Molecular Modeling and Prediction of Bioactivity

000 - 55D3E1D654E6DB79055661A467DBA2.pdf......Page 1
Subject Index......Page 0
001 - 53145B4E422A6DBC13D1821DEB8CF7.pdf......Page 4
Section 1. Overview......Page 14
Receptor Structure - Molecular Detail......Page 15
Electron Crystallography - The Tubulin Dimer......Page 17
SAR by NMR......Page 18
Mixed Dopamine Antagonists and Serotonin Agonists......Page 19
Vasopressin Antagonists......Page 23
Generalization......Page 24
Drug Oral Activity......Page 25
Predictions......Page 26
The Human Factor......Page 27
Conclusions......Page 28
References......Page 29
Section 2. New Developments and Applications of Multivariate QSAR......Page 36
Abstract......Page 37
1.2 Some Nagging Difficulties......Page 38
2.1 Parameterization......Page 39
2.4 The Mathematical Form of the Model......Page 40
3.1 A "QSAR"......Page 41
4. Statistical Molecular Design - SMD......Page 43
4.1 A Better "QSAR"......Page 44
5. Multivariate Analysis by Means of Projections......Page 46
5.2 A Combinatorial Chemistry Application......Page 47
5.4 Some Bioinformatics Applications......Page 50
References......Page 53
Introduction......Page 56
Molecular Descriptors......Page 57
Results, Correlation, and Prediction......Page 59
References......Page 61
Introduction......Page 62
Results and Discussion......Page 63
Computational Methods......Page 66
References......Page 67
Molecular Descriptors......Page 68
Data......Page 70
Results......Page 71
References......Page 73
Illustration......Page 74
Modelling Approaches and Data Analytical Methods......Page 75
Results......Page 76
Discussion......Page 77
References......Page 79
Section 3. The Future of 3D-QSAR......Page 80
Chemical Model: 3D Grid Map......Page 81
Multiblock Methods......Page 83
Interactive Plots......Page 84
References......Page 88
Introduction......Page 90
Methodology......Page 91
Flexible Alignment of Protein Structures......Page 93
References......Page 94
Introduction......Page 96
The Volsurf^2 Descriptors......Page 97
Correlations with Pharmacokinetic Data......Page 98
References......Page 101
Introduction......Page 102
Rank Transform......Page 103
Distribution Factor......Page 104
Results......Page 106
References......Page 107
Section 4. Prediction of Ligand-Protein Binding......Page 108
Knowledge-based Approaches to Protein-Ligand Recognition Principles......Page 109
Computer-based Lead Finding for t-RNA Guanosine Transglycosylase Inhibitors......Page 110
Scoring of Putative Hits in Lead Finding......Page 111
Experimental Characterization of the Ligand Binding Process......Page 112
Correlation of Ligand Properties with Binding Affinity and Selectivity......Page 113
References......Page 115
Use of Mid-derived Shape Descriptors as a Novel Way to Predict the in Vivo Activity of Flexible Molecules - The Case of New Immunosuppessive Peptides......Page 117
Introduction......Page 118
Materials and Methods......Page 119
Results and Discussions......Page 121
References......Page 126
3D-QSAR for MMP-3 and MMP-8 Affinity......Page 128
Comparison With Receptor Topology......Page 130
Understanding Ligand Selectivity......Page 131
References......Page 133
Introduction......Page 134
Docking in Condensed Phases......Page 135
Fractional Representation of Solvation......Page 138
References......Page 139
Introduction......Page 140
Pharmacophore Generation......Page 141
Pseudoreceptor Model of the Resting State......Page 142
References......Page 145
Introduction......Page 146
Molecular Electrostatic Potential Analysis......Page 147
References......Page 151
Section 5. Computational Aspects of Molecular Diversity and Combinatorial Libraries......Page 152
Introduction......Page 153
The Data......Page 154
The Analysis Method: Recursive Partitioning......Page 156
Example......Page 157
Sequential Screening......Page 158
Multivariate Scam......Page 159
References......Page 160
Introduction......Page 161
Neural Networks......Page 162
Coding the Constitution......Page 163
3D Structure......Page 164
Conformational Flexibility......Page 166
Molecular Surfaces......Page 167
Acknowledgements......Page 170
References......Page 171
Introduction......Page 173
Fragment Based Screening......Page 174
Determining a Screening Fragment......Page 175
Results......Page 176
References......Page 178
Simple Molecular Representations......Page 179
Molecular Hologram Generation......Page 180
Simulation of Combinatorial Discovery......Page 181
Benzodiazepine Virtual Receptor......Page 182
References......Page 183
Section 6. Affinity and Efficacy Models of G-Protein Coupled Receptors......Page 185
5-HT1A Receptors Mapping by Conformational Analysis (2D NOESYM) and "Threewaymodelling" (HASL, CoMFA, PARM)......Page 186
NMR Conformational Analysis......Page 187
3D-QSAR......Page 189
Results and Discussions......Page 190
References......Page 196
Introduction......Page 198
Methods......Page 199
