 32
2.4.1 Calculated pKa 33
2.5 Molecular Size and Shape 33
2.5.1 Calculated Size Descriptors 33
2.6 H bonding 34
2.6.1 Calculated H bonding descriptors 34
2.7 Lipophilicity 35
2.7.1 Calculated log P and log D 37
2.8 Permeability 37
2.8.1 Artificial Membranes and PAMPA 37
2.8.1.1 7n Silico PAMPA 39
2.8.2 IAM, Immobilized Liposome Chromatography (ILC), Micellar
Electrokinetic Chromatography (MEKC) and Biopartitioning Micellar
Chromatography (BMC) 39
2.8.3 Liposome Partitioning 39
2.8.4 Biosensors 40
2.9 Amphiphilicity 40
2.10 Drug like Properties 40
2.11 Computation versus Measurement of Physicochemical Properties 42
2.11.1 QSAR Modeling 42
2.11.2 In Combo: Using the Best of two Worlds 42
2.12 Outlook 43
II Electronic Properties and H Bonding
3 Drug Ionization and Physicochemical Profiling 55
Alex Avdeef
3.1 Introduction 55
3.1.1 Absorption, the Henderson Hasselbalch Equation and the pH partition
Hypothesis 56
3.1.2 "Shift in the pK/ 57
3.2 Accurate Determination of Ionization Constants 58
3.2.1 Definitions Activity versus Concentration Thermodynamic Scales 58
3.2.2 Potentiometric Method 60
3.2.3 pH Scales 60
3.2.4 Cosolvent Methods 60
3.2.5 Recent Improvements in the Potentiometric Method Applied to
Sparingly Soluble Drugs 61
3.2.6 Spectrophotometric Measurements 61
3.2.7 Use of Buffers in UV Spectrophotometry 62
3.2.8 pKa Prediction Methods and Software 63
Contents IX
3.2.9 Tabulations of Ionization Constants 63
3.3 "Octanol" and "Membrane" pKa in Partition Coefficients
Measurement 63
3.3.1 Definitions 64
3.3.2 Shape of the LogDoct pH Lipophilicity Profiles 65
3.3.3 The "diff3 4" Approximation in logDoct pH Profiles for Monoprotic
Molecules 66
3.3.4 Liposome Water Partitioning and the "diff\ 2" Approximation in
log DMEM pH Profiles for Monoprotic Molecules 67
3.4 "Gibbs" and Other "Apparent" pKa in Solubility Measurement 68
3.4.1 Interpretation of Measured Solubility of Ionizable Drug Like
Compounds can be Difficult 68
3.4.2 Simple Henderson Hasselbalch Equations 68
3.4.3 Gibbs' pKa and the "sdiff3 4" Approximation 69
3.4.4 Aggregation Equations and "Shift in the pKa" Analysis 72
3.5 "Flux" and other "Apparent" pfQ in Permeability
Measurement 74
3.5.1 Correcting Permeability for the ABL Effect by the pKaLUX
Method 74
3.5.2 Membrane Rate Limiting Transport (Hydrophilic Molecules) 76
3.5.3 Water Layer Rate Limiting Transport (Lipophilic Molecules) 77
3.5.4 Ionic species Transport in PAMPA 77
3.6 Conclusions 78
4 Electrotopological State Indices 85
Ovidiu Ivanciuc
4.1 Introduction 86
4.2 E state Indices 87
4.2.1 Molecular Graph Representation of Chemical Structures 87
4.2.2 The Randic Kier Hall Molecular Connectivity Indices 88
4.2.3 The E state Index 89
4.2.4 Hydrogen Intrinsic State 90
4.2.5 Bond E state Indices 90
4.2.6 E state 3D Field 91
4.2.7 Atom type E state Indices 93
4.2.8 Other E state Indices 91
4.3 Application of E State Indices in Medicinal Chemistry 92
4.3.1 Prediction of Aqueous Solubility 93
4.3.2 QSAR Models 93
4.3.3 Absorption, Distribution, Metabolism, Excretion and Toxicity
(ADMET) 96
4.3.4 Mutagenicity and Carcinogenicity 100
4.3.5 Anticancer Compounds 102