Results and Discussion......Page 201
References......Page 203
Introduction......Page 204
Computational Methods......Page 205
Superimposition of CP55244 and WIN55212-2......Page 206
Proposed Cannabinoid Receptor Map......Page 207
References......Page 208
Introduction......Page 210
ACC Description......Page 211
PLS Analysis......Page 213
Conclusions......Page 214
References......Page 215
Section 7. New Methods in Drug Discovery......Page 216
Methodology......Page 217
Results and Discussion......Page 218
Isomers Predictions......Page 220
Acknowledgements......Page 221
References......Page 222
Hydrogen Bond Contributions to Properties and Activities of Chemicals and Drugs......Page 223
Acknowledgements......Page 228
References......Page 229
Section 8. Modeling of Membrane Penetration......Page 230
Introduction......Page 231
Design of Model Peptides......Page 232
Statistical Analysis......Page 233
Results......Page 234
Acknowledgements......Page 235
References......Page 236
Introduction......Page 237
Molecular Properties and Bioavailability......Page 238
Physicochemical High Throughput Screening (pC-HTS) in the Description of Aspects Bioavailability......Page 239
Acknowledgements......Page 242
References......Page 243
Methods......Page 244
Calculation of Parameters to Develop Quantitative Structure-Property Relationships......Page 245
Conclusions......Page 246
References......Page 247
Introduction......Page 248
Descriptor Generation and Analysis......Page 249
Computational Neural Networks......Page 250
Results and Discussion......Page 251
References......Page 253
Section 9. Poster Presentation......Page 255
Poster Session I: New Developments and Applications of Multivariate QSAR......Page 256
Free-Wilson-Type QSAR Anayses Using Linear and Nonlinear Regression Techniques......Page 257
References......Page 258
Introduction......Page 259
References......Page 260
Results......Page 261
References......Page 262
World Wide Web-Based Calculations of Subsituent Parameters for QSAR Studies......Page 263
References......Page 264
Results......Page 265
References......Page 266
Limiting Case B: Inside Model, Outside Y range......Page 267
References......Page 268
Introduction......Page 269
References......Page 270
Materials and Methods......Page 271
Results and Discussion......Page 272
"Classical" and Quantum Mechanical Descriptors for Phenolic Inhibition of Bacterial Growth......Page 273
EVA Results......Page 274
References......Page 275
Results and Discussion......Page 276
References......Page 277
Development and Validation of a Novel Variable Selection Technique with Application to QSAR Studies......Page 278
Methods......Page 280
References......Page 281
Materials and Methods......Page 282
References......Page 283
Results......Page 284
References......Page 285
Materials and Methods......Page 286
References......Page 287
References......Page 288
Method......Page 289
References and Notes......Page 290
Methodology......Page 291
References......Page 292
Results and Discussion......Page 293
References......Page 294
Methods......Page 295
References......Page 296
The Portsmouth Formulation of Joint Continuum Regression......Page 297
References......Page 298
CoMFA Analysis of Pyrethroid Insecticides......Page 299
References......Page 300
Results and Discussion......Page 301
References......Page 302
Data and Methods......Page 303
References......Page 304
Poster Session II: The Future of 3D-QSAR......Page 305
Partition Coefficients of Binary Mixtures of Chemicals: Possibility for the QSAR Analysis......Page 306
Acknowledgement......Page 308
Method......Page 309
References......Page 310
Antileishmanial Chalcones: Statistical Design and 3D-QSAR Analysis......Page 311
Methods and Results......Page 313
References......Page 315
Combine and Grid/Golpe Analyses......Page 316
References......Page 317
Methods......Page 318
References......Page 319
NMR Analysis......Page 320
Molecular Modelling......Page 322
References......Page 323
Combine Analysis......Page 324
References......Page 325
"Classical EVA"......Page 326
EVA_GA......Page 327
References......Page 328
3D-QSAR, Grid Descriptors and Chemometric Tools in the Development of Selective Antagonists of Muscarinic Receptor......Page 329
Small Cyclic Peptide SAR Study Using APEX-3D System: Somatostatin Receptor Type 2 (SSTR2) Specific Pharmacophores......Page 331
References......Page 332
COMFA Analysis......Page 333
References......Page 334
Molecular Similarity Analysis and 3D-QSAR of Neonicotinoid Insecticides......Page 335
References......Page 336
Materials and Methods......Page 337
Results and Discussion......Page 338
Reference......Page 339
Discussion......Page 340
References......Page 341
Introduction......Page 342
References......Page 343
Methodolopv of the 3D-OSAR CoMFA Studv......Page 344
Poster Session III: Prediction of Ligand-Protein Binding......Page 346