4.3.6 Virtual Screening of Chemical Libraries 103
4.4 Conclusions and Outlook 105
X Contents
5 Polar Surface Area 111
Peter Ertl
5.1 I ntroduction 111
5.2 Application of PSA for Prediction of Drug Transport
Properties 113
5.2.1 Intestinal Absorption 114
5.2.2 Blood Brain Barrier Penetration 115
5.2.3 Other Drug Characteristics 117
5.3 Application of PSA in Virtual Screening 117
5.4 Calculation of P SA 119
5.5 Correlation of PSA with other Molecular Descriptors 121
5.6 Conclusions 123
6 H bonding Parameterization in Quantitative Structure Activity
Relationships and Drug Design 127
Oleg Raevsky
6.1 Introduction 128
6.2 Two dimensional H bond Descriptors 129
6.2.1 Indirect H bond Descriptors 129
6.2.2 Indicator Variables 131
6.2.3 Two dimensional Thermodynamics Descriptors 131
6.3 Three dimensional H bond Descriptors 134
6.3.1 Surface H bond Descriptors 134
6.3.2 SYBYL H bond Parameters 136
6.3.3 Distance H bond Potentials 236
6.4 Application of H bond Descriptors in QSAR Studies and Drug
Design 142
6.4.1 Solubility and Partitioning of Chemicals in Water Solvent Gas
Systems 143
6.4.2 Permeability and Absorption in Humans 145
6.4.3 Classification of Pharmacokinetic Properties in Computer aided
Selection of Useful Compounds 147
6.4.4 Chemical Interactions with Biological Targets 148
6.4.5 Aquatic Toxicity 149
6.5 Conclusions 149
III Conformations
7 Three dimensional Structure Generation 257
Jens Sadowski
7.1 Introduction 257
7.2 Problem Description 260
7.2.1 Computational Requirements 260
7.2.2 General Problems 262
7.2.3 What 3D Structures Do You Need? 262
Contents XI
7.3 Concepts 163
7.3.1 Classification of Strategies 163
7.3.2 Standard Values 164
7.3.3 Fragments 166
7.3.4 Rules 169
7.3.5 Quality Control 173
7.3.6 Comparison of 3D Structures 174
7.4 Practical Aspects 175
7.4.1 Brief Overview and Evaluation of Available Software 175
7.4.2 Practical Recommendations 178
7.5 Conclusions 180
8 Exploiting Ligand Conformations in Drug Design 183
Jonas Bostrom and Andrew Grant
8.1 Introduction 183
8.1.1 Molecular Geometry and Energy Minimizations 184
8.1.2 Conformational Analysis Techniques 185
8.1.2.1 The Relevance of the Input Structure 186
8.1.3 Software 186
8.2 Generating Relevant Conformational Ensembles 187
8.2.1 Conformational Energy Cutoffs 187
8.2.1.1 Thermodynamics of Ligand Binding 188
8.2.1.2 Methods and Computational Procedure 188
8.2.1.3 Calculated Conformational Energy Cutoff Values 190
8.2.1.4 Importance of Using Solvation Models 190
8.2.2 Diverse or Low Energy Conformational Ensembles? 192
8.2.2.1 Methods and Computational Procedure 193
8.2.2.2 Reproducing Bioactive Conformations Using Different Duplicate
Removal Values 194
8.2.3 Combinatorial Explosion in Conformational Analysis 195
8.2.3.1 Representing a Conformational Ensemble by a Single
Conformation 196
8.3 Using Conformational Effects in Drug Design 198
8.3.1 Conformational Restriction 198
8.3.2 Shape Based Scaffold Hopping 200
8.4 Conclusions 202
9 Conformational Analysis of Drugs by Nuclear Magnetic Resonance
Spectroscopy 207
Burkhard Luy, Andreas Frank, and Horst Kessler
9.1 Introduction 208
9.2 NMR Parameters for Conformational Analysis 211