Reversible Inhibition of MAO-A and B by Diazoheterocyclic Compounds: Development of QSAR/CoMFA Models......Page 347
References......Page 348
5-HT2A Receptor Model Building......Page 349
References......Page 350
Results and Discussion......Page 351
References......Page 352
Results and Discussion......Page 353
References......Page 354
Methods and Results......Page 355
References......Page 356
Elucidation of Active Conformations of Drugs Using Conformer Sampling by Molecular Dynamics Calculations and Molecular Overlay......Page 357
References......Page 358
Results......Page 359
References......Page 360
Results......Page 361
References......Page 362
Results and Discussion......Page 363
References......Page 364
Procedure and Results......Page 365
References......Page 366
Conformational Analysis......Page 367
References......Page 368
Introduction......Page 369
Results and Discussion......Page 370
Introduction......Page 371
Acknowledgements......Page 372
References......Page 373
Introduction......Page 374
References......Page 375
Results......Page 376
References......Page 377
Introduction......Page 378
References......Page 379
Conformation and Receptor Binding......Page 380
References......Page 381
Introduction......Page 382
References......Page 383
Results and Discussion......Page 384
Acknowledgements......Page 385
References......Page 386
Protocol......Page 387
Conclusions......Page 388
Introduction......Page 389
References......Page 390
Methods......Page 391
References......Page 392
Introduction......Page 393
References......Page 394
Quantitative Structure-Function Relationships......Page 395
Computational Site-Directed Mutagenesis......Page 396
References......Page 397
Introduction......Page 398
Conclusions......Page 399
Binding by Entropic Trapping......Page 400
References......Page 401
Results and Discussion......Page 402
References......Page 403
Results......Page 404
References......Page 405
Results......Page 406
References......Page 407
Results and Discussion......Page 408
References......Page 409
Results and Discussion......Page 410
References......Page 411
The Electron-Topological Method (ETM): Its Further Development and Use in the Problems of SAR Study......Page 412
Acknowledgments......Page 413
Poster Session IV: Computational Aspects of Molecular Diversity and Combinatorial Libraries......Page 414
MOLDIVS - A New Program for Molecular Similarity and Diversity Calculations......Page 415
Introduction......Page 417
References......Page 418
Topological Analysi of 3D Smoothed Electron Density Maps......Page 419
References......Page 420
A Decision Tree Learning Approach for the Classification and Analysis of High-Throughput Screening Data......Page 421
Poster Session V: Affinity and Efficacy Models of G-Protein Coupled Receptors......Page 423
Application of Parm to Constructing and Comparing 5-HT1A and alpha1 Receptor Models......Page 424
References......Page 430
Method......Page 431
References......Page 432
Analysis of HIV Protease Inhibitors......Page 433
References......Page 434
Methods......Page 435
References......Page 436
Application of Artificial Neural Networks in QSAR of a New Model of Phenylpiperazine Derivatives1 with Affinity for 5-HT1a and alpha1 Receptors: A Comparison of Ann Models......Page 437
Results......Page 439
Bibliography......Page 440
Poster Session VI: Discovery 4 New Methods in Drug......Page 441
Technique, Results and Discussion......Page 442
Property Patches in GPCRS: A Multivariate Study......Page 444
References......Page 446
Method......Page 447
References......Page 448
Molecular Field Topology Analysi (MFTA) as the Basis for Molecular Design......Page 449
References......Page 450
Rank Distance Clustering......Page 451
References......Page 452
Methods......Page 453
References......Page 454
Data Description......Page 455
References......Page 456
Main Results......Page 457
References......Page 458
Methods......Page 459
References......Page 460
Methods and Datasets......Page 461
References......Page 462
Introduction......Page 463
Reference......Page 464
Rodent Tumor Profiles Induced by 536 Chemicals Carcinogens: An Information Intensive Analysis......Page 465
Set of Studied Molecules......Page 467
Acknowledgements......Page 468
Methodology......Page 469
References......Page 470
Optimization Geometries Procedures......Page 471
Conclusions......Page 472
Stereoelectronic and Conformational Properties of Zolpidem......Page 473
Elaboration of an Interaction Model......Page 474
Poster Session VII: Modelling of Membrane Penetration......Page 475
Slipper - A New Program for Water Solubility, Lipophilicity and Permeability Prediction......Page 476
References......Page 477
Methods......Page 478
References......Page 479
Material and Methods......Page 480
Reference......Page 481
Determination of Accurate Thermodynamics of Binding for Proteinase-Inhibitor Interactions......Page 482
References......Page 483
018 - 415D3B5BE7FAF614D44E2245FBCA971.pdf......Page 484