9.2.1 NOE/ROE 211
9.2.2 Residual Dipolar Couplings (RDCs) 217
9.2.2.1 Dipolar Interaction 218
XII I Contents
9.2.2.2 Alignment Media 219
9.2.2.3 Measurement of RDCs 221
9.2.2.4 Structural Interpretation of RDCs 222
9.2.3 Other Anisotropic NMR Parameters 225
9.2.3.1 Residual Quadrupolar Coupling (RQCs) 225
9.2.3.2 Residual Chemical Shift Anisotropy (RCSA) 225
9.2.3.3 Pseudo Contact Shift (PCS) 226
9.2.4 Scalar Coupling Constants (J couplings) 226
9.2.5 Cross Correlated Relaxation (CCR) 229
9.3 Conformation Bound to the Receptor 230
9.3.1 Ligand Conformation 232
9.3.1.1 Exchange transferred NOE (etNOE) 232
9.3.1.2 Exchange transferred RDCs (etRDCs) 233
9.3.1.3 Exchange transferred PCS (etPCS) 234
9.3.1.4 Exchange transferred CCR (etCCR) 234
9.3.2 Ligand receptor Binding Surface 235
9.3.2.1 STD Spectroscopy 235
9.3.2.2 Paramagnetic Relaxation Enhancement (PRE) 235
9.4 Refinement of Conformations by Computational Methods 236
9.4.1 Distance Geometry (DG) 237
9.4.1.1 Distance Matrices 238
9.4.1.2 Metrization 238
9.4.1.3 Embedding 238
9.4.2 Molecular Dynamics (MD) 239
9.4.2.1 Preparation of an MD Simulation 239
9.4.2.2 MD Simulations in vacuo 240
9.4.2.3 Ensemble and Time averaged Distance Restraints 241
9.4.2.4 Restrained MD (rMD) 241
9.4.2.5 Free MD (fMD) 242
9.4.2.6 Simulated Annealing (SA) 243
9.4.3 Conclusions 243
IV Solubility
10 Drug Solubility in Water and Dimethylsulfoxide 257
Christopher Lipinski
10.1 Introduction 257
10.2 Water Solubility 258
10.2.1 Where does Drug Poor Water Solubility Come From? 258
10.2.2 Water Solubility is Multifactorial 259
10.2.3 Water Solubility and Oral Absorption 259
10.2.4 Importance and Guidelines 260
10.2.5 Intestinal Fluid Solubility 261
10.3 Early Discovery Water Solubility and Biological Testing 261
10.3.1 HTS Application 261
Contents I XIII
10.3.2 Improving HTS Assay Quality 262
10.4 Water Solubility Measurement Technology 263
10.4.1 Discovery stage Water Solubility Advantages 263
10.4.2 Discovery stage Water Solubility Limitations 264
10.4.3 In Vivo Dosing Application 264
10.4.4 In Vivo SAR to Guide Chemistry 264
10.4.5 Discovery Solubility Assay Endpoint Detection 265
10.4.6 Advantages of Out of solution Detection 265
10.4.7 Limitations of Out of solution Detection 265
10.5 Compound Ionization Properties 266
10.5.1 Acids 267
10.5.2 Importance and Measurement 267
10.5.3 Bases 268
10.5.4 Importance and Measurement 268
10.5.5 Neutral Compounds 269
10.5.6 Importance and Measurement 269
10.5.7 Zwitterions 270
10.5.8 Importance and Measurement 270
10.6 Compound Solid state Properties 270
10.6.1 Solid state Properties and Water Solubility 270
10.6.2 Amorphous 271
10.6.3 Crystalline 272
10.6.4 Salt Forms 272
10.6.5 Ostwald's Rules 272
10.6.6 Isolation Procedure Changes 273
10.6.7 Greaseballs 273
10.6.8 Properties 273
10.6.9 Measuring and Fixing Solubility 273
10.6.10 Brickdust 274
10.6.11 Properties 274
10.6.12 Measuring and Fixing Solubility 274
10.6.13 Preformulation Technology in Early Discovery 275
10.6.14 Discovery Development Interface Water Solubility 275
10.6.15 Thermodynamic Equilibrium Measurements 275
10.7 DMSO Solubility 276
10.7.1 Where Does Poor DMSO Solubility Come From? 277
10.7.2 DMSO Solubility is Multifactorial 277
10.7.3 DMSO Compared to Water Solubility 278
10.7.4 DMSO Compound Storage Stocks and Compound Integrity 278
10.7.5 DMSO Solubility and Precipitation 279
10.7.6 DMSO Water Content 279
10.7.7 Freeze Thaw Cycles 280
10.7.8 Fixing Precipitation 280
10.7.9 Short term End user Storage of DMSO Stocks 281
10.8 Conclusions 281
XIV Contents
11 Challenge of Drug Solubility Prediction 283
Andreas Klamt and Brian J Smith
11.1 Importance of Aqueous Drug Solubility 283
11.2 Thermodynamic States Relevant for Drug Solubility 285
11.3 Prediction of AGfus 290
11.4 Prediction of Liquid Solubility with COSMO RS 292
11.5 Prediction of Liquid Solubility with Molecular Dynamics (MD) and
Monte Carlo (MC) Methods 296
11.6 Group Group Interaction Methods 298
11.7 Nonlinear Character of Log Sw 298
11.8 QSPRs 301
11.9 Experimental Solubility Datasets 302
11.10 Atom Contribution Methods, Electrotopological State (E state) Indices
and GCMs 304
11.11 Three dimensional Geometry based Models 305
11.12 Conclusions and Outlook 306
V Lipophilicity
12 Lipophilicity: Chemical Nature and Biological Relevance 315
Giulia Caron and Giuseppe Ermondi
12.1 Chemical Nature of Lipophilicity 315
12.1.1 Chemical Concepts Required to Understand the Significance of
Lipophilicity 315
12.1.1.1 Molecular Charges and Dipoles 315
12.1.1.2 Intermolecular Forces 318
12.1.1.3 Solvation and Hydrophobic Effect 318
12.1.2 Lipophilicity Systems 320
12.1.3 Determination of Log P and Log D 322
12.1.4 Traditional Factorization of Lipophilicity (Only Valid for Neutral
Species) 322
12.1.5 General Factorization of Lipophilicity (Valid For
All Species) 324
12.2 Biological Relevance of Lipophilicity 325
12.2.1 Lipophilicity and Membrane Permeation 325
12.2.2 Lipophilicity and Receptor Affinity 326
12.2.3 Lipophilicity and the Control of Undesired Human Ether a go go
related Gene (hERG) Activity 327
12.3 Conclusions 328
13 Chromatographic Approaches for Measuring LogP 331
Sophie Mattel, Davy Guillarme, Yveline Henchoz, Alexandra Galland,
Jean Luc Veuthey, Serge Rudaz, and Pierre Alain Corrupt
13.1 Introduction 332
13.2 Lipophilicity Measurements by RPLC: Isocratic Conditions 332
13.2.1 Main Features of RPLC Approaches 333
Contents I XV
13.2.1.1 Principles of Lipophilicity Determination 333
13.2.1.2 Retention Factors Used as RPLC Lipophilicity Indices 333
13.2.2 Relation Between Logfcw and LogPoct Using Different Conventional
Stationary Phases 334
13.2.2.1 Conventional Apolar Stationary Phases 334
13.2.2.2 IAMs 336
13.2.3 Some Guidelines for the Selection of Adequate Experimental
Conditions 337
13.2.3.1 Organic Modifiers 337
13.2.3.2 Addition of 1 Octanol in the Mobile Phase 338
13.2.3.3 Column Length 338
13.2.4 Limitations of the Isocratic Approach for log P Estimation 339
13.3 Lipophilicity Measurements by RPLC: Gradient Approaches 339
13.3.1 Gradient Elution in RPLC 339
13.3.2 Significance of High performance Liquid Chromatography (HPLC)
Lipophilicity Indices 340
13.3.2.1 General Equations of Gradient Elution in HPLC 340
13.3.3 Determination of log kw from Gradient Experiments 341
13.3.3.1 From a Single Gradient Run 341
13.3.3.2 From Two Gradient Runs 341
13.3.3.3 With Optimization Software and Two Gradient Runs 342
13.3.4 Chromatographic Hydrophobicity Index (CHI) as a Measure of
Hydrophobicity 341
13.3.4.1 Experimental Determination of CHI 342
13.3.4.2 Advantages/Limitations of CHI 342
13.3.5 Experimental Conditions and Analysis of Results 343
13.3.5.1 Prediction of log P and Comparison of Lipophilicity Indices 343
13.3.6 Approaches to Improve Throughput 344
13.3.6.1 Fast Gradient Elution in RPLC 344
13.3.6.2 Use of MS Detection 345
13.3.7 Some Guidelines for a Typical Application of Gradient RPLC in
Physicochemical Profiling 346
13.3.7.1 A Careful Selection of Experimental Conditions 346
13.3.7.2 General Procedure for log fcw Determination 347
13.3.7.3 General Procedure for CHI Determination 347
13.4 Lipophilicity Measurements by Capillary Electrophoresis (CE) 347
13.4.1 MEKC 348
13.4.2 MEEKC 349
13.4.3 LEKC/VEKC 349
13.5 Supplementary Material 350
14 Prediction of LogP with Substructure based Methods 357
Raimund Mannhold and Claude Ostermann
14.1 Introduction 357
14.2 Fragmental Methods 358
XVI I Contents
14.2.1 I/System 359
14.2.2 KLOGP 361
14.2.3 KOWWIN 363
14.2.4 CLOGP 364
14.2.4.1 Fragmentation Rules 365
14.2.4.2 Structural Factors 365
14.2.4.3 Interaction Factors: Aliphatic Proximity 365
14.2.4.4 Interaction Factors: Electronic Effects through 7t Bonds 366
14.2.4.5 Interaction Factors: Special Ortho Effects 366
14.2.5 ACD/LogP 367
14.2.6 AB/LogP 368
14.3 Atom based Methods 371
14.3.1 Ghose Crippen Approach 371
14.3.2 XLOGP 373
14.4 Predictive Power of Substructure based Approaches 374
15 Prediction of Log P with Property based Methods 381
Igor V. Tetko and Gennadiy I. Poda
15.1 Introduction 381
15.2 Methods Based on 3D Structure Representation 382
15.2.1 Empirical Approaches 382
15.2.1.1 LSER 382
15.2.1.2 SLIPPER 383
15.2.1.3 SPARC 384
15.2.2 Methods Based on Quantum Chemical Semiempirical
Calculations 385
15.2.2.1 Correlation of Log Pwith Calculated Quantum Chemical
Parameters 385
15.2.2.2 QLOGP: Importance of Molecular Size 385
15.2.3 Approaches Based on Continuum Solvation Models 386
15.2.3.1 GBLOGP 386
15.2.3.2 COSMO RS (Full) Approach 387
15.2.3.3 COSMOfrag (Fragment based) Approach 388
15.2.3.4 Ab Initio Methods 388
15.2.3.5 QuantlogP 389
15.2.4 Models Based on MD Calculations 389
15.2.5 MLP Methods 390
15.2.5.1 Early Methods of MLP Calculations 390
15.2.5.2 Hydrophobic Interactions (HINT) 391
15.2.5.3 Calculated Lipophilicity Potential (CLIP) 391
15.2.6 Log P Prediction Using Lattice Energies 392
15.3 Methods Based on Topological Descriptors 392
15.3.1 MLOGP 392
15.3.2 Graph Molecular Connectivity 392
15.3.2.1 TLOGP 393
Contents I XVII
15.3.3 Methods Based on Electrotopological State (E state)
Descriptors 393
15.3.3.1 VLOGP 393
15.3.3.2 ALOGPS 394
15.3.3.3 CSlogP 394
15.3.3.4 A_S+logP 394
15.4 Prediction Power of Property based Approaches 394
15.4.1 Datasets Quality and Consistence 395
15.4.2 Background Models 395
15.4.3 Benchmarking Results 397
15.4.4 Pitfalls of the Benchmarking 397
15.4.4.1 Do We Compare Methods or Their Implementations? 397
15.4.4.2 Overlap in the Training and Benchmarking Sets 399
15.4.4.3 Zwitterions 399
15.4.4.4 Tautomers and Aromaticity 400
15.5 Conclusions 401
16 The Good, the Bad and the Ugly of Distribution Coefficients: Current
Status, Views and Outlook 407
Franco Lombardo, Bernard Falter, Marina Shalaeva, Igor Tetko, and
Suzanne Tilton
16.1 Log D and Log P 408
16.1.1 Definitions and Equations 408
16.1.2 Is There Life After Octanol? 410
16.1.3 Log P or Log D? 412
16.1.4 ADME Applications 413
16.2 Issues and Automation in the Determination of Log D 414
16.2.1 Shake Flask Method 414
16.2.2 Potentiometric Method 415
16.2.3 Chromatographic Methods 416
16.2.4 Electrophoretic Methods 418
16.2.5 IAMs 419
16.2.6 Applications Perspective 419
16.3 pH partition Theory and Ion pairing 421
16.3.1 General Aspects and Foundation of the pH partition Theory 421
16.3.2 Ion pairing: In Vitro and In Vivo Implications 421
16.3.2.1 Ion pairing In Vitro 421
16.3.2.2 Ion pairing In Vivo 424
16.4 Computational Approaches 425
16.4.1 Methods to Predict Log D at Arbitrary pH 425
16.4.2 Methods to Predict Log D at Fixed pH 427
16.4.3 Issues and Needs 428
16.4.3.1 LogD Models in ADMET Prediction 428
16.4.3.2 Applicability Domain of Models 429
16.5 Some Concluding Remarks: The Good, the Bad and the Ugly 430
XVIII I Contents
VI Drug and Lead likeness
17 Properties Guiding Drug and Lead likeness 441
Sorel Muresan and Jens Sadowski
17.1 Introduction 441
17.2 Properties of Leads and Drugs 442
17.2.1 Simple Molecular Properties 442
17.2.2 Chemical Filters 445
17.2.3 Correlated Properties 446
17.2.4 Property Trends and Property Ranges 448
17.2.5 Ligand Efficiency 450
17.3 Drug likeness as a Classification Problem 453
Y7A Application Example: Compound Acquisition 455
17.5 Conclusions 457
Index 463 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author2 | Mannhold, Raimund |
| author2_role | edt |
| author2_variant | r m rm |
| author_facet | Mannhold, Raimund |
| building | Verbundindex |
| bvnumber | BV022548867 |
| callnumber-first | R - Medicine |
| callnumber-label | RM301 |
| callnumber-raw | RM301.42 |
| callnumber-search | RM301.42 |
| callnumber-sort | RM 3301.42 |
| callnumber-subject | RM - Therapeutics and Pharmacology |
| classification_rvk | VX 5200 |
| ctrlnum | (OCoLC)182662675 (DE-599)DNB983932875 |
| dewey-full | 615.7 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 615 - Pharmacology and therapeutics |
| dewey-raw | 615.7 |
| dewey-search | 615.7 |
| dewey-sort | 3615.7 |
| dewey-tens | 610 - Medicine and health |
| discipline | Chemie / Pharmazie Medizin |
| discipline_str_mv | Chemie / Pharmazie Medizin |
| edition | 1. Aufl. |
| format | Book |
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| genre_facet | Aufsatzsammlung |
| id | DE-604.BV022548867 |
| illustrated | Illustrated |
| index_date | 2024-07-02T18:12:50Z |
| indexdate | 2024-07-20T09:21:26Z |
| institution | BVB |
| isbn | 9783527317554 3527317554 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015755204 |
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| physical | XXX, 471 S. Ill., graph. Darst. 240 mm x 170 mm |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | WILEY-VCH |
| record_format | marc |
| series | Methods and principles in medicinal chemistry |
| series2 | Methods and principles in medicinal chemistry |
| spelling | Molecular drug properties measurement and prediction ed. by Raimund Mannhold 1. Aufl. Weinheim WILEY-VCH 2008 XXX, 471 S. Ill., graph. Darst. 240 mm x 170 mm txt rdacontent n rdamedia nc rdacarrier Methods and principles in medicinal chemistry 37 Chemistry, Pharmaceutical methods Drug development Drugs Structure-activity relationships Models, Molecular Pharmaceutical Preparations metabolism Pharmacokinetics Pharmakokinetik (DE-588)4115557-9 gnd rswk-swf Arzneimittelentwicklung (DE-588)4143176-5 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Arzneimittelentwicklung (DE-588)4143176-5 s Pharmakokinetik (DE-588)4115557-9 s DE-604 Mannhold, Raimund edt Methods and principles in medicinal chemistry 37 (DE-604)BV035418617 37 text/html http://deposit.dnb.de/cgi-bin/dokserv?id=2945638&prov=M&dok_var=1&dok_ext=htm Inhaltstext HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015755204&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Molecular drug properties measurement and prediction Methods and principles in medicinal chemistry Chemistry, Pharmaceutical methods Drug development Drugs Structure-activity relationships Models, Molecular Pharmaceutical Preparations metabolism Pharmacokinetics Pharmakokinetik (DE-588)4115557-9 gnd Arzneimittelentwicklung (DE-588)4143176-5 gnd |
| subject_GND | (DE-588)4115557-9 (DE-588)4143176-5 (DE-588)4143413-4 |
| title | Molecular drug properties measurement and prediction |
| title_auth | Molecular drug properties measurement and prediction |
| title_exact_search | Molecular drug properties measurement and prediction |
| title_exact_search_txtP | Molecular drug properties measurement and prediction |
| title_full | Molecular drug properties measurement and prediction ed. by Raimund Mannhold |
| title_fullStr | Molecular drug properties measurement and prediction ed. by Raimund Mannhold |
| title_full_unstemmed | Molecular drug properties measurement and prediction ed. by Raimund Mannhold |
| title_short | Molecular drug properties |
| title_sort | molecular drug properties measurement and prediction |
| title_sub | measurement and prediction |
| topic | Chemistry, Pharmaceutical methods Drug development Drugs Structure-activity relationships Models, Molecular Pharmaceutical Preparations metabolism Pharmacokinetics Pharmakokinetik (DE-588)4115557-9 gnd Arzneimittelentwicklung (DE-588)4143176-5 gnd |
| topic_facet | Chemistry, Pharmaceutical methods Drug development Drugs Structure-activity relationships Models, Molecular Pharmaceutical Preparations metabolism Pharmacokinetics Pharmakokinetik Arzneimittelentwicklung Aufsatzsammlung |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=2945638&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015755204&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV035418617 |
| work_keys_str_mv | AT mannholdraimund moleculardrugpropertiesmeasurementandprediction